First Comprehensive In Silico Analysis of the Functional and Structural Consequences of SNPs in Human GalNAc-T1 Gene

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Hussein Sheikh Ali Mohamoud

2014-01-01

Full Text Available GalNAc-T1, a key candidate of GalNac-transferases genes family that is involved in mucin-type O-linked glycosylation pathway, is expressed in most biological tissues and cell types. Despite the reported association of GalNAc-T1 gene mutations with human disease susceptibility, the comprehensive computational analysis of coding, noncoding and regulatory SNPs, and their functional impacts on protein level, still remains unknown. Therefore, sequence- and structure-based computational tools were employed to screen the entire listed coding SNPs of GalNAc-T1 gene in order to identify and characterize them. Our concordant in silico analysis by SIFT, PolyPhen-2, PANTHER-cSNP, and SNPeffect tools, identified the potential nsSNPs (S143P, G258V, and Y414D variants from 18 nsSNPs of GalNAc-T1. Additionally, 2 regulatory SNPs (rs72964406 and #x26; rs34304568 were also identified in GalNAc-T1 by using FastSNP tool. Using multiple computational approaches, we have systematically classified the functional mutations in regulatory and coding regions that can modify expression and function of GalNAc-T1 enzyme. These genetic variants can further assist in better understanding the wide range of disease susceptibility associated with the mucin-based cell signalling and pathogenic binding, and may help to develop novel therapeutic elements for associated diseases.

Modeling Dynamic Regulatory Processes in Stroke

Science.gov (United States)

McDermott, Jason E.; Jarman, Kenneth; Taylor, Ronald; Lancaster, Mary; Shankaran, Harish; Vartanian, Keri B.; Stevens, Susan L.; Stenzel-Poore, Mary P.; Sanfilippo, Antonio

2012-01-01

The ability to examine the behavior of biological systems in silico has the potential to greatly accelerate the pace of discovery in diseases, such as stroke, where in vivo analysis is time intensive and costly. In this paper we describe an approach for in silico examination of responses of the blood transcriptome to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) from the data relating these functional clusters to each other in terms of their regulatory influence on one another. Dynamic models were developed by coupling these ODEs into a model that simulates the expression of regulated functional clusters. By changing the magnitude of gene expression in the initial input state it was possible to assess the behavior of the networks through time under varying conditions since the dynamic model only requires an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. We discuss the implications of our models on neuroprotection in stroke, explore the limitations of the approach, and report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different neuroprotective paradigms. PMID:23071432

Comparative analysis of chromatin landscape in regulatory regions of human housekeeping and tissue specific genes

Directory of Open Access Journals (Sweden)

Dasgupta Dipayan

2005-05-01

Full Text Available Abstract Background Global regulatory mechanisms involving chromatin assembly and remodelling in the promoter regions of genes is implicated in eukaryotic transcription control especially for genes subjected to spatial and temporal regulation. The potential to utilise global regulatory mechanisms for controlling gene expression might depend upon the architecture of the chromatin in and around the gene. In-silico analysis can yield important insights into this aspect, facilitating comparison of two or more classes of genes comprising of a large number of genes within each group. Results In the present study, we carried out a comparative analysis of chromatin characteristics in terms of the scaffold/matrix attachment regions, nucleosome formation potential and the occurrence of repetitive sequences, in the upstream regulatory regions of housekeeping and tissue specific genes. Our data show that putative scaffold/matrix attachment regions are more abundant and nucleosome formation potential is higher in the 5' regions of tissue specific genes as compared to the housekeeping genes. Conclusion The differences in the chromatin features between the two groups of genes indicate the involvement of chromatin organisation in the control of gene expression. The presence of global regulatory mechanisms mediated through chromatin organisation can decrease the burden of invoking gene specific regulators for maintenance of the active/silenced state of gene expression. This could partially explain the lower number of genes estimated in the human genome.

Regenerative orthopaedics: in vitro, in vivo...in silico.

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Geris, Liesbet

2014-09-01

In silico, defined in analogy to in vitro and in vivo as those studies that are performed on a computer, is an essential step in problem-solving and product development in classical engineering fields. The use of in silico models is now slowly easing its way into medicine. In silico models are already used in orthopaedics for the planning of complicated surgeries, personalised implant design and the analysis of gait measurements. However, these in silico models often lack the simulation of the response of the biological system over time. In silico models focusing on the response of the biological systems are in full development. This review starts with an introduction into in silico models of orthopaedic processes. Special attention is paid to the classification of models according to their spatiotemporal scale (gene/protein to population) and the information they were built on (data vs hypotheses). Subsequently, the review focuses on the in silico models used in regenerative orthopaedics research. Contributions of in silico models to an enhanced understanding and optimisation of four key elements-cells, carriers, culture and clinics-are illustrated. Finally, a number of challenges are identified, related to the computational aspects but also to the integration of in silico tools into clinical practice.

An integer optimization algorithm for robust identification of non-linear gene regulatory networks

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Chemmangattuvalappil Nishanth

2012-09-01

Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters

Applicability of in silico genotoxicity models on food and feed ingredients.

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Vuorinen, Anna; Bellion, Phillip; Beilstein, Paul

2017-11-01

Evaluation of the genotoxic potential of food and feed ingredients is required in the development of new substances and for their registration. In addition to in vitro and in vivo assays, in silico tools such as expert alert-based and statistical models can be used for data generation. These in silico models are commonly used among the pharmaceutical industry, whereas the food industry has not widely adopted them. In this study, the applicability of in silico tools for predicting genotoxicity was evaluated, with a focus on bacterial mutagenicity, in vitro and in vivo chromosome damage assays. For this purpose, a test set of 27 food and feed ingredients including vitamins, carotenoids, and nutraceuticals with experimental genotoxicity data was constructed from proprietary data. This dataset was run through multiple models and the model applicability was analyzed. The compounds were generally within the applicability domain of the models and the models predicted the compounds correctly in most of the cases. Although the regulatory acceptance of in silico tools as single data source is still limited, the models are applicable and can be used in the safety evaluation of food and feed ingredients. Copyright © 2017 Elsevier Inc. All rights reserved.

Phenotype prediction for mucopolysaccharidosis type I by in silico analysis.

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Ou, Li; Przybilla, Michael J; Whitley, Chester B

2017-07-04

Mucopolysaccharidosis type I (MPS I) is an autosomal recessive disease due to deficiency of α-L-iduronidase (IDUA), a lysosomal enzyme that degrades glycosaminoglycans (GAG) heparan and dermatan sulfate. To achieve optimal clinical outcomes, early and proper treatment is essential, which requires early diagnosis and phenotype severity prediction. To establish a genotype/phenotype correlation of MPS I disease, a combination of bioinformatics tools including SIFT, PolyPhen, I-Mutant, PROVEAN, PANTHER, SNPs&GO and PHD-SNP are utilized. Through analyzing single nucleotide polymorphisms (SNPs) by these in silico approaches, 28 out of 285 missense SNPs were predicted to be damaging. By integrating outcomes from these in silico approaches, a prediction algorithm (sensitivity 94%, specificity 80%) was thereby developed. Three dimensional structural analysis of 5 candidate SNPs (P533R, P496R, L346R, D349G, T374P) were performed by SWISS PDB viewer, which revealed specific structural changes responsible for the functional impacts of these SNPs. Additionally, SNPs in the untranslated region were analyzed by UTRscan and PolymiRTS. Moreover, by investigating known pathogenic mutations and relevant patient phenotypes in previous publications, phenotype severity (severe, intermediate or mild) of each mutation was deduced. Collectively, these results identified potential candidate SNPs with functional significance for studying MPS I disease. This study also demonstrates the effectiveness, reliability and simplicity of these in silico approaches in addressing complexity of underlying genetic basis of MPS I disease. Further, a step-by-step guideline for phenotype prediction of MPS I disease is established, which can be broadly applied in other lysosomal diseases or genetic disorders.

An in silico approach reveals associations between genetic and epigenetic factors within regulatory elements in B cells from primary Sjögren’s syndrome patients

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Orsia D. Konsta

2015-08-01

Full Text Available Recent advances in genetics have highlighted several regions and candidate genes associated with primary Sjögren's syndrome (SS, a systemic autoimmune epithelitis that combines exocrine gland dysfunctions, and focal lymphocytic infiltrations. In addition to genetic factors, it is now clear that epigenetic deregulations are present during SS and restricted to specific cell type subsets such as lymphocytes and salivary gland epithelial cells. In this study, 72 single nucleotide polymorphisms (SNPs associated with 43 SS gene risk factors were selected from publicly available and peer reviewed literature for further in silico analysis. SS risk variant location was tested revealing a broad distribution in coding sequences (5.6%, intronic sequences (55.6%, upstream/downstream genic regions (30.5%, and intergenic regions (8.3%. Moreover, a significant enrichment of regulatory motifs (promoter, enhancer, insulator, DNAse peak and eQTL characterizes SS risk variants (94.4%. Next, screening SNPs in high linkage disequilibrium (r2 ≥ 0.8 in Caucasians revealed 645 new variants including 5 SNPs with missense mutations, and indicated an enrichment of transcriptionally active motifs according to the cell type (B cells > monocytes > T cells >> A549. Finally, we looked at SS risk variants for histone markers in B cells (GM12878, monocytes (CD14+ and epithelial cells (A548. Active histone markers were associated with SS risk variants at both promoters and enhancers in B cells, and within enhancers in monocytes. In conclusion and based on the obtained in silico results, that need further confirmation, associations were observed between SS genetic risk factors and epigenetic factors and these associations predominate in B cells such as those observed at the FAM167A-BLK locus.

In silico analysis of cis-acting regulatory elements in 5' regulatory regions of sucrose transporter gene families in rice (Oryza sativa Japonica) and Arabidopsis thaliana.

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Ibraheem, Omodele; Botha, Christiaan E J; Bradley, Graeme

2010-12-01

The regulation of gene expression involves a multifarious regulatory system. Each gene contains a unique combination of cis-acting regulatory sequence elements in the 5' regulatory region that determines its temporal and spatial expression. Cis-acting regulatory elements are essential transcriptional gene regulatory units; they control many biological processes and stress responses. Thus a full understanding of the transcriptional gene regulation system will depend on successful functional analyses of cis-acting elements. Cis-acting regulatory elements present within the 5' regulatory region of the sucrose transporter gene families in rice (Oryza sativa Japonica cultivar-group) and Arabidopsis thaliana, were identified using a bioinformatics approach. The possible cis-acting regulatory elements were predicted by scanning 1.5kbp of 5' regulatory regions of the sucrose transporter genes translational start sites, using Plant CARE, PLACE and Genomatix Matinspector professional databases. Several cis-acting regulatory elements that are associated with plant development, plant hormonal regulation and stress response were identified, and were present in varying frequencies within the 1.5kbp of 5' regulatory region, among which are; A-box, RY, CAT, Pyrimidine-box, Sucrose-box, ABRE, ARF, ERE, GARE, Me-JA, ARE, DRE, GA-motif, GATA, GT-1, MYC, MYB, W-box, and I-box. This result reveals the probable cis-acting regulatory elements that possibly are involved in the expression and regulation of sucrose transporter gene families in rice and Arabidopsis thaliana during cellular development or environmental stress conditions. Copyright © 2010 Elsevier Ltd. All rights reserved.

Large Dataset of Acute Oral Toxicity Data Created for Testing in Silico Models (ASCCT meeting)

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Acute toxicity data is a common requirement for substance registration in the US. Currently only data derived from animal tests are accepted by regulatory agencies, and the standard in vivo tests use lethality as the endpoint. Non-animal alternatives such as in silico models are ...

In silico analysis of bacterial arsenic islands reveals remarkable synteny and functional relatedness between arsenate and phosphate

DEFF Research Database (Denmark)

Li, Hang; Li, Mingshun; Huang, Yinyan

2013-01-01

In order to construct a more universal model for understanding the genetic requirements for bacterial AsIII oxidation, an in silico examination of the available sequences in the GenBank was assessed and revealed 21 conserved 5-71 kb arsenic islands within phylogenetically diverse bacterial genomes....... The arsenic islands included the AsIII oxidase structural genes aioBA, ars operons (e.g., arsRCB) which code for arsenic resistance, and pho, pst, and phn genes known to be part of the classical phosphate stress response and that encode functions associated with regulating and acquiring organic and inorganic...... phosphorus. The regulatory genes aioXSR were also an island component, but only in Proteobacteria and orientated differently depending on whether they were in a-Proteobacteria or β-/γ-Proteobacteria. Curiously though, while these regulatory genes have been shown to be essential to AsIII oxidation...

[Pharmacological mechanism analysis of oligopeptide from Pinctada fucata based on in silico proteolysis and protein interaction network].

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Chen, Yan-Kun; Qiao, Lian-Sheng; Huo, Xiao-Qian; Zhang, Xu; Han, Na; Zhang, Yan-Ling

2017-09-01

Pinctada fucata oligopeptide is one of key pharmaceutical effective constituents of P. fucata. It is significant to analyze its pharmacological effect and mechanism. This study aims to discover the potential oligopeptides from P. fucata and analyze the mechanism of P. fucata oligopeptide based on in silico technologies and protein interaction network(PIN). First, main protein sequences of P. fucata were collected, and oligopeptides were obtained using in silico gastrointestinal tract proteolysis. Then, key potential targets of P. fucata oligopeptides were obtained through pharmacophore screening. The protein-protein interaction(PPI) of targets was achieved and implemented to construct PIN and analyze the mechanism of P. fucata oligopeptides. P. fucata oligopeptide database was constructed based on in silico technologies, including 458 oligopeptides. Twelve modules were identified from PIN by a graph theoretic clustering algorithm Molecular Complex Detection(MCODE) and analyzed by Gene ontology(GO) enrichment. The results indicated that P. fucata oligopeptides have an effect in treating neurological diseases, such as Alzheimer's disease. In silico proteolysis could be used to analyze the protein sequences of traditional Chinese medicine(TCM). According to the combination of in silico proteolysis and PIN, the biological activity of oligopeptides could be interpreted rapidly based on the known TCM protein sequence. The study provides the methodology basis for rapidly and efficiently implementing the mechanism analysis of TCM oligopeptides. Copyright© by the Chinese Pharmaceutical Association.

In silico assessment of biomedical products: The conundrum of rare but not so rare events in two case studies.

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Viceconti, Marco; Cobelli, Claudio; Haddad, Tarek; Himes, Adam; Kovatchev, Boris; Palmer, Mark

2017-05-01

In silico clinical trials, defined as "The use of individualized computer simulation in the development or regulatory evaluation of a medicinal product, medical device, or medical intervention," have been proposed as a possible strategy to reduce the regulatory costs of innovation and the time to market for biomedical products. We review some of the the literature on this topic, focusing in particular on those applications where the current practice is recognized as inadequate, as for example, the detection of unexpected severe adverse events too rare to be detected in a clinical trial, but still likely enough to be of concern. We then describe with more details two case studies, two successful applications of in silico clinical trial approaches, one relative to the University of Virginia/Padova simulator that the Food and Drug Administration has accepted as possible replacement for animal testing in the preclinical assessment of artificial pancreas technologies, and the second, an investigation of the probability of cardiac lead fracture, where a Bayesian network was used to combine in vivo and in silico observations, suggesting a whole new strategy of in silico-augmented clinical trials, to be used to increase the numerosity where recruitment is impossible, or to explore patients' phenotypes that are unlikely to appear in the trial cohort, but are still frequent enough to be of concern.

Antimicrobial Peptides of Meat Origin - An In silico and In vitro Analysis.

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Keska, Paulina; Stadnik, Joanna

2017-01-01

The aim of this study was to evaluate the antimicrobial activity of meat protein-derived peptides against selected Gram-positive and Gram-negative bacteria. The in silico and in vitro approach was combined to determine the potency of antimicrobial peptides derived from pig (Sus scrofa) and cow (Bos taurus) proteins. The in silico studies consisted of an analysis of the amino acid composition of peptides obtained from the CAMPR database, their molecular weight and other physicochemical properties (isoelectric point, molar extinction coefficient, instability index, aliphatic index, hydropathy index and net charge). The degree of similarity was estimated between the antimicrobial peptide sequences derived from the slaughtered animals and the main meat proteins. Antimicrobial activity of peptides isolated from dry-cured meat products was analysed (in vitro) against two strains of pathogenic bacteria using the disc diffusion method. There was no evidence of growthinhibitory properties of peptides isolated from dry-cured meat products against Escherichia coli K12 ATCC 10798 and Staphylococcus aureus ATCC 25923. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Genotype, phenotype and in silico pathogenicity analysis of HEXB mutations: Panel based sequencing for differential diagnosis of gangliosidosis.

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Mahdieh, Nejat; Mikaeeli, Sahar; Tavasoli, Ali Reza; Rezaei, Zahra; Maleki, Majid; Rabbani, Bahareh

2018-04-01

Gangliosidosis is an inherited metabolic disorder causing neurodegeneration and motor regression. Preventive diagnosis is the first choice for the affected families due to lack of straightforward therapy. Genetic studies could confirm the diagnosis and help families for carrier screening and prenatal diagnosis. An update of HEXB gene variants concerning genotype, phenotype and in silico analysis are presented. Panel based next generation sequencing and direct sequencing of four cases were performed to confirm the clinical diagnosis and for reproductive planning. Bioinformatic analyses of the HEXB mutation database were also performed. Direct sequencing of HEXA and HEXB genes showed recurrent homozygous variants at c.509G>A (p.Arg170Gln) and c.850C>T (p.Arg284Ter), respectively. A novel variant at c.416T>A (p.Leu139Gln) was identified in the GLB1 gene. Panel based next generation sequencing was performed for an undiagnosed patient which showed a novel mutation at c.1602C>A (p.Cys534Ter) of HEXB gene. Bioinformatic analysis of the HEXB mutation database showed 97% consistency of in silico genotype analysis with the phenotype. Bioinformatic analysis of the novel variants predicted to be disease causing. In silico structural and functional analysis of the novel variants showed structural effect of HEXB and functional effect of GLB1 variants which would provide fast analysis of novel variants. Panel based studies could be performed for overlapping symptomatic patients. Consequently, genetic testing would help affected families for patients' management, carrier detection, and family planning's. Copyright © 2018 Elsevier B.V. All rights reserved.

Interaction of silico-12-molybdic acid with acetone

International Nuclear Information System (INIS)

Chuvaev, V.F.; Pinchuk, I.N.; Gubin, V.V.

1984-01-01

Methods of thermal analysis, mass-spectrometry, IR, PMR, ESR spectroscopy are used to investigate interaction processes of silico-12-molybdic acid H 4 SiMo 12 O 40 with acetone. Reactions in solution and with participation of solid heteropolyacid are studied. Organic products of catalytic and oxidation-reduction reactions are identified. The effect of conditions on the formation of different condensation and oxidation products and the sequence of appropriate reactions is discussed. Transformations of silico-12-molybolic acid are considered

Genome wide in silico SNP-tumor association analysis

International Nuclear Information System (INIS)

Qiu, Ping; Wang, Luquan; Kostich, Mitch; Ding, Wei; Simon, Jason S; Greene, Jonathan R

2004-01-01

Carcinogenesis occurs, at least in part, due to the accumulation of mutations in critical genes that control the mechanisms of cell proliferation, differentiation and death. Publicly accessible databases contain millions of expressed sequence tag (EST) and single nucleotide polymorphism (SNP) records, which have the potential to assist in the identification of SNPs overrepresented in tumor tissue. An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106). A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigation This novel in silico approach can assist in prioritization of genes and SNPs in the effort to elucidate the genetic mechanisms underlying the development of cancer

Unveiling combinatorial regulation through the combination of ChIP information and in silico cis-regulatory module detection

Science.gov (United States)

Sun, Hong; Guns, Tias; Fierro, Ana Carolina; Thorrez, Lieven; Nijssen, Siegfried; Marchal, Kathleen

2012-01-01

Computationally retrieving biologically relevant cis-regulatory modules (CRMs) is not straightforward. Because of the large number of candidates and the imperfection of the screening methods, many spurious CRMs are detected that are as high scoring as the biologically true ones. Using ChIP-information allows not only to reduce the regions in which the binding sites of the assayed transcription factor (TF) should be located, but also allows restricting the valid CRMs to those that contain the assayed TF (here referred to as applying CRM detection in a query-based mode). In this study, we show that exploiting ChIP-information in a query-based way makes in silico CRM detection a much more feasible endeavor. To be able to handle the large datasets, the query-based setting and other specificities proper to CRM detection on ChIP-Seq based data, we developed a novel powerful CRM detection method ‘CPModule’. By applying it on a well-studied ChIP-Seq data set involved in self-renewal of mouse embryonic stem cells, we demonstrate how our tool can recover combinatorial regulation of five known TFs that are key in the self-renewal of mouse embryonic stem cells. Additionally, we make a number of new predictions on combinatorial regulation of these five key TFs with other TFs documented in TRANSFAC. PMID:22422841

Safety analysis - current and future regulatory challenges

Energy Technology Data Exchange (ETDEWEB)

Jamieson, T., E-mail: Terry.Jamieson@cnsc-ccsn.gc.ca [Canadian Nuclear Safety Commission, Ottawa, ON (Canada)

2015-07-01

'Full text:' The current and future regulatory challenges associated with deterministic safety analysis are reviewed, including: 1. The CNSC's and safety control areas. 2. Traditional safety analysis approach. 3. Experience gained and impact. 4. Current analysis and regulatory approaches. 5. Current status. 6. Complexity and challenges In particular, the technical, regulatory and strategic aspects of these challenges are discussed. (author)

Safety analysis - current and future regulatory challenges

International Nuclear Information System (INIS)

Jamieson, T.

2015-01-01

'Full text:' The current and future regulatory challenges associated with deterministic safety analysis are reviewed, including: 1. The CNSC's and safety control areas. 2. Traditional safety analysis approach. 3. Experience gained and impact. 4. Current analysis and regulatory approaches. 5. Current status. 6. Complexity and challenges In particular, the technical, regulatory and strategic aspects of these challenges are discussed. (author)

Eucalyptus microsatellites mined in silico

Indian Academy of Sciences (India)

https://www.ias.ac.in/article/fulltext/jgen/087/01/0021-0025 ... Eucalyptus is an important short rotation pulpy woody plant, grown widely in the tropics. ... In this study, in silico analysis of 15,285 sequences representing partial and full-length mRNA from Eucalyptus species for their use in developing SSRs or microsatellites ...

Towards prediction of metabolic products of polyketide synthases: an in silico analysis.

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Gitanjali Yadav

2009-04-01

Full Text Available Sequence data arising from an increasing number of partial and complete genome projects is revealing the presence of the polyketide synthase (PKS family of genes not only in microbes and fungi but also in plants and other eukaryotes. PKSs are huge multifunctional megasynthases that use a variety of biosynthetic paradigms to generate enormously diverse arrays of polyketide products that posses several pharmaceutically important properties. The remarkable conservation of these gene clusters across organisms offers abundant scope for obtaining novel insights into PKS biosynthetic code by computational analysis. We have carried out a comprehensive in silico analysis of modular and iterative gene clusters to test whether chemical structures of the secondary metabolites can be predicted from PKS protein sequences. Here, we report the success of our method and demonstrate the feasibility of deciphering the putative metabolic products of uncharacterized PKS clusters found in newly sequenced genomes. Profile Hidden Markov Model analysis has revealed distinct sequence features that can distinguish modular PKS proteins from their iterative counterparts. For iterative PKS proteins, structural models of iterative ketosynthase (KS domains have revealed novel correlations between the size of the polyketide products and volume of the active site pocket. Furthermore, we have identified key residues in the substrate binding pocket that control the number of chain extensions in iterative PKSs. For modular PKS proteins, we describe for the first time an automated method based on crucial intermolecular contacts that can distinguish the correct biosynthetic order of substrate channeling from a large number of non-cognate combinatorial possibilities. Taken together, our in silico analysis provides valuable clues for formulating rules for predicting polyketide products of iterative as well as modular PKS clusters. These results have promising potential for discovery of

Retention behavior of nickel, copper, cadmium and zinc ions from aqueous solutions on silico-titanate and silico-antimonate used as inorganic ion exchange materials

International Nuclear Information System (INIS)

Abou-Mesalam, M.M.

2002-01-01

Silico-titanate (SiTi) and silico-antimonate (SiSb) have been synthesized and characterized using X-ray diffraction patterns, infrared and thermal analysis techniques. Divalent cations such as Ni 2+ , Cd 2+ , Zn 2+ and Cu 2+ in the pH range 2 to 8 have been exchanged with the exchangeable active sites of the exchangers using a batch technique. From the results obtained, the equilibrium capacities and distribution coefficient values were calculated indicating high selectivity values for Ni 2+ , Cd 2+ , Zn 2+ and Cu 2+ ions on silico-titanate and silico-antimonate compared to other titanates and antimonates. Also SiTi and SiSb show high chemical stability in H 2 O, nitric and hydrochloric acids. All these results support the suitability of the prepared materials for the removal of the toxic metals concerned from waste waters. Based on the results obtained, practical separation experiments for the above mentioned cations on SiTi and SiSb columns from aqueous waste solutions were carried out. (author)

Altered retinal microRNA expression profiles in early diabetic retinopathy: an in silico analysis.

Science.gov (United States)

Xiong, Fen; Du, Xinhua; Hu, Jianyan; Li, Tingting; Du, Shanshan; Wu, Qiang

2014-07-01

MicroRNAs (miRNAs) - as negative regulators of target genes - are associated with various human diseases, but their precise role(s) in diabetic retinopathy (DR) remains to be elucidated. The aim of this study was to elucidate the involvement of miRNAs in early DR using in silico analysis to explore their gene expression patterns. We used the streptozotocin (STZ)-induced diabetic rat to investigate the roles of miRNAs in early DR. Retinal miRNA expression profiles from diabetic versus healthy control rats were examined by miRNA array analysis. Based on several bioinformatic systems, specifically, gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, we identified signatures of the potential pathological processes, gene functions, and signaling pathways that are influenced by dysregulated miRNAs. We used quantitative real-time polymerase chain reaction (qRT-PCR) to validate six (i.e. those with significant changes in expression levels) of the 17 miRNAs that were detected in the miRNA array. We also describe the significant role of the miRNA-gene network, which is based on the interactions between miRNAs and target genes. GO analysis of the 17 miRNAs detected in the miRNA array analysis revealed the most prevalent miRNAs to be those related to biological processes, olfactory bulb development and axonogenesis. These miRNAs also exert significant influence on additional pathways, including the mitogen-activated protein and calcium signaling pathways. Six of the seventeen miRNAs were chosen for qRT-PCR validation. With the exception of a slight difference in miRNA-350, our results are in close agreement with the differential expressions detected by array analysis. This study, which describes miRNA expression during the early developmental phases of DR, revealed extensive miRNA interactions. Based on both their target genes and signaling pathways, we suggest that miRNAs perform critical regulatory functions during the early stages of DR

Putative 3-nitrotyrosine detoxifying genes identified in the yeast Debaryomyces hansenii: In silico search of regulatory sequences responsive to salt and nitrogen stress

Directory of Open Access Journals (Sweden)

Daniela E. Castro

2017-09-01

Conclusions: D. hansenii can grow in the presence of 3-nitrotyrosine as the only nitrogen source and has a high specific denitrase activity to degrade 3-nitrotyrosine in 1 and 2 M NaCl stress conditions. The results suggest that given the lack of information on transcriptional factors in D. hansenii, the genes identified in our in silico analysis may help explain 3-nitrotyrosine assimilation mechanisms.

In-silico Metabolome Target Analysis Towards PanC-based Antimycobacterial Agent Discovery.

Science.gov (United States)

Khoshkholgh-Sima, Baharak; Sardari, Soroush; Izadi Mobarakeh, Jalal; Khavari-Nejad, Ramezan Ali

2015-01-01

Mycobacterium tuberculosis, the main cause of tuberculosis (TB), has still remained a global health crisis especially in developing countries. Tuberculosis treatment is a laborious and lengthy process with high risk of noncompliance, cytotoxicity adverse events and drug resistance in patient. Recently, there has been an alarming rise of drug resistant in TB. In this regard, it is an unmet need to develop novel antitubercular medicines that target new or more effective biochemical pathways to prevent drug resistant Mycobacterium. Integrated study of metabolic pathways through in-silico approach played a key role in antimycobacterial design process in this study. Our results suggest that pantothenate synthetase (PanC), anthranilate phosphoribosyl transferase (TrpD) and 3-isopropylmalate dehydratase (LeuD) might be appropriate drug targets. In the next step, in-silico ligand analysis was used for more detailed study of chemical tractability of targets. This was helpful to identify pantothenate synthetase (PanC, Rv3602c) as the best target for antimycobacterial design procedure. Virtual library screening on the best ligand of PanC was then performed for inhibitory ligand design. At the end, five chemical intermediates showed significant inhibition of Mycobacterium bovis with good selectivity indices (SI) ≥10 according to Tuberculosis Antimicrobial Acquisition & Coordinating Facility of US criteria for antimycobacterial screening programs.

In silico prediction of genotoxicity.

Science.gov (United States)

Wichard, Jörg D

2017-08-01

The in silico prediction of genotoxicity has made considerable progress during the last years. The main driver for the pharmaceutical industry is the ICH M7 guideline about the assessment of DNA reactive impurities. An important component of this guideline is the use of in silico models as an alternative approach to experimental testing. The in silico prediction of genotoxicity provides an established and accepted method that defines the first step in the assessment of DNA reactive impurities. This was made possible by the growing amount of reliable Ames screening data, the attempts to understand the activity pathways and the subsequent development of computer-based prediction systems. This paper gives an overview of how the in silico prediction of genotoxicity is performed under the ICH M7 guideline. Copyright © 2016 Elsevier Ltd. All rights reserved.

In silico analysis and verification of S100 gene expression in gastric cancer

International Nuclear Information System (INIS)

Liu, Ji; Li, Xue; Dong, Guang-Long; Zhang, Hong-Wei; Chen, Dong-Li; Du, Jian-Jun; Zheng, Jian-Yong; Li, Ji-Peng; Wang, Wei-Zhong

2008-01-01

The S100 protein family comprises 22 members whose protein sequences encompass at least one EF-hand Ca 2+ binding motif. They were involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation. However, the expression status of S100 family members in gastric cancer was not known yet. Combined with analysis of series analysis of gene expression, virtual Northern blot and microarray data, the expression levels of S100 family members in normal and malignant stomach tissues were systematically investigated. The expression of S100A3 was further evaluated by quantitative RT-PCR. At least 5 S100 genes were found to be upregulated in gastric cance by in silico analysis. Among them, four genes, including S100A2, S100A4, S100A7 and S100A10, were reported to overexpressed in gastric cancer previously. The expression of S100A3 in eighty patients of gastric cancer was further examined. The results showed that the mean expression levels of S100A3 in gastric cancer tissues were 2.5 times as high as in adjacent non-tumorous tissues. S100A3 expression was correlated with tumor differentiation and TNM (Tumor-Node-Metastasis) stage of gastric cancer, which was relatively highly expressed in poorly differentiated and advanced gastric cancer tissues (P < 0.05). To our knowledge this is the first report of systematic evaluation of S100 gene expressions in gastric cancers by multiple in silico analysis. The results indicated that overexpression of S100 gene family members were characteristics of gastric cancers and S100A3 might play important roles in differentiation and progression of gastric cancer

Radiology in silico-tuberculosis

International Nuclear Information System (INIS)

Otto, H.

1981-01-01

In spite of a decreasing number of new cases of silico-tuberculosis even today there still remains a serious complication of silicosis. The job of radiology is to recognise the disease, evaluate the course of the disease during therapy and classify the disease for compensation purposes. Due to the pathogenetic and pathomorphologic similarities of silicosis and tuberculosis, it is often difficult and sometimes even impossible to recognise the presence of tuberculosis in cases of silicoses or to identify and isolate the TB component in silico-tuberculosis. Careful consideration of all radiological and clinical parameters improves the accuracy of diagnosis. Since the radiographic examination provides the only method of evaluating the morphologic state of the disease, radiology will keep its central position in the diagnosis of silico-tuberculosis. (orig.) [de

Regulatory analysis technical evaluation handbook. Final report

International Nuclear Information System (INIS)

1997-01-01

The purpose of this Handbook is to provide guidance to the regulatory analyst to promote preparation of quality regulatory analysis documents and to implement the policies of the Regulatory Analysis Guidelines of the US Nuclear Regulatory Commission (NUREG/BR-0058 Rev. 2). This Handbook expands upon policy concepts included in the NRC Guidelines and translates the six steps in preparing regulatory analyses into implementable methodologies for the analyst. It provides standardized methods of preparation and presentation of regulatory analyses, with the inclusion of input that will satisfy all backfit requirements and requirements of NRC's Committee to Review Generic Requirements. Information on the objectives of the safety goal evaluation process and potential data sources for preparing a safety goal evaluation is also included. Consistent application of the methods provided here will result in more directly comparable analyses, thus aiding decision-makers in evaluating and comparing various regulatory actions. The handbook is being issued in loose-leaf format to facilitate revisions. NRC intends to periodically revise the handbook as new and improved guidance, data, and methods become available

In silico fragment-based drug design.

Science.gov (United States)

Konteatis, Zenon D

2010-11-01

In silico fragment-based drug design (FBDD) is a relatively new approach inspired by the success of the biophysical fragment-based drug discovery field. Here, we review the progress made by this approach in the last decade and showcase how it complements and expands the capabilities of biophysical FBDD and structure-based drug design to generate diverse, efficient drug candidates. Advancements in several areas of research that have enabled the development of in silico FBDD and some applications in drug discovery projects are reviewed. The reader is introduced to various computational methods that are used for in silico FBDD, the fragment library composition for this technique, special applications used to identify binding sites on the surface of proteins and how to assess the druggability of these sites. In addition, the reader will gain insight into the proper application of this approach from examples of successful programs. In silico FBDD captures a much larger chemical space than high-throughput screening and biophysical FBDD increasing the probability of developing more diverse, patentable and efficient molecules that can become oral drugs. The application of in silico FBDD holds great promise for historically challenging targets such as protein-protein interactions. Future advances in force fields, scoring functions and automated methods for determining synthetic accessibility will all aid in delivering more successes with in silico FBDD.

In silico analysis of cacao (Theobroma cacao L.) genes that involved in pathogen and disease responses

Science.gov (United States)

Agung, Muhammad Budi; Budiarsa, I. Made; Suwastika, I. Nengah

2017-02-01

Cocoa bean is one of the main commodities from Indonesia for the world, which still have problem regarding yield degradation due to pathogens and disease attack. Developing robust cacao plant that genetically resistant to pathogen and disease attack is an ideal solution in over taking on this problem. The aim of this study was to identify Theobroma cacao genes on database of cacao genome that homolog to response genes of pathogen and disease attack in other plant, through in silico analysis. Basic information survey and gene identification were performed in GenBank and The Arabidopsis Information Resource database. The In silico analysis contains protein BLAST, homology test of each gene's protein candidates, and identification of homologue gene in Cacao Genome Database using data source "Theobroma cacao cv. Matina 1-6 v1.1" genome. Identification found that Thecc1EG011959t1 (EDS1), Thecc1EG006803t1 (EDS5), Thecc1EG013842t1 (ICS1), and Thecc1EG015614t1 (BG_PPAP) gene of Cacao Genome Database were Theobroma cacao genes that homolog to plant's resistance genes which highly possible to have similar functions of each gene's homologue gene.

In Silico PCR Tools for a Fast Primer, Probe, and Advanced Searching.

Science.gov (United States)

Kalendar, Ruslan; Muterko, Alexandr; Shamekova, Malika; Zhambakin, Kabyl

2017-01-01

The polymerase chain reaction (PCR) is fundamental to molecular biology and is the most important practical molecular technique for the research laboratory. The principle of this technique has been further used and applied in plenty of other simple or complex nucleic acid amplification technologies (NAAT). In parallel to laboratory "wet bench" experiments for nucleic acid amplification technologies, in silico or virtual (bioinformatics) approaches have been developed, among which in silico PCR analysis. In silico NAAT analysis is a useful and efficient complementary method to ensure the specificity of primers or probes for an extensive range of PCR applications from homology gene discovery, molecular diagnosis, DNA fingerprinting, and repeat searching. Predicting sensitivity and specificity of primers and probes requires a search to determine whether they match a database with an optimal number of mismatches, similarity, and stability. In the development of in silico bioinformatics tools for nucleic acid amplification technologies, the prospects for the development of new NAAT or similar approaches should be taken into account, including forward-looking and comprehensive analysis that is not limited to only one PCR technique variant. The software FastPCR and the online Java web tool are integrated tools for in silico PCR of linear and circular DNA, multiple primer or probe searches in large or small databases and for advanced search. These tools are suitable for processing of batch files that are essential for automation when working with large amounts of data. The FastPCR software is available for download at http://primerdigital.com/fastpcr.html and the online Java version at http://primerdigital.com/tools/pcr.html .

In silico and in vivo analysis of Toxoplasma gondii epitopes by correlating survival data with peptide-MHC-I binding affinities.

Science.gov (United States)

Huang, Si-Yang; Jensen, Maria Risager; Rosenberg, Carina Agerbo; Zhu, Xing-Quan; Petersen, Eskild; Vorup-Jensen, Thomas

2016-07-01

Protein antigens comprising peptide motifs with high binding affinity to major histocompatibility complex class I (MHC-I) molecules are expected to induce a stronger cytotoxic T-lymphocyte response and thus provide better protection against infection with microorganisms where cytotoxic T-cells are the main effector arm of the immune system. Data on cyst formation and survival were extracted from past studies on the DNA immunization of mice with plasmids coding for Toxoplasma gondii antigens. From in silico analyses of the vaccine antigens, the correlation was tested between the predicted affinity for MHC-I molecules of the vaccine peptides and the survival of immunized mice after challenge with T. gondii. ELISPOT analysis was used for the experimental testing of peptide immunogenicity. Predictions for the Db MHC-I molecule produced a strong, negative correlation between survival and the dissociation constant of vaccine-derived peptides. The in silico analyses of nine T. gondii antigens identified peptides with a predicted dissociation constant in the interval from 10nM to 40μM. ELISPOT assays with splenocytes from T. gondii-infected mice further supported the importance of the peptide affinity for MHC-I. In silico analysis clearly helped the search for protective vaccine antigens. The ELISPOT analysis confirmed that the predicted T-cell epitopes were immunogenic by their ability to release interferon gamma in spleen cells. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods.

Science.gov (United States)

Schaffter, Thomas; Marbach, Daniel; Floreano, Dario

2011-08-15

Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data. However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks. Here, we describe a novel and comprehensive method for in silico benchmark generation and performance profiling of network inference methods available to the community as an open-source software called GeneNetWeaver (GNW). In addition to the generation of detailed dynamical models of gene regulatory networks to be used as benchmarks, GNW provides a network motif analysis that reveals systematic prediction errors, thereby indicating potential ways of improving inference methods. The accuracy of network inference methods is evaluated using standard metrics such as precision-recall and receiver operating characteristic curves. We show how GNW can be used to assess the performance and identify the strengths and weaknesses of six inference methods. Furthermore, we used GNW to provide the international Dialogue for Reverse Engineering Assessments and Methods (DREAM) competition with three network inference challenges (DREAM3, DREAM4 and DREAM5). GNW is available at http://gnw.sourceforge.net along with its Java source code, user manual and supporting data. Supplementary data are available at Bioinformatics online. dario.floreano@epfl.ch.

Propagating annotations of molecular networks using in silico fragmentation.

Science.gov (United States)

da Silva, Ricardo R; Wang, Mingxun; Nothias, Louis-Félix; van der Hooft, Justin J J; Caraballo-Rodríguez, Andrés Mauricio; Fox, Evan; Balunas, Marcy J; Klassen, Jonathan L; Lopes, Norberto Peporine; Dorrestein, Pieter C

2018-04-18

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.

In silico modeling of epigenetic-induced changes in photoreceptor cis-regulatory elements.

Science.gov (United States)

Hossain, Reafa A; Dunham, Nicholas R; Enke, Raymond A; Berndsen, Christopher E

2018-01-01

DNA methylation is a well-characterized epigenetic repressor of mRNA transcription in many plant and vertebrate systems. However, the mechanism of this repression is not fully understood. The process of transcription is controlled by proteins that regulate recruitment and activity of RNA polymerase by binding to specific cis-regulatory sequences. Cone-rod homeobox (CRX) is a well-characterized mammalian transcription factor that controls photoreceptor cell-specific gene expression. Although much is known about the functions and DNA binding specificity of CRX, little is known about how DNA methylation modulates CRX binding affinity to genomic cis-regulatory elements. We used bisulfite pyrosequencing of human ocular tissues to measure DNA methylation levels of the regulatory regions of RHO , PDE6B, PAX6 , and LINE1 retrotransposon repeats. To describe the molecular mechanism of repression, we used molecular modeling to illustrate the effect of DNA methylation on human RHO regulatory sequences. In this study, we demonstrate an inverse correlation between DNA methylation in regulatory regions adjacent to the human RHO and PDE6B genes and their subsequent transcription in human ocular tissues. Docking of CRX to the DNA models shows that CRX interacts with the grooves of these sequences, suggesting changes in groove structure could regulate binding. Molecular dynamics simulations of the RHO promoter and enhancer regions show changes in the flexibility and groove width upon epigenetic modification. Models also demonstrate changes in the local dynamics of CRX binding sites within RHO regulatory sequences which may account for the repression of CRX-dependent transcription. Collectively, these data demonstrate epigenetic regulation of CRX binding sites in human retinal tissue and provide insight into the mechanism of this mode of epigenetic regulation to be tested in future experiments.

In vitro fatigue tests and in silico finite element analysis of dental implants with different fixture/abutment joint types using computer-aided design models.

Science.gov (United States)

Yamaguchi, Satoshi; Yamanishi, Yasufumi; Machado, Lucas S; Matsumoto, Shuji; Tovar, Nick; Coelho, Paulo G; Thompson, Van P; Imazato, Satoshi

2018-01-01

The aim of this study was to evaluate fatigue resistance of dental fixtures with two different fixture-abutment connections by in vitro fatigue testing and in silico three-dimensional finite element analysis (3D FEA) using original computer-aided design (CAD) models. Dental implant fixtures with external connection (EX) or internal connection (IN) abutments were fabricated from original CAD models using grade IV titanium and step-stress accelerated life testing was performed. Fatigue cycles and loads were assessed by Weibull analysis, and fatigue cracking was observed by micro-computed tomography and a stereomicroscope with high dynamic range software. Using the same CAD models, displacement vectors of implant components were also analyzed by 3D FEA. Angles of the fractured line occurring at fixture platforms in vitro and of displacement vectors corresponding to the fractured line in silico were compared by two-way ANOVA. Fatigue testing showed significantly greater reliability for IN than EX (pimplant fixture platforms. FEA demonstrated that crack lines of both implant systems in vitro were observed in the same direction as displacement vectors of the implant fixtures in silico. In silico displacement vectors in the implant fixture are insightful for geometric development of dental implants to reduce complex interactions leading to fatigue failure. Copyright © 2017 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

The Complexity of Posttranscriptional Small RNA Regulatory Networks Revealed by In Silico Analysis of Gossypium arboreum L. Leaf, Flower and Boll Small Regulatory RNAs.

Directory of Open Access Journals (Sweden)

Hongtao Hu

Full Text Available MicroRNAs (miRNAs and secondary small interfering RNAs (principally phased siRNAs or trans-acting siRNAs are two distinct subfamilies of small RNAs (sRNAs that are emerging as key regulators of posttranscriptional gene expression in plants. Both miRNAs and secondary-siRNAs (sec-siRNAs are processed from longer RNA precursors by DICER-LIKE proteins (DCLs. Gossypium arboreum L., also known as tree cotton or Asian cotton, is a diploid, possibly ancestral relative of tetraploid Gossypium hirsutum L., the predominant type of commercially grown cotton worldwide known as upland cotton. To understand the biological significance of these gene regulators in G. arboreum, a bioinformatics analysis was performed on G. arboreum small RNAs produced from G. arboreum leaf, flower, and boll tissues. Consequently, 263 miRNAs derived from 353 precursors, including 155 conserved miRNAs (cs-miRNAs and 108 novel lineage-specific miRNAs (ls-miRNAs. Along with miRNAs, 2,033 miRNA variants (isomiRNAs were identified as well. Those isomiRNAs with variation at the 3'-miRNA end were expressed at the highest levels, compared to other types of variants. In addition, 755 pha-siRNAs derived 319 pha-siRNA gene transcripts (PGTs were identified, and the potential pha-siRNA initiators were predicted. Also, 2,251 non-phased siRNAs were found as well, of which 1,088 appeared to be produced by so-called cis- or trans-cleavage of the PGTs observed at positions differing from pha-siRNAs. Of those sRNAs, 148 miRNAs/isomiRNAs and 274 phased/non-phased siRNAs were differentially expressed in one or more pairs of tissues examined. Target analysis revealed that target genes for both miRNAs and pha-siRNAs are involved a broad range of metabolic and enzymatic activities. We demonstrate that secondary siRNA production could result from initial cleavage of precursors by both miRNAs or isomiRNAs, and that subsequently produced phased and unphased siRNAs could result that also serve as triggers

The Complexity of Posttranscriptional Small RNA Regulatory Networks Revealed by In Silico Analysis of Gossypium arboreum L. Leaf, Flower and Boll Small Regulatory RNAs.

Science.gov (United States)

Hu, Hongtao; Rashotte, Aaron M; Singh, Narendra K; Weaver, David B; Goertzen, Leslie R; Singh, Shree R; Locy, Robert D

2015-01-01

MicroRNAs (miRNAs) and secondary small interfering RNAs (principally phased siRNAs or trans-acting siRNAs) are two distinct subfamilies of small RNAs (sRNAs) that are emerging as key regulators of posttranscriptional gene expression in plants. Both miRNAs and secondary-siRNAs (sec-siRNAs) are processed from longer RNA precursors by DICER-LIKE proteins (DCLs). Gossypium arboreum L., also known as tree cotton or Asian cotton, is a diploid, possibly ancestral relative of tetraploid Gossypium hirsutum L., the predominant type of commercially grown cotton worldwide known as upland cotton. To understand the biological significance of these gene regulators in G. arboreum, a bioinformatics analysis was performed on G. arboreum small RNAs produced from G. arboreum leaf, flower, and boll tissues. Consequently, 263 miRNAs derived from 353 precursors, including 155 conserved miRNAs (cs-miRNAs) and 108 novel lineage-specific miRNAs (ls-miRNAs). Along with miRNAs, 2,033 miRNA variants (isomiRNAs) were identified as well. Those isomiRNAs with variation at the 3'-miRNA end were expressed at the highest levels, compared to other types of variants. In addition, 755 pha-siRNAs derived 319 pha-siRNA gene transcripts (PGTs) were identified, and the potential pha-siRNA initiators were predicted. Also, 2,251 non-phased siRNAs were found as well, of which 1,088 appeared to be produced by so-called cis- or trans-cleavage of the PGTs observed at positions differing from pha-siRNAs. Of those sRNAs, 148 miRNAs/isomiRNAs and 274 phased/non-phased siRNAs were differentially expressed in one or more pairs of tissues examined. Target analysis revealed that target genes for both miRNAs and pha-siRNAs are involved a broad range of metabolic and enzymatic activities. We demonstrate that secondary siRNA production could result from initial cleavage of precursors by both miRNAs or isomiRNAs, and that subsequently produced phased and unphased siRNAs could result that also serve as triggers of a second

In Silico analysis of perturbed steroidogenesis and gonad growth in fathead minnows (P. promelas) exposed to 17α-ethynylestradiol.

Science.gov (United States)

Hala, David; Petersen, Lene H; Martinović, Dalma; Huggett, Duane B

2015-06-01

The multi-factorial nature of adverse reproductive effects mediated by endocrine disrupting compounds (or EDCs) makes understanding the mechanistic basis of reproductive dysfunction a highly pertinent area of research. As a consequence, a main motivator for continued research is to integrate 'multi-leveled' complexity (i.e., from genes to phenotype) using mathematical methods capable of encapsulating properties of physiological relevance. In this study, an in silico stoichiometric model of piscine steroidogenesis was augmented with a 'biomass' reaction associating the underlying stoichiometry of steroidogenesis with a reaction representative of gonad growth. The ability of the in silico model to predict perturbed steroidogenesis and subsequent effects on gonad growth was tested by exposing reproductively active male and female fathead minnows (Pimephales promelas) to 88 ng/L of the synthetic estrogen, 17α-ethynylestradiol (EE2). The in silico model was parameterized (or constrained) with experimentally quantified concentrations of selected steroid hormones (using mass spectrometry) and fold changes in gene expression (using RT-qPCR) for selected steroidogenic enzyme genes, in gonads of male and female fish. Once constrained, the optimization framework of flux balance analysis (FBA) was used to calculate an optimal flux through the biomass reaction (analogous to gonad growth) and associated steroidogenic flux distributions required to generate biomass. FBA successfully predicted effects of EE2 exposure on fathead minnow gonad growth (%gonadosomatic index or %GSI) and perturbed production of steroid hormones. Specifically, FBA accurately predicted no effects of exposure on male %GSI and a significant reduction for female %GSI. Furthermore, in silico simulations accurately identified disrupted reaction fluxes catalyzing productions of androgens (in male fish) and progestogens (in female fish), an observation which agreed with in vivo experimentation. The analyses

Incorporation of in silico biodegradability screening in early drug development--a feasible approach?

Science.gov (United States)

Steger-Hartmann, Thomas; Länge, Reinhard; Heuck, Klaus

2011-05-01

The concentration of a pharmaceutical found in the environment is determined by the amount used by the patient, the excretion and metabolism pattern, and eventually by its persistence. Biological degradation or persistence of a pharmaceutical is experimentally tested rather late in the development of a pharmaceutical, often shortly before submission of the dossier to regulatory authorities. To investigate whether the aspect of persistence of a compound could be assessed early during drug development, we investigated whether biodegradation of pharmaceuticals could be predicted with the help of in silico tools. To assess the value of in silico prediction, we collected results for the OECD 301 degradation test ("ready biodegradability") of 42 drugs or drug synthesis intermediates and compared them to the prediction of the in silico tool BIOWIN. Of these compounds, 38 were predictable with BIOWIN, which is a module of the Estimation Programs Interface (EPI) Suite™ provided by the US EPA. The program failed to predict the two drugs which proved to be readily biodegradable in the degradation tests. On the other hand, BIOWIN predicted two compounds to be readily biodegradable which, however, proved to be persistent in the test setting. The comparison of experimental data with the predicted one resulted in a specificity of 94% and a sensitivity of 0%. The results of this study do not indicate that application of the biodegradation prediction tool BIOWIN is a feasible approach to assess the ready biodegradability during early drug development.

In silico transcriptional regulatory networks involved in tomato fruit ripening

Directory of Open Access Journals (Sweden)

Stilianos Arhondakis

2016-08-01

Full Text Available ABSTRACTTomato fruit ripening is a complex developmental programme partly mediated by transcriptional regulatory networks. Several transcription factors (TFs which are members of gene families such as MADS-box and ERF were shown to play a significant role in ripening through interconnections into an intricate network. The accumulation of large datasets of expression profiles corresponding to different stages of tomato fruit ripening and the availability of bioinformatics tools for their analysis provide an opportunity to identify TFs which might regulate gene clusters with similar co-expression patterns. We identified two TFs, a SlWRKY22-like and a SlER24 transcriptional activator which were shown to regulate modules by using the LeMoNe algorithm for the analysis of our microarray datasets representing four stages of fruit ripening, breaker, turning, pink and red ripe. The WRKY22-like module comprised a subgroup of six various calcium sensing transcripts with similar to the TF expression patterns according to real time PCR validation. A promoter motif search identified a cis acting element, the W-box, recognized by WRKY TFs that was present in the promoter region of all six calcium sensing genes. Moreover, publicly available microarray datasets of similar ripening stages were also analyzed with LeMoNe resulting in TFs such as SlERF.E1, SlERF.C1, SlERF.B2, SLERF.A2, SlWRKY24, SLWRKY37 and MADS-box/TM29 which might also play an important role in regulation of ripening. These results suggest that the SlWRKY22-like might be involved in the coordinated regulation of expression of the six calcium sensing genes. Conclusively the LeMoNe tool might lead to the identification of putative TF targets for further physiological analysis as regulators of tomato fruit ripening.

Application of WGS data for O-specific antigen analysis and in silico serotyping of Pseudomonas aeruginosa isolates

DEFF Research Database (Denmark)

Thrane, Sandra Wingaard; Taylor, Véronique L.; Lund, Ole

2016-01-01

aeruginosa serotyper (PAst) program, which enabled in silico serotyping of P. aeruginosa isolates using WGS data. PAst has been made publically available as a web-service, and aptly facilitate high-throughput serotyping analysis. The program overcomes critical issues such as the loss of in vitro typeability...... often associated with P. aeruginosa isolates from chronic infections, and quickly determines the serogroup of an isolate based on the sequence of the O-specific antigen (OSA) gene cluster. Here, PAst analysis of 1649 genomes resulted in successful serogroup assignments in 99.27% of the cases...

Sequence-based model of gap gene regulatory network.

Science.gov (United States)

Kozlov, Konstantin; Gursky, Vitaly; Kulakovskiy, Ivan; Samsonova, Maria

2014-01-01

The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The gap gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation gene network. The knowledge of molecular mechanisms involved in gap gene regulation is far less complete than that of genetics of the system. Mathematical modeling goes beyond insights gained by genetics and molecular approaches. It allows us to reconstruct wild-type gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. We developed a new model that provides a dynamical description of gap gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces gap gene expression patterns in wild type embryos and is able to predict gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the gap gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and for the set with the site of interest excluded. The reconstructed topology of the gap gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3

Yak milk casein as potential precursor of angiotensin I-converting enzyme inhibitory peptides based on in silico proteolysis.

Science.gov (United States)

Lin, Kai; Zhang, Lan-Wei; Han, Xue; Xin, Liang; Meng, Zhao-Xu; Gong, Pi-Min; Cheng, Da-You

2018-07-15

Yak milk casein was selected as a potential precursor of bioactive peptides based on in silico analysis. Most notable among these are the angiotensin I-converting enzyme (ACE) inhibitory peptides. First, yak milk casein has high homology with cow milk casein by homologous analysis. The potential of yak milk casein for the releasing bioactive peptides was evaluated by determining the frequency of occurrence of fragments with a given activity. Through the BIOPEP database analysis, there are many bioactive peptides in yak milk casein sequences. Then, an in silico proteolysis using single or combined enzymes to obtained ACE inhibitory peptides was investigated. Cytotoxicity analysis using the online toxic prediction tool ToxinPred revealed that all in silico proteolysis derived ACE inhibitory peptides are non-cytotoxic. Overall, the present study highlights a in silico proteolysis approach to assist the yak milk casein releasing ACE inhibitory peptides and provides a guidance for the actual hydrolysis of proteins for the production of bioactive peptides. Copyright © 2018 Elsevier Ltd. All rights reserved.

In silico polymorphism analysis for the development of simple sequence repeat and transposon markers and construction of linkage map in cultivated peanut

Directory of Open Access Journals (Sweden)

Shirasawa Kenta

2012-06-01

Full Text Available Abstract Background Peanut (Arachis hypogaea is an autogamous allotetraploid legume (2n = 4x = 40 that is widely cultivated as a food and oil crop. More than 6,000 DNA markers have been developed in Arachis spp., but high-density linkage maps useful for genetics, genomics, and breeding have not been constructed due to extremely low genetic diversity. Polymorphic marker loci are useful for the construction of such high-density linkage maps. The present study used in silico analysis to develop simple sequence repeat-based and transposon-based markers. Results The use of in silico analysis increased the efficiency of polymorphic marker development by more than 3-fold. In total, 926 (34.2% of 2,702 markers showed polymorphisms between parental lines of the mapping population. Linkage analysis of the 926 markers along with 253 polymorphic markers selected from 4,449 published markers generated 21 linkage groups covering 2,166.4 cM with 1,114 loci. Based on the map thus produced, 23 quantitative trait loci (QTLs for 15 agronomical traits were detected. Another linkage map with 326 loci was also constructed and revealed a relationship between the genotypes of the FAD2 genes and the ratio of oleic/linoleic acid in peanut seed. Conclusions In silico analysis of polymorphisms increased the efficiency of polymorphic marker development, and contributed to the construction of high-density linkage maps in cultivated peanut. The resultant maps were applicable to QTL analysis. Marker subsets and linkage maps developed in this study should be useful for genetics, genomics, and breeding in Arachis. The data are available at the Kazusa DNA Marker Database (http://marker.kazusa.or.jp.

In-silico ADME Studies for New Drug Discovery: From Chemical Compounds to Chinese Herbal Medicines.

Science.gov (United States)

Yan, Guojun; Wang, Xiaobing; Chen, Zhou; Wu, Xianhui; Pan, Jinhuo; Huang, Yushen; Wan, Gang; Yang, Zhaogang

2017-07-21

Nowadays, in silico tools are widely used to provide the potential structure of the metabolites formed depending on the site of metabolism. These methods can also highlight the molecular moieties that help to direct the molecule into the cytochrome cavity so that the site of metabolism is in proximity to the catalytic center. In this minireview, we summarized three aspects of the in silico methods in the application of prediction of ADME (absorption, distribution, metabolism and excretion) properties of compounds: structure-based approaches for predicting molecular modeling of drug metabolizing enzymes; in silico metabolite prediction; and pharmacophore models for analysis substrate specificity. Moreover, we also extended the in silico studies in Chinese herbal medicines (CHM) research. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Synchronous versus asynchronous modeling of gene regulatory networks.

Science.gov (United States)

Garg, Abhishek; Di Cara, Alessandro; Xenarios, Ioannis; Mendoza, Luis; De Micheli, Giovanni

2008-09-01

In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

In silico modeling predicts drug sensitivity of patient-derived cancer cells.

Science.gov (United States)

Pingle, Sandeep C; Sultana, Zeba; Pastorino, Sandra; Jiang, Pengfei; Mukthavaram, Rajesh; Chao, Ying; Bharati, Ila Sri; Nomura, Natsuko; Makale, Milan; Abbasi, Taher; Kapoor, Shweta; Kumar, Ansu; Usmani, Shahabuddin; Agrawal, Ashish; Vali, Shireen; Kesari, Santosh

2014-05-21

Glioblastoma (GBM) is an aggressive disease associated with poor survival. It is essential to account for the complexity of GBM biology to improve diagnostic and therapeutic strategies. This complexity is best represented by the increasing amounts of profiling ("omics") data available due to advances in biotechnology. The challenge of integrating these vast genomic and proteomic data can be addressed by a comprehensive systems modeling approach. Here, we present an in silico model, where we simulate GBM tumor cells using genomic profiling data. We use this in silico tumor model to predict responses of cancer cells to targeted drugs. Initially, we probed the results from a recent hypothesis-independent, empirical study by Garnett and co-workers that analyzed the sensitivity of hundreds of profiled cancer cell lines to 130 different anticancer agents. We then used the tumor model to predict sensitivity of patient-derived GBM cell lines to different targeted therapeutic agents. Among the drug-mutation associations reported in the Garnett study, our in silico model accurately predicted ~85% of the associations. While testing the model in a prospective manner using simulations of patient-derived GBM cell lines, we compared our simulation predictions with experimental data using the same cells in vitro. This analysis yielded a ~75% agreement of in silico drug sensitivity with in vitro experimental findings. These results demonstrate a strong predictability of our simulation approach using the in silico tumor model presented here. Our ultimate goal is to use this model to stratify patients for clinical trials. By accurately predicting responses of cancer cells to targeted agents a priori, this in silico tumor model provides an innovative approach to personalizing therapy and promises to improve clinical management of cancer.

Inferring regulatory networks from expression data using tree-based methods.

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Vân Anh Huynh-Thu

2010-09-01

Full Text Available One of the pressing open problems of computational systems biology is the elucidation of the topology of genetic regulatory networks (GRNs using high throughput genomic data, in particular microarray gene expression data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM challenge aims to evaluate the success of GRN inference algorithms on benchmarks of simulated data. In this article, we present GENIE3, a new algorithm for the inference of GRNs that was best performer in the DREAM4 In Silico Multifactorial challenge. GENIE3 decomposes the prediction of a regulatory network between p genes into p different regression problems. In each of the regression problems, the expression pattern of one of the genes (target gene is predicted from the expression patterns of all the other genes (input genes, using tree-based ensemble methods Random Forests or Extra-Trees. The importance of an input gene in the prediction of the target gene expression pattern is taken as an indication of a putative regulatory link. Putative regulatory links are then aggregated over all genes to provide a ranking of interactions from which the whole network is reconstructed. In addition to performing well on the DREAM4 In Silico Multifactorial challenge simulated data, we show that GENIE3 compares favorably with existing algorithms to decipher the genetic regulatory network of Escherichia coli. It doesn't make any assumption about the nature of gene regulation, can deal with combinatorial and non-linear interactions, produces directed GRNs, and is fast and scalable. In conclusion, we propose a new algorithm for GRN inference that performs well on both synthetic and real gene expression data. The algorithm, based on feature selection with tree-based ensemble methods, is simple and generic, making it adaptable to other types of genomic data and interactions.

Formal modeling and analysis of ER-α associated Biological Regulatory Network in breast cancer

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Samra Khalid

2016-10-01

Full Text Available Background Breast cancer (BC is one of the leading cause of death among females worldwide. The increasing incidence of BC is due to various genetic and environmental changes which lead to the disruption of cellular signaling network(s. It is a complex disease in which several interlinking signaling cascades play a crucial role in establishing a complex regulatory network. The logical modeling approach of René Thomas has been applied to analyze the behavior of estrogen receptor-alpha (ER-α associated Biological Regulatory Network (BRN for a small part of complex events that leads to BC metastasis. Methods A discrete model was constructed using the kinetic logic formalism and its set of logical parameters were obtained using the model checking technique implemented in the SMBioNet software which is consistent with biological observations. The discrete model was further enriched with continuous dynamics by converting it into an equivalent Petri Net (PN to analyze the logical parameters of the involved entities. Results In-silico based discrete and continuous modeling of ER-α associated signaling network involved in BC provides information about behaviors and gene-gene interaction in detail. The dynamics of discrete model revealed, imperative behaviors represented as cyclic paths and trajectories leading to pathogenic states such as metastasis. Results suggest that the increased expressions of receptors ER-α, IGF-1R and EGFR slow down the activity of tumor suppressor genes (TSGs such as BRCA1, p53 and Mdm2 which can lead to metastasis. Therefore, IGF-1R and EGFR are considered as important inhibitory targets to control the metastasis in BC. Conclusion The in-silico approaches allow us to increase our understanding of the functional properties of living organisms. It opens new avenues of investigations of multiple inhibitory targets (ER-α, IGF-1R and EGFR for wet lab experiments as well as provided valuable insights in the treatment of cancers

Bioinformatics Identification of Modules of Transcription Factor Binding Sites in Alzheimer's Disease-Related Genes by In Silico Promoter Analysis and Microarrays

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Regina Augustin

2011-01-01

Full Text Available The molecular mechanisms and genetic risk factors underlying Alzheimer's disease (AD pathogenesis are only partly understood. To identify new factors, which may contribute to AD, different approaches are taken including proteomics, genetics, and functional genomics. Here, we used a bioinformatics approach and found that distinct AD-related genes share modules of transcription factor binding sites, suggesting a transcriptional coregulation. To detect additional coregulated genes, which may potentially contribute to AD, we established a new bioinformatics workflow with known multivariate methods like support vector machines, biclustering, and predicted transcription factor binding site modules by using in silico analysis and over 400 expression arrays from human and mouse. Two significant modules are composed of three transcription factor families: CTCF, SP1F, and EGRF/ZBPF, which are conserved between human and mouse APP promoter sequences. The specific combination of in silico promoter and multivariate analysis can identify regulation mechanisms of genes involved in multifactorial diseases.

Association of rs1801157 single nucleotide polymorphism of CXCL12 gene in breast cancer in Pakistan and in-silico expression analysis of CXCL12–CXCR4 associated biological regulatory network

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Samra Khalid

2017-09-01

Full Text Available Background C-X-C chemokine ligand 12 (CXCL12 has important implications in breast cancer (BC pathogenesis. It is selectively expressed on B and T lymphocytes and is involved in hematopoiesis, thymocyte trafficking, stem cell motility, neovascularization, and tumorigenesis. The single nucleotide polymorphism (SNP rs1801157 of CXCL12 gene has been found to be associated with higher risk of BC. Methods Our study focuses on the genotypic and allelic distribution of SNP (rs1801157; G/A in Pakistani population as well as its association with the clinico-pathological features. The association between rs1801157 genotypes (G/A and BC risks was assessed by a multivariate logistic regression (MLR analysis. Genotyping was performed in both healthy individuals and patients of BC using PCR-restriction fragment length polymorphism (PCR-RFLP method. Furthermore, in-silico approaches were adapted to investigate the association of CXCL12 and its receptor CXCR4 with genes/proteins involved in BC signalling. Results Significant differences in allelic and genotypic distribution between BC patients and healthy individuals of genotype (G/G and (A/G (p  0.05 was assessed. In a MLR analysis, a number of variables including age, weight of an individual, affected lymph nodes, hormonal status (estrogen and progesterone receptor, alcohol consumption and family history associated with the GG genotype (GG:AA, odds ratio (OR = 1.30, 95% CI [1.06–1.60] were found to be independent risk factors for BC. Our in-vitro results suggest that genotype GG is possibly increasing the risk of BC in Pakistani cohorts. in-silico analysis finds that CXCL12–CXCR4 is associated with an increased expression of PDZK1, PI3k and Akt which lead the breast tumor towards metastasis. Conclusion Multiple targets such as CXCL12, CXCR4, PDZK1, PI3k and Akt can be inhibited in combined strategies to treat BC metastasis.

CoryneRegNet: an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks.

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Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-02-14

The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

Association of Human Methionine Synthase-A2756G Transition With Prostate Cancer: A Case-Control Study and in Silico Analysis

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Arezou Ebrahimi

2017-07-01

Full Text Available Methionine synthase (MTR is one of the key enzymes of folate pathway, which play a key role in the construction, repair, and methylation of DNA. In this study, an association of MTR A2756G gene transition with prostate cancer in men populations of Kashan-Iran was investigated by a case-control study and an in silico analysis. The 200 samples including 100 patients with prostate cancer, as case group and 100 healthy men, as control group included in this study. MTR-A2756G genotyping was performed by PCR-RFLP technique. Some in silico tools used to evaluate the effects of A2756G transition on the structure and function of MTR. Results showed that the AG genotype (OR: 2.4014, 95% CI: 1.3216-4.3636, P=0.0040, and GG genotype (OR: 3.6324, 95% CI: 1.2629-10.4475, P=0.0167 and G allele (OR: 2.0120, 95% CI: 1.3098-3.0905, P=0.0014 were associated with prostate cancer. In silico analysis showed that polymorphisms of the enzyme protein might change properties of MTR such as relative mutability and flexibility, which leads to alteration of stability and function of the enzyme. Based on the results, an MTR-A2756G polymorphism which changes activity and stability of the methionine synthase associated with prostate cancer in men. It is a preliminary study and is presenting data for future comprehensive study for making a clinical conclusion that this gene transition is a biomarker for susceptibility to prostate cancer.

BRCA1/2 missense mutations and the value of in-silico analyses.

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Sadowski, Carolin E; Kohlstedt, Daniela; Meisel, Cornelia; Keller, Katja; Becker, Kerstin; Mackenroth, Luisa; Rump, Andreas; Schröck, Evelin; Wimberger, Pauline; Kast, Karin

2017-11-01

The clinical implications of genetic variants in BRCA1/2 in healthy and affected individuals are considerable. Variant interpretation, however, is especially challenging for missense variants. The majority of them are classified as variants of unknown clinical significance (VUS). Computational (in-silico) predictive programs are easy to access, but represent only one tool out of a wide range of complemental approaches to classify VUS. With this single-center study, we aimed to evaluate the impact of in-silico analyses in a spectrum of different BRCA1/2 missense variants. We conducted mutation analysis of BRCA1/2 in 523 index patients with suspected hereditary breast and ovarian cancer (HBOC). Classification of the genetic variants was performed according to the German Consortium (GC)-HBOC database. Additionally, all missense variants were classified by the following three in-silico prediction tools: SIFT, Mutation Taster (MT2) and PolyPhen2 (PPH2). Overall 201 different variants, 68 of which constituted missense variants were ranked as pathogenic, neutral, or unknown. The classification of missense variants by in-silico tools resulted in a higher amount of pathogenic mutations (25% vs. 13.2%) compared to the GC-HBOC-classification. Altogether, more than fifty percent (38/68, 55.9%) of missense variants were ranked differently. Sensitivity of in-silico-tools for mutation prediction was 88.9% (PPH2), 100% (SIFT) and 100% (MT2). We found a relevant discrepancy in variant classification by using in-silico prediction tools, resulting in potential overestimation and/or underestimation of cancer risk. More reliable, notably gene-specific, prediction tools and functional tests are needed to improve clinical counseling. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Sensitivity analysis for missing data in regulatory submissions.

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Permutt, Thomas

2016-07-30

The National Research Council Panel on Handling Missing Data in Clinical Trials recommended that sensitivity analyses have to be part of the primary reporting of findings from clinical trials. Their specific recommendations, however, seem not to have been taken up rapidly by sponsors of regulatory submissions. The NRC report's detailed suggestions are along rather different lines than what has been called sensitivity analysis in the regulatory setting up to now. Furthermore, the role of sensitivity analysis in regulatory decision-making, although discussed briefly in the NRC report, remains unclear. This paper will examine previous ideas of sensitivity analysis with a view to explaining how the NRC panel's recommendations are different and possibly better suited to coping with present problems of missing data in the regulatory setting. It will also discuss, in more detail than the NRC report, the relevance of sensitivity analysis to decision-making, both for applicants and for regulators. Published 2015. This article is a U.S. Government work and is in the public domain in the USA. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

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Baumbach Jan

2007-11-01

Full Text Available Abstract Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user can be analyzed in the context of known

High accuracy in silico sulfotransferase models.

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Cook, Ian; Wang, Ting; Falany, Charles N; Leyh, Thomas S

2013-11-29

Predicting enzymatic behavior in silico is an integral part of our efforts to understand biology. Hundreds of millions of compounds lie in targeted in silico libraries waiting for their metabolic potential to be discovered. In silico "enzymes" capable of accurately determining whether compounds can inhibit or react is often the missing piece in this endeavor. This problem has now been solved for the cytosolic sulfotransferases (SULTs). SULTs regulate the bioactivities of thousands of compounds--endogenous metabolites, drugs and other xenobiotics--by transferring the sulfuryl moiety (SO3) from 3'-phosphoadenosine 5'-phosphosulfate to the hydroxyls and primary amines of these acceptors. SULT1A1 and 2A1 catalyze the majority of sulfation that occurs during human Phase II metabolism. Here, recent insights into the structure and dynamics of SULT binding and reactivity are incorporated into in silico models of 1A1 and 2A1 that are used to identify substrates and inhibitors in a structurally diverse set of 1,455 high value compounds: the FDA-approved small molecule drugs. The SULT1A1 models predict 76 substrates. Of these, 53 were known substrates. Of the remaining 23, 21 were tested, and all were sulfated. The SULT2A1 models predict 22 substrates, 14 of which are known substrates. Of the remaining 8, 4 were tested, and all are substrates. The models proved to be 100% accurate in identifying substrates and made no false predictions at Kd thresholds of 100 μM. In total, 23 "new" drug substrates were identified, and new linkages to drug inhibitors are predicted. It now appears to be possible to accurately predict Phase II sulfonation in silico.

In silico cancer research towards 3R.

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Jean-Quartier, Claire; Jeanquartier, Fleur; Jurisica, Igor; Holzinger, Andreas

2018-04-12

Improving our understanding of cancer and other complex diseases requires integrating diverse data sets and algorithms. Intertwining in vivo and in vitro data and in silico models are paramount to overcome intrinsic difficulties given by data complexity. Importantly, this approach also helps to uncover underlying molecular mechanisms. Over the years, research has introduced multiple biochemical and computational methods to study the disease, many of which require animal experiments. However, modeling systems and the comparison of cellular processes in both eukaryotes and prokaryotes help to understand specific aspects of uncontrolled cell growth, eventually leading to improved planning of future experiments. According to the principles for humane techniques milestones in alternative animal testing involve in vitro methods such as cell-based models and microfluidic chips, as well as clinical tests of microdosing and imaging. Up-to-date, the range of alternative methods has expanded towards computational approaches, based on the use of information from past in vitro and in vivo experiments. In fact, in silico techniques are often underrated but can be vital to understanding fundamental processes in cancer. They can rival accuracy of biological assays, and they can provide essential focus and direction to reduce experimental cost. We give an overview on in vivo, in vitro and in silico methods used in cancer research. Common models as cell-lines, xenografts, or genetically modified rodents reflect relevant pathological processes to a different degree, but can not replicate the full spectrum of human disease. There is an increasing importance of computational biology, advancing from the task of assisting biological analysis with network biology approaches as the basis for understanding a cell's functional organization up to model building for predictive systems. Underlining and extending the in silico approach with respect to the 3Rs for replacement, reduction and

Isolation and in silico analysis of Fe-superoxide dismutase in the cyanobacterium Nostoc commune.

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Kesheri, Minu; Kanchan, Swarna; Richa; Sinha, Rajeshwar P

2014-12-15

Cyanobacteria are known to endure various stress conditions due to the inbuilt potential for oxidative stress alleviation owing to the presence of an array of antioxidants. The present study shows that Antarctic cyanobacterium Nostoc commune possesses two antioxidative enzymes viz., superoxide dismutase (SOD) and catalase that jointly cope with environmental stresses prevailing at its natural habitat. Native-PAGE analysis illustrates the presence of a single prominent isoform recognized as Fe-SOD and three distinct isoforms of catalase. The protein sequence of Fe-SOD in N. commune retrieved from NCBI protein sequence database was used for in silico analysis. 3D structure of N. commune was predicted by comparative modeling using MODELLER 9v11. Further, this model was validated for its quality by Ramachandran plot, ERRAT, Verify 3D and ProSA-web which revealed good structure quality of the model. Multiple sequence alignment showed high conservation in N and C-terminal domain regions along with all metal binding positions in Fe-SOD which were also found to be highly conserved in all 28 cyanobacterial species under study, including N. commune. In silico prediction of isoelectric point and molecular weight of Fe-SOD was found to be 5.48 and 22,342.98Da respectively. The phylogenetic tree revealed that among 28 cyanobacterial species, Fe-SOD in N. commune was the closest evolutionary homolog of Fe-SOD in Nostoc punctiforme as evident by strong bootstrap value. Thus, N. commune may serve as a good biological model for studies related to survival of life under extreme conditions prevailing at the Antarctic region. Moreover cyanobacteria may be exploited for biochemical and biotechnological applications of enzymatic antioxidants. Copyright © 2014 Elsevier B.V. All rights reserved.

In silico pattern-based analysis of the human cytomegalovirus genome.

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Rigoutsos, Isidore; Novotny, Jiri; Huynh, Tien; Chin-Bow, Stephen T; Parida, Laxmi; Platt, Daniel; Coleman, David; Shenk, Thomas

2003-04-01

More than 200 open reading frames (ORFs) from the human cytomegalovirus genome have been reported as potentially coding for proteins. We have used two pattern-based in silico approaches to analyze this set of putative viral genes. With the help of an objective annotation method that is based on the Bio-Dictionary, a comprehensive collection of amino acid patterns that describes the currently known natural sequence space of proteins, we have reannotated all of the previously reported putative genes of the human cytomegalovirus. Also, with the help of MUSCA, a pattern-based multiple sequence alignment algorithm, we have reexamined the original human cytomegalovirus gene family definitions. Our analysis of the genome shows that many of the coded proteins comprise amino acid combinations that are unique to either the human cytomegalovirus or the larger group of herpesviruses. We have confirmed that a surprisingly large portion of the analyzed ORFs encode membrane proteins, and we have discovered a significant number of previously uncharacterized proteins that are predicted to be G-protein-coupled receptor homologues. The analysis also indicates that many of the encoded proteins undergo posttranslational modifications such as hydroxylation, phosphorylation, and glycosylation. ORFs encoding proteins with similar functional behavior appear in neighboring regions of the human cytomegalovirus genome. All of the results of the present study can be found and interactively explored online (http://cbcsrv.watson.ibm.com/virus/).

CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks

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Czaja Lisa F

2006-02-01

Full Text Available Abstract Background The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. Description CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. Conclusion CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

Comparative in silico profiling of epigenetic modifiers in human tissues.

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Son, Mi-Young; Jung, Cho-Rok; Kim, Dae-Soo; Cho, Hyun-Soo

2018-04-06

The technology of tissue differentiation from human pluripotent stem cells has attracted attention as a useful resource for regenerative medicine, disease modeling and drug development. Recent studies have suggested various key factors and specific culture methods to improve the successful tissue differentiation and efficient generation of human induced pluripotent stem cells. Among these methods, epigenetic regulation and epigenetic signatures are regarded as an important hurdle to overcome during reprogramming and differentiation. Thus, in this study, we developed an in silico epigenetic panel and performed a comparative analysis of epigenetic modifiers in the RNA-seq results of 32 human tissues. We demonstrated that an in silico epigenetic panel can identify epigenetic modifiers in order to overcome epigenetic barriers to tissue-specific differentiation.

In vitro/in silico investigation of failure criteria to predict flexural strength of composite resins.

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Yamaguchi, Satoshi; Mehdawi, Idris Mohamed; Sakai, Takahiko; Abe, Tomohiro; Inoue, Sayuri; Imazato, Satoshi

2018-01-30

The aim of this study was to investigate a failure criterion to predict flexural strengths of composite resins (CR) by three-dimensional finite element analysis (3D-FEA). Models of flexural strength for test specimens of CR and rods comprising a three-point loading were designed. Calculation of Young's moduli and Poisson's ratios of CR were conducted using a modified McGee-McCullough model. Using the experimental CR, flexural strengths were measured by three-point bending tests with crosshead speed 1.0 mm/min and compared with the values determined by in silico analysis. The flexural strengths of experimental CR calculated using the maximum principal strain significantly correlated with those obtained in silico amongst the four types of failure criteria applied. The in silico analytical model established in this study was found to be effective to predict the flexural strengths of CR incorporating various silica filler contents by maximum principal strain.

[In silico CRISPR-based sgRNA design].

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Wang, Yuanli; Chuai, Guohui; Yan, Jifang; Shi, Lei; Liu, Qi

2017-10-25

CRISPR-based genome editing has been widely implemented in various cell types. In-silico single guide RNA (sgRNA) design is a key step for successful gene editing using CRISPR system. Continuing efforts are made to refine in-silico sgRNA design with high on-target efficacy and reduced off-target effects. In this paper, we summarize the present sgRNA design tools, and show that efficient in-silico models can be built that integrate current heterogeneous genome-editing data to derive unbiased sgRNA design rules and identify key features for improving sgRNA design. Our review shows that systematic comparisons and evaluation of on-target and off-target effects of sgRNA will allow more precise genome editing and gene therapies using the CRISPR system.

A Comprehensive in Silico Analysis of Regulatory SNPs of Human CLEC7A Gene and Its Validation as Genotypic and Phenotypic Disease Marker in Recurrent Vulvovaginal Infections

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Namarta Kalia

2018-03-01

Full Text Available Recurrent Vulvovaginal infections (RVVI are the commonly reported microbiological syndrome affecting millions of women globally. Various molecules of innate immune system are instrumental in clearance of these microbial pathogens, thus suggested as one of the most important contributing factor in determining the disease outcome. Dendritic cell-associated C-type lectin-1 (Dectin-1 is an important molecule of innate immunity that is primarily known for its role in antifungal defenses. However, role of dectin-1 in recognition of other pathogens is also documented. The intracellular expression of dectin-1 was shown to be up-regulated by Mannose Binding Lectin (MBL-mediated opsonophagocytosis of pathogens. Dectin-1 is encoded by CLEC7A, postulated to be a candidate gene in modulating risk of developing RVVI. In this study, we identified CLEC7A causal variants using in silico analysis. To assess their impact on susceptibility to RVVI, these causal variants along with serum dectin-1 levels (sDectin-1 were investigated using polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP and Enzyme Linked Immnosorbent Assay (ELISA respectively, under a case-control design. Furthermore, effect of these polymorphisms was also assessed on sMBL levels. In silico analysis revealed 9 putative functional conserved SNPs of CLEC7A. Association analysis revealed a significantly lower risk of developing RVVI and its types in carriers of CLEC7A rs3901533 G allele and its homozygous genotypes (p < 0.05. The heterozygous genotype was associated with significant protection against RVVI (p = 0.004. Haplotypes GGG and GTA showed significant protection against RVVI (p < 0.0001; p = 0.0003, Bacterial Vaginosis (p = 0.03; p = 0.002, Vulvovaginal Candidiasis (p = 0.03; p = 0.01 and Mixed Infections (p = 0.007; p = 0.04. Mean sDectin-1 levels were significantly high in RVVI and its types compared to controls (p < 0.05. Further, genotype

FutureTox II: in vitro data and in silico models for predictive toxicology.

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Knudsen, Thomas B; Keller, Douglas A; Sander, Miriam; Carney, Edward W; Doerrer, Nancy G; Eaton, David L; Fitzpatrick, Suzanne Compton; Hastings, Kenneth L; Mendrick, Donna L; Tice, Raymond R; Watkins, Paul B; Whelan, Maurice

2015-02-01

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Barcoded DNA-tag reporters for multiplex cis-regulatory analysis.

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Jongmin Nam

Full Text Available Cis-regulatory DNA sequences causally mediate patterns of gene expression, but efficient experimental analysis of these control systems has remained challenging. Here we develop a new version of "barcoded" DNA-tag reporters, "Nanotags" that permit simultaneous quantitative analysis of up to 130 distinct cis-regulatory modules (CRMs. The activities of these reporters are measured in single experiments by the NanoString RNA counting method and other quantitative procedures. We demonstrate the efficiency of the Nanotag method by simultaneously measuring hourly temporal activities of 126 CRMs from 46 genes in the developing sea urchin embryo, otherwise a virtually impossible task. Nanotags are also used in gene perturbation experiments to reveal cis-regulatory responses of many CRMs at once. Nanotag methodology can be applied to many research areas, ranging from gene regulatory networks to functional and evolutionary genomics.

Human MTHFR-G1793A transition may be a protective mutation against male infertility: a genetic association study and in silico analysis.

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Karimian, Mohammad; Hosseinzadeh Colagar, Abasalt

2018-06-01

In this paper, we evaluate the association of the human methylenetetrahydrofolate reductase (MTHFR)-G1793A transition with male infertility using a case-control study, a meta-analysis and an in silico analysis. In the case-control study, 308 blood samples (169 infertile and 139 fertile men) were collected. MTHFR-G1793A genotyping was performed by PCR-RFLP. The study revealed a significant protective association between the GA genotype (OR: 0.3737, 95%CI: 0.1874-0.7452, p = 0.0052) and A allele (OR: 0.4266, 95%CI: 0.2267-0.8030, p = 0.0083) with male infertility. Meta-analysis showed that the G1793A transition might be a protective mutation against male infertility in both A vs. G (OR: 0.608, 95%CI: 0.466-0.792, p silico-analysis revealed that although G1793A could not make fundamental changes in the function and structure of MTHFR, it could modify the structure of the mRNA (Distance =0.1809, p = 0.1095; p < 0.2 is significant). The results suggest that G1793A substitution might be a protective genetic factor against male infertility. However, further case-control studies are required to provide a more robust conclusion.

In silico environmental chemical science: properties and processes from statistical and computational modelling.

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Tratnyek, Paul G; Bylaska, Eric J; Weber, Eric J

2017-03-22

Quantitative structure-activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with "in silico" results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs using descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for "in silico environmental chemical science" are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.

In silico analysis suggests interaction between Ebola virus and the extracellular matrix

Directory of Open Access Journals (Sweden)

Veljko eVeljkovic

2015-02-01

Full Text Available The worst Ebola virus (EV outbreak in history has hit Liberia, Sierra Leone and Guinea hardest and the trendlines in this crisis are grave, and now represents global public health threat concern. Limited therapeutic and/or prophylactic options which are available for humans suffering from Ebola virus disease (EVD further complicate situation. Previous studies suggested that the EV glycoprotein (GP is the main determinant causing structural damage of endothelial cells that triggers the hemorrhagic diathesis, but molecular mechanisms underlying this phenomenon remains elusive. Using the informational spectrum method (ISM, a virtual spectroscopy method for analysis of the protein-protein interactions, the interaction of GP with endothelial extracellular matrix (ECM was investigated. Presented results of this in silico study suggest that Elastin Microfibril Interface Located Proteins (EMILINs are involved in interaction between GP and ECM. This finding could contribute to better understanding of EV/endothelium interaction and its role in pathogenesis, prevention and therapy of EVD.

In silico analysis of glycinamide ribonucleotide transformylase inhibition by PY873, PY899 and DIA

Directory of Open Access Journals (Sweden)

Sidra Batool

2017-09-01

Full Text Available In humans, purine de novo synthesis pathway consists of multi-functional enzymes. Nucleotide metabolism enzymes are potential drug targets for treating cancer and autoimmune diseases. Glycinamide ribonucleotide transformylase (GART is one of the most important trifunctional enzymes involved in purine synthesis. Previous studies have demonstrated the role of folate inhibitors against tumor activity. In this present study, three components of GART enzyme were targeted as receptor dataset and in silico analysis was carried out with folate ligand dataset. To accomplish the task, Autodock 4.2 was used for determining the docking compatibilities of ligand and receptor dataset. Taken together, it has been suggested that folate ligands could be potentially used as inhibitors of GART.

Regulatory compliance analysis for the closure of single-shell tanks

International Nuclear Information System (INIS)

Smith, E.H.; Boomer, K.D.; Letourneau, M.; Oakes, L.; Lorang, R.

1991-08-01

This document provides a regulatory compliance analysis of the baseline environmental protection requirements for the closure of single-shell tanks. In preparing this document, the Westinghouse Hanford Company has analyzed the regulatory pathways and decisions points that have been identified to data through systems engineering and related studies as they relate to environmental protection. This regulatory compliance analysis has resulted in several conclusions that will aid the US Department of Energy in managing the single-shell tank waste and in developing strategies for the closure of these tanks. These conclusions include likely outcomes of current strategies, regulatory rulings that are required for future actions, variances and exemptions to be pursued, where appropriate, and potential rulings that may affect systems engineering and other portions of the single-shell tank closure effort. The conclusions and recommendations presented here are based on analysis of current regulations, regulatory exemptions and variances, and federal facility agreements. Because the remediation of the single-shell tanks will span 30 years, regulations that have yet to be promulgated and future interpretations of existing laws and regulations may impact the recommendations and conclusions presented here. 50 refs., 22 figs

NASA's Agency-Wide Strategy for Environmental Regulatory Risk Analysis and Communication

Science.gov (United States)

Scroggins, Sharon; Duda, Kristen

2008-01-01

This viewgraph presentation gives an overview of NASA's risk analysis communication programs associated with changing environmental policies. The topics include: 1) NASA Program Transition; 2) Principal Center for Regulatory Risk Analysis and Communication (RRAC PC); and 3) Regulatory Tracking and Communication Process.

A novel method for in silico identification of regulatory SNPs in human genome.

Science.gov (United States)

Li, Rong; Zhong, Dexing; Liu, Ruiling; Lv, Hongqiang; Zhang, Xinman; Liu, Jun; Han, Jiuqiang

2017-02-21

Regulatory single nucleotide polymorphisms (rSNPs), kind of functional noncoding genetic variants, can affect gene expression in a regulatory way, and they are thought to be associated with increased susceptibilities to complex diseases. Here a novel computational approach to identify potential rSNPs is presented. Different from most other rSNPs finding methods which based on hypothesis that SNPs causing large allele-specific changes in transcription factor binding affinities are more likely to play regulatory functions, we use a set of documented experimentally verified rSNPs and nonfunctional background SNPs to train classifiers, so the discriminating features are found. To characterize variants, an extensive range of characteristics, such as sequence context, DNA structure and evolutionary conservation etc. are analyzed. Support vector machine is adopted to build the classifier model together with an ensemble method to deal with unbalanced data. 10-fold cross-validation result shows that our method can achieve accuracy with sensitivity of ~78% and specificity of ~82%. Furthermore, our method performances better than some other algorithms based on aforementioned hypothesis in handling false positives. The original data and the source matlab codes involved are available at https://sourceforge.net/projects/rsnppredict/. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Holistic In silico Approach to Develop Novel Inhibitors Targeting ...

African Journals Online (AJOL)

Purpose: To design a dual inhibitor of natural origin capable of targeting ErbB1 and ErbB2 kinases for the treatment of lung cancer. Method: Advanced In silico drug designing techniques were explored in this study. Sequence and structure analysis of ErbB1 and ErbB2 was followed by three dimensional (3D) ...

Extending in silico mechanism-of-action analysis by annotating targets with pathways: application to cellular cytotoxicity readouts.

Science.gov (United States)

Liggi, Sonia; Drakakis, Georgios; Koutsoukas, Alexios; Cortes-Ciriano, Isidro; Martínez-Alonso, Patricia; Malliavin, Thérèse E; Velazquez-Campoy, Adrian; Brewerton, Suzanne C; Bodkin, Michael J; Evans, David A; Glen, Robert C; Carrodeguas, José Alberto; Bender, Andreas

2014-01-01

An in silico mechanism-of-action analysis protocol was developed, comprising molecule bioactivity profiling, annotation of predicted targets with pathways and calculation of enrichment factors to highlight targets and pathways more likely to be implicated in the studied phenotype. The method was applied to a cytotoxicity phenotypic endpoint, with enriched targets/pathways found to be statistically significant when compared with 100 random datasets. Application on a smaller apoptotic set (10 molecules) did not allowed to obtain statistically relevant results, suggesting that the protocol requires modification such as analysis of the most frequently predicted targets/annotated pathways. Pathway annotations improved the mechanism-of-action information gained by target prediction alone, allowing a better interpretation of the predictions and providing better mapping of targets onto pathways.

In silico ADME-Tox modeling: progress and prospects.

Science.gov (United States)

Alqahtani, Saeed

2017-11-01

Although significant progress has been made in high-throughput screening of absorption, distribution, metabolism and excretion, and toxicity (ADME-Tox) properties in drug discovery and development, in silico ADME-Tox prediction continues to play an important role in facilitating the appropriate selection of candidate drugs by pharmaceutical companies prior to expensive clinical trials. Areas covered: This review provides an overview of the available in silico models that have been used to predict the ADME-Tox properties of compounds. It also provides a comprehensive overview and summarization of the latest modeling methods and algorithms available for the prediction of physicochemical characteristics, ADME properties, and drug toxicity issues. Expert opinion: The in silico models currently available have greatly contributed to the knowledge of screening approaches in the early stages of drug discovery and the development process. As the definitive goal of in silico molding is to predict the pharmacokinetics and disposition of compounds in vivo by assembling all kinetic processes within one global model, PBPK models can serve this purpose. However, much work remains to be done in this area to generate more data and input parameters to build more reliable and accurate prediction models.

Comparative genomics of metabolic capacities of regulons controlled by cis-regulatory RNA motifs in bacteria.

Science.gov (United States)

Sun, Eric I; Leyn, Semen A; Kazanov, Marat D; Saier, Milton H; Novichkov, Pavel S; Rodionov, Dmitry A

2013-09-02

In silico comparative genomics approaches have been efficiently used for functional prediction and reconstruction of metabolic and regulatory networks. Riboswitches are metabolite-sensing structures often found in bacterial mRNA leaders controlling gene expression on transcriptional or translational levels.An increasing number of riboswitches and other cis-regulatory RNAs have been recently classified into numerous RNA families in the Rfam database. High conservation of these RNA motifs provides a unique advantage for their genomic identification and comparative analysis. A comparative genomics approach implemented in the RegPredict tool was used for reconstruction and functional annotation of regulons controlled by RNAs from 43 Rfam families in diverse taxonomic groups of Bacteria. The inferred regulons include ~5200 cis-regulatory RNAs and more than 12000 target genes in 255 microbial genomes. All predicted RNA-regulated genes were classified into specific and overall functional categories. Analysis of taxonomic distribution of these categories allowed us to establish major functional preferences for each analyzed cis-regulatory RNA motif family. Overall, most RNA motif regulons showed predictable functional content in accordance with their experimentally established effector ligands. Our results suggest that some RNA motifs (including thiamin pyrophosphate and cobalamin riboswitches that control the cofactor metabolism) are widespread and likely originated from the last common ancestor of all bacteria. However, many more analyzed RNA motifs are restricted to a narrow taxonomic group of bacteria and likely represent more recent evolutionary innovations. The reconstructed regulatory networks for major known RNA motifs substantially expand the existing knowledge of transcriptional regulation in bacteria. The inferred regulons can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. The obtained genome

In silico analysis of a novel MKRN3 missense mutation in familial central precocious puberty.

Science.gov (United States)

Neocleous, Vassos; Shammas, Christos; Phelan, Marie M; Nicolaou, Stella; Phylactou, Leonidas A; Skordis, Nicos

2016-01-01

The onset of puberty is influenced by the interplay of stimulating and restraining factors, many of which have a genetic origin. Premature activation of the GnRH secretion in central precocious puberty (CPP) may arise either from gain-of-function mutations of the KISS1 and KISS1R genes or from loss-of-function manner mutations of the MKRN3 gene leading to MKRN3 deficiency. To explore the genetic causes responsible for CPP and the potential role of the RING finger protein 3 (MKRN3) gene. We investigated potential sequence variations in the intronless MKRN3 gene by Sanger sequencing of the entire 507 amino acid coding region of exon 1 in a family with two affected girls presented with CPP at the age of 6 and 5·7 years, respectively. A novel heterozygous g.Gly312Asp missense mutation in the MKRN3 gene was identified in these siblings. The imprinted MKRN3 missense mutation was also identified as expected in the unaffected father and followed as expected an imprinted mode of inheritance. In silico analysis of the altered missense variant using the computational algorithms Polyphen2, SIFT and Mutation Taster predicted a damage and pathogenic alteration causing CPP. The pathogenicity of the alteration at the protein level via an in silico structural model is also explored. A novel mutation in the MKRN3 gene in two sisters with CPP was identified, supporting the fundamental role of this gene in the suppression of the hypothalamic GnRH neurons. © 2015 John Wiley & Sons Ltd.

Multiple cis-regulatory elements are involved in the complex regulation of the sieve element-specific MtSEO-F1 promoter from Medicago truncatula.

Science.gov (United States)

Bucsenez, M; Rüping, B; Behrens, S; Twyman, R M; Noll, G A; Prüfer, D

2012-09-01

The sieve element occlusion (SEO) gene family includes several members that are expressed specifically in immature sieve elements (SEs) in the developing phloem of dicotyledonous plants. To determine how this restricted expression profile is achieved, we analysed the SE-specific Medicago truncatula SEO-F1 promoter (PMtSEO-F1) by constructing deletion, substitution and hybrid constructs and testing them in transgenic tobacco plants using green fluorescent protein as a reporter. This revealed four promoter regions, each containing cis-regulatory elements that activate transcription in SEs. One of these segments also contained sufficient information to suppress PMtSEO-F1 transcription in the phloem companion cells (CCs). Subsequent in silico analysis revealed several candidate cis-regulatory elements that PMtSEO-F1 shares with other SEO promoters. These putative sieve element boxes (PSE boxes) are promising candidates for cis-regulatory elements controlling the SE-specific expression of PMtSEO-F1. © 2012 German Botanical Society and The Royal Botanical Society of the Netherlands.

FORECAST: Regulatory effects cost analysis software annual

International Nuclear Information System (INIS)

Lopez, B.; Sciacca, F.W.

1991-11-01

Over the past several years the NRC has developed a generic cost methodology for the quantification of cost/economic impacts associated with a wide range of new or revised regulatory requirements. This methodology has been developed to aid the NRC in preparing Regulatory Impact Analyses (RIAs). These generic costing methods can be useful in quantifying impacts both to industry and to the NRC. The FORECAST program was developed to facilitate the use of the generic costing methodology. This PC program integrates the major cost considerations that may be required because of a regulatory change. FORECAST automates much of the calculations typically needed in an RIA and thus reduces the time and labor required to perform these analysis. More importantly, its integrated and consistent treatment of the different cost elements should help assure comprehensiveness, uniformity, and accuracy in the preparation of needed cost estimates

In silico proteome analysis to facilitate proteomics experiments using mass spectrometry

Directory of Open Access Journals (Sweden)

Lindo Micheal

2003-08-01

Full Text Available Abstract Proteomics experiments typically involve protein or peptide separation steps coupled to the identification of many hundreds to thousands of peptides by mass spectrometry. Development of methodology and instrumentation in this field is proceeding rapidly, and effective software is needed to link the different stages of proteomic analysis. We have developed an application, proteogest, written in Perl that generates descriptive and statistical analyses of the biophysical properties of multiple (e.g. thousands protein sequences submitted by the user, for instance protein sequences inferred from the complete genome sequence of a model organism. The application also carries out in silico proteolytic digestion of the submitted proteomes, or subsets thereof, and the distribution of biophysical properties of the resulting peptides is presented. proteogest is customizable, the user being able to select many options, for instance the cleavage pattern of the digestion treatment or the presence of modifications to specific amino acid residues. We show how proteogest can be used to compare the proteomes and digested proteome products of model organisms, to examine the added complexity generated by modification of residues, and to facilitate the design of proteomics experiments for optimal representation of component proteins.

The starch-binding domain family CBM41 - an in silico analysis of evolutionary relationships

DEFF Research Database (Denmark)

Janeček, Štefan; Majzlová, Katarína; Svensson, Birte

2017-01-01

Within the CAZy database, there are 81 carbohydrate-binding module (CBM) families. A CBM represents a non-catalytic domain in a modular arrangement of glycoside hydrolases (GHs). The present in silico study has been focused on starch-binding domains from the family CBM41 that are usually part...

Characterization of Putative cis-Regulatory Elements in Genes Preferentially Expressed in Arabidopsis Male Meiocytes

Directory of Open Access Journals (Sweden)

Junhua Li

2014-01-01

Full Text Available Meiosis is essential for plant reproduction because it is the process during which homologous chromosome pairing, synapsis, and meiotic recombination occur. The meiotic transcriptome is difficult to investigate because of the size of meiocytes and the confines of anther lobes. The recent development of isolation techniques has enabled the characterization of transcriptional profiles in male meiocytes of Arabidopsis. Gene expression in male meiocytes shows unique features. The direct interaction of transcription factors (TFs with DNA regulatory sequences forms the basis for the specificity of transcriptional regulation. Here, we identified putative cis-regulatory elements (CREs associated with male meiocyte-expressed genes using in silico tools. The upstream regions (1 kb of the top 50 genes preferentially expressed in Arabidopsis meiocytes possessed conserved motifs. These motifs are putative binding sites of TFs, some of which share common functions, such as roles in cell division. In combination with cell-type-specific analysis, our findings could be a substantial aid for the identification and experimental verification of the protein-DNA interactions for the specific TFs that drive gene expression in meiocytes.

Restoration of optimal ellipsoid left ventricular geometry: lessons learnt from in silico surgical modelling.

Science.gov (United States)

Adhyapak, Srilakshmi M; Menon, Prahlad G; Rao Parachuri, V

2014-02-01

Several issues that are inherent in the surgical techniques of surgical ventricular restoration (SVR) need specialized devices or techniques to overcome them, which may not always result in optimal outcomes. We used a non-invasive novel in silico modelling technique to study left ventricular (LV) morphology and function before and after SVR. The cardiac magnetic resonance imaging derived actual pre- and postoperative endocardial morphology and function was compared with the in silico analysis of the same. Cardiac magnetic resonance steady state free precession (SSFP) cine images were employed to segment endocardial surface contours over the cardiac cycle. Using the principle of Hausdorff distance to examine phase-to-phase regional endocardial displacement, dyskinetic/akinetic areas were identified at the instant of peak basal contraction velocity. Using a three-dimensional (3D) surface clipping tool, the maximally scarred, dyskinetic or akinetic LV antero-apical areas were virtually resected and a new apex was created. A virtual rectangular patch was created upon the clipped surface LV model by 3D Delaunay triangulation. Presurgical endocardial mechanical function quantified from cine cardiac magnetic resonance, using a technique of spherical harmonics (SPHARM) surface parameterization, was applied onto the virtually clipped and patched LV surface model. Finally, the in silico model of post-SVR LV shape was analysed for quantification of regional left ventricular volumes (RLVVs) and function. This was tested in 2 patients with post-myocardial infarction antero-apical LV aneuryms. Left ventricular mechanical dysynchrony was evaluated by RLVV analysis of pre-SVR, in silico post-SVR and actual post-SVR LV endocardial surface data. Following exclusion of the scarred areas, the virtual resected LV model demonstrated significantly lesser areas of akinesia. The decreases in regional LV volumes in the in silico modelling were significant and comparable with the actual

Comparing Distributions of Environmental Outcomes for Regulatory Environmental Justice Analysis

Directory of Open Access Journals (Sweden)

Glenn Sheriff

2011-05-01

Full Text Available Economists have long been interested in measuring distributional impacts of policy interventions. As environmental justice (EJ emerged as an ethical issue in the 1970s, the academic literature has provided statistical analyses of the incidence and causes of various environmental outcomes as they relate to race, income, and other demographic variables. In the context of regulatory impacts, however, there is a lack of consensus regarding what information is relevant for EJ analysis, and how best to present it. This paper helps frame the discussion by suggesting a set of questions fundamental to regulatory EJ analysis, reviewing past approaches to quantifying distributional equity, and discussing the potential for adapting existing tools to the regulatory context.

In silico toxicology for the pharmaceutical sciences

International Nuclear Information System (INIS)

Valerio, Luis G.

2009-01-01

The applied use of in silico technologies (a.k.a. computational toxicology, in silico toxicology, computer-assisted tox, e-tox, i-drug discovery, predictive ADME, etc.) for predicting preclinical toxicological endpoints, clinical adverse effects, and metabolism of pharmaceutical substances has become of high interest to the scientific community and the public. The increased accessibility of these technologies for scientists and recent regulations permitting their use for chemical risk assessment supports this notion. The scientific community is interested in the appropriate use of such technologies as a tool to enhance product development and safety of pharmaceuticals and other xenobiotics, while ensuring the reliability and accuracy of in silico approaches for the toxicological and pharmacological sciences. For pharmaceutical substances, this means active and impurity chemicals in the drug product may be screened using specialized software and databases designed to cover these substances through a chemical structure-based screening process and algorithm specific to a given software program. A major goal for use of these software programs is to enable industry scientists not only to enhance the discovery process but also to ensure the judicious use of in silico tools to support risk assessments of drug-induced toxicities and in safety evaluations. However, a great amount of applied research is still needed, and there are many limitations with these approaches which are described in this review. Currently, there is a wide range of endpoints available from predictive quantitative structure-activity relationship models driven by many different computational software programs and data sources, and this is only expected to grow. For example, there are models based on non-proprietary and/or proprietary information specific to assessing potential rodent carcinogenicity, in silico screens for ICH genetic toxicity assays, reproductive and developmental toxicity, theoretical

FASTQSim: platform-independent data characterization and in silico read generation for NGS datasets.

Science.gov (United States)

Shcherbina, Anna

2014-08-15

High-throughput next generation sequencing technologies have enabled rapid characterization of clinical and environmental samples. Consequently, the largest bottleneck to actionable data has become sample processing and bioinformatics analysis, creating a need for accurate and rapid algorithms to process genetic data. Perfectly characterized in silico datasets are a useful tool for evaluating the performance of such algorithms. Background contaminating organisms are observed in sequenced mixtures of organisms. In silico samples provide exact truth. To create the best value for evaluating algorithms, in silico data should mimic actual sequencer data as closely as possible. FASTQSim is a tool that provides the dual functionality of NGS dataset characterization and metagenomic data generation. FASTQSim is sequencing platform-independent, and computes distributions of read length, quality scores, indel rates, single point mutation rates, indel size, and similar statistics for any sequencing platform. To create training or testing datasets, FASTQSim has the ability to convert target sequences into in silico reads with specific error profiles obtained in the characterization step. FASTQSim enables users to assess the quality of NGS datasets. The tool provides information about read length, read quality, repetitive and non-repetitive indel profiles, and single base pair substitutions. FASTQSim allows the user to simulate individual read datasets that can be used as standardized test scenarios for planning sequencing projects or for benchmarking metagenomic software. In this regard, in silico datasets generated with the FASTQsim tool hold several advantages over natural datasets: they are sequencing platform independent, extremely well characterized, and less expensive to generate. Such datasets are valuable in a number of applications, including the training of assemblers for multiple platforms, benchmarking bioinformatics algorithm performance, and creating challenge

In Silico Screening and In Vitro Activity Measurement of Javamide Analogues as Potential p38 MAPK Inhibitors.

Science.gov (United States)

Park, Jae B

2017-12-13

p38 Mitogen-activated protein kinase (p38 MAPK) is a protein kinase critically involved in the progress of inflammation/stress-associated diseases. Our data suggested that javamide analogues may contain strong anti-inflammation activities, but there is little information about their effects on p38 MAPK. Therefore, in this paper, the effects of thirty javamide analogues on p38 MAPK were investigated using in silico screening and in vitro p38 MAPK assay methods. The javamide analogues were synthesized and their chemical structures were confirmed using nuclear magnetic resonance (NMR) spectroscopic methods. Then, the javamide analogues were screened using an in silico modeling program. The screened analogues demonstrated a wide range of binding energy (ΔE; -20 to -39) and several analogues with ΔE; -34 to -39 showed strong binding affinity to p38 MAPK. In vitro p38 MAPK assay, the kinase was significantly inhibited by the analogues with great binding energy (ΔE; -34 to -39) and in silico scores (Avg. score; -27.5 to -29.3). Furthermore, the comparative analysis of both assays showed a positive correlation between the in silico scores and p38 MAPK inhibition. In fact, the javamide analogues with top five in silico scores (Avg. score; -27.5 to -29.3) were found to inhibit p38 MAPK by 27-31% ( p silico score (Avg. score; -29.2) inhibited p38 MAPK (IC 50 = 9.9 μM) a little better than its methyl ester with best in silico score (Avg. score; -29.3). To support the ability to inhibit p38 MAPK, the treatment of javamide-II-ethyl and -methyl esters could suppress the production of IL-8 and MCP-1 protein significantly by 22-73% ( p silico and in vitro assay approach may be a useful and efficient solution as a functional screening approach in searching new lead compounds for targeted molecules.

Computational Genetic Regulatory Networks Evolvable, Self-organizing Systems

CERN Document Server

Knabe, Johannes F

2013-01-01

Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting fr...

Strength of bond with Comspan Opaque to three silicoated alloys and titanium.

Science.gov (United States)

Hansson, O

1990-06-01

In Sweden high-gold alloys or cobalt-chromium alloys are used for resin-bonded prostheses. The bond strength between a resin cement and different sandblasted or silicoated metals were measured before and after thermocycling; in connection with this some rapid thermocycling methods were studied. The effect of different storage times and different protection coatings on bond strength were tested. Finally, the influence of rubbing and contamination with saliva on bond strength were investigated. Silicoating increased the bond strength significantly. The highest bond strengths were these of silicoated Wirobond and titanium, unsusceptible to thermal stress; the bond strengths of the sandblasted metals were the weakest, and sensitive to thermocycling as well. The influence on bond strength for silicoated gold alloys, protected with an unpolymerized composite resin coating, stored in sealed plastic bags up to 7 days, was negligible. Rubbing and contamination with saliva did not influence bond strength. Preferably, silicoated Wirobond and titanium should be used for resin-bonded prostheses, but gold alloys may still be adequate for clinical use. The experimental method described for storing, sealing, and cleaning the silicoated metal surfaces in this article can be recommended for laboratory and clinical use.

78 FR 27235 - Technical Guidance for Assessing Environmental Justice in Regulatory Analysis

Science.gov (United States)

2013-05-09

... Justice in Regulatory Analysis.'' The purpose of this guidance is to provide EPA analysts with technical...-566-2363. Mail: Technical Guidance for Assessing Environmental Justice in Regulatory Analysis... ENVIRONMENTAL PROTECTION AGENCY [EPA-HQ-OA-2013-0320; FRL-9810-5] Technical Guidance for Assessing...

In-silico studies in Chinese herbal medicines' research: evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date.

Science.gov (United States)

Barlow, D J; Buriani, A; Ehrman, T; Bosisio, E; Eberini, I; Hylands, P J

2012-04-10

The available databases that catalogue information on traditional Chinese medicines are reviewed in terms of their content and utility for in-silico research on Chinese herbal medicines, as too are the various protein database resources, and the software available for use in such studies. The software available for bioinformatics and 'omics studies of Chinese herbal medicines are summarised, and a critical evaluation given of the various in-silico methods applied in screening Chinese herbal medicines, including classification trees, neural networks, support vector machines, docking and inverse docking algorithms. Recommendations are made regarding any future in-silico studies of Chinese herbal medicines. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

In Silico survey of functional coding variants in human AEG-1 gene ...

African Journals Online (AJOL)

Background and aims: Non-synonymous (ns)SNPs represent typical genetic variations that may potentially affect the structure or function of expressed proteins and therefore could have an impact on complex disorders. A computational-based (In Silico) analysis has been done to evaluate the phenotypic effect of nsSNPs in ...

Structural modeling and in silico analysis of human superoxide dismutase 2.

Directory of Open Access Journals (Sweden)

Mariana Dias Castela de Carvalho

Full Text Available Aging in the world population has increased every year. Superoxide dismutase 2 (Mn-SOD or SOD2 protects against oxidative stress, a main factor influencing cellular longevity. Polymorphisms in SOD2 have been associated with the development of neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, as well as psychiatric disorders, such as schizophrenia, depression and bipolar disorder. In this study, all of the described natural variants (S10I, A16V, E66V, G76R, I82T and R156W of SOD2 were subjected to in silico analysis using eight different algorithms: SNPeffect, PolyPhen-2, PhD-SNP, PMUT, SIFT, SNAP, SNPs&GO and nsSNPAnalyzer. This analysis revealed disparate results for a few of the algorithms. The results showed that, from at least one algorithm, each amino acid substitution appears to harmfully affect the protein. Structural theoretical models were created for variants through comparative modelling performed using the MHOLline server (which includes MODELLER and PROCHECK and ab initio modelling, using the I-Tasser server. The predicted models were evaluated using TM-align, and the results show that the models were constructed with high accuracy. The RMSD values of the modelled mutants indicated likely pathogenicity for all missense mutations. Structural phylogenetic analysis using ConSurf revealed that human SOD2 is highly conserved. As a result, a human-curated database was generated that enables biologists and clinicians to explore SOD2 nsSNPs, including predictions of their effects and visualisation of the alignment of both the wild-type and mutant structures. The database is freely available at http://bioinfogroup.com/database and will be regularly updated.

In silico and in vivo anti-inflammatory studies of curcuminoids ...

African Journals Online (AJOL)

Purpose: To determine the anti-inflammatory activity of curcuminoids in comparison with that of eugenol in silico, and to determine the anti-inflammatory activity of wound dressings made from zinc oxide powder and liquid turmeric extract with a high curcuminoid content. Methods: In silico studies were conducted, using ...

Provisional in-silico biopharmaceutics classification (BCS) to guide oral drug product development.

Science.gov (United States)

Wolk, Omri; Agbaria, Riad; Dahan, Arik

2014-01-01

The main objective of this work was to investigate in-silico predictions of physicochemical properties, in order to guide oral drug development by provisional biopharmaceutics classification system (BCS). Four in-silico methods were used to estimate LogP: group contribution (CLogP) using two different software programs, atom contribution (ALogP), and element contribution (KLogP). The correlations (r(2)) of CLogP, ALogP and KLogP versus measured LogP data were 0.97, 0.82, and 0.71, respectively. The classification of drugs with reported intestinal permeability in humans was correct for 64.3%-72.4% of the 29 drugs on the dataset, and for 81.82%-90.91% of the 22 drugs that are passively absorbed using the different in-silico algorithms. Similar permeability classification was obtained with the various in-silico methods. The in-silico calculations, along with experimental melting points, were then incorporated into a thermodynamic equation for solubility estimations that largely matched the reference solubility values. It was revealed that the effect of melting point on the solubility is minor compared to the partition coefficient, and an average melting point (162.7 °C) could replace the experimental values, with similar results. The in-silico methods classified 20.76% (± 3.07%) as Class 1, 41.51% (± 3.32%) as Class 2, 30.49% (± 4.47%) as Class 3, and 6.27% (± 4.39%) as Class 4. In conclusion, in-silico methods can be used for BCS classification of drugs in early development, from merely their molecular formula and without foreknowledge of their chemical structure, which will allow for the improved selection, engineering, and developability of candidates. These in-silico methods could enhance success rates, reduce costs, and accelerate oral drug products development.

SPO11-C631T Gene Polymorphism: Association With Male Infertility and an in Silico-Analysis

Directory of Open Access Journals (Sweden)

Mohammad Karimian

2016-04-01

Full Text Available Objective: To investigate the association of C631T single nucleotide polymorphisms in SPO11 gene with male infertilityfollowed by an in silico approach. SPO11 is a gene involved in meiosis and spermatogenesis process, which in humans, this gene is located on chromosome 20 (20q13.2-13.3 with 13 exons.Materials and methods: In a case-control study, 200 blood samples were collected from the IVF center (Kashan, Iran including; 100 infertile and 100 healthy control men. SPO11-C631T were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP method.The effects of C631T transition on the structure of mRNA and protein of SPO11 was evaluated by bioinformatics tools.Results: Our data revealed that all subjects were wild-type homozygous inC631T positionsand just a sample from fertile group was heterozygousin C631T (OR: 0.3300, 95% CI: 0.0133 to 8.1992, p = 0.4988.Our in silico-analysis revealed that C631T transition could make fundamental changes in the structure of the mRNA (Score: 0.1983 and protein (PROVEAN Score: -3.371; Reliability Index: 4; Expected Accuracy: 82% of SPO11. Also, C631T substitution could change the aggregation prone regions of the SPO11 protein (dTANGO = 209.99.Conclusion: So even though the SPO11-C631T don’t increase the risk of male infertility, it could be deleterious for themRNA and protein.

Role of in-house safety analysis and research activities in regulatory decision making

International Nuclear Information System (INIS)

Pradhan, Santosh K.; Nagrale, Dhanesh B.; Gaikwad, Avinash J.

2015-01-01

Achievement of an acceptable level of nuclear safety is an essential requirement for the peaceful utilization of nuclear energy. The success of Global Nuclear Safety Regime is built upon a foundation of research. Such research has been sponsored by Governments and industry and has led to improved designs, safer and more reliable plant operation, and improvements in operating plant efficiency. A key element of this research has been the nuclear safety research performed or sponsored by regulatory organizations. In part, it has been the safety research performed or sponsored by regulatory organizations that has contributed to improved safety and has laid the foundation for activities such as risk-informed regulation, plant life extension, improved plant performance (e.g. power uprates) and new plant designs. The regulatory research program is meant to improve the regulatory authority’s knowledge where uncertainty exists, where safety margins are not well-characterized, and where regulatory decisions need to be confirmed in existing or new designs and technologies. The regulatory body get research initiated either in-house or by the licensee or through technical support organizations (TSOs). Research and analysis carried out within the regulatory body is of immense value in this context. This could be in the form of analysis of safety significant events, analysis of severe accidents, review of operating experience, independent checks of critical designs and even review of operator responses under different situations towards arriving at modifications to training programmes and licensing procedures for operating personnel. A latent benefit of regulatory research carried out by the regulators themselves is that it improves their technical competence considerably which in turn leads to high quality safety reviews and improved regulation in general. The aim of the present paper is to provide an overview of role of regulatory research and the in-house regulatory safety

Empirical Bayes conditional independence graphs for regulatory network recovery

Science.gov (United States)

Mahdi, Rami; Madduri, Abishek S.; Wang, Guoqing; Strulovici-Barel, Yael; Salit, Jacqueline; Hackett, Neil R.; Crystal, Ronald G.; Mezey, Jason G.

2012-01-01

Motivation: Computational inference methods that make use of graphical models to extract regulatory networks from gene expression data can have difficulty reconstructing dense regions of a network, a consequence of both computational complexity and unreliable parameter estimation when sample size is small. As a result, identification of hub genes is of special difficulty for these methods. Methods: We present a new algorithm, Empirical Light Mutual Min (ELMM), for large network reconstruction that has properties well suited for recovery of graphs with high-degree nodes. ELMM reconstructs the undirected graph of a regulatory network using empirical Bayes conditional independence testing with a heuristic relaxation of independence constraints in dense areas of the graph. This relaxation allows only one gene of a pair with a putative relation to be aware of the network connection, an approach that is aimed at easing multiple testing problems associated with recovering densely connected structures. Results: Using in silico data, we show that ELMM has better performance than commonly used network inference algorithms including GeneNet, ARACNE, FOCI, GENIE3 and GLASSO. We also apply ELMM to reconstruct a network among 5492 genes expressed in human lung airway epithelium of healthy non-smokers, healthy smokers and individuals with chronic obstructive pulmonary disease assayed using microarrays. The analysis identifies dense sub-networks that are consistent with known regulatory relationships in the lung airway and also suggests novel hub regulatory relationships among a number of genes that play roles in oxidative stress and secretion. Availability and implementation: Software for running ELMM is made available at http://mezeylab.cb.bscb.cornell.edu/Software.aspx. Contact: ramimahdi@yahoo.com or jgm45@cornell.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22685074

Stochastic models for the in silico simulation of synaptic processes

OpenAIRE

Bracciali, Andrea; Brunelli, Marcello; Cataldo, Enrico; Degano, Pierpaolo

2008-01-01

Background Research in life sciences is benefiting from a large availability of formal description techniques and analysis methodologies. These allow both the phenomena investigated to be precisely modeled and virtual experiments to be performed in silico. Such experiments may result in easier, faster, and satisfying approximations of their in vitro/vivo counterparts. A promising approach is represented by the study of biological phenomena as a collection of interactive entities through proce...

Optimization of an In silico Cardiac Cell Model for Proarrhythmia Risk Assessment

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Sara Dutta

2017-08-01

Full Text Available Drug-induced Torsade-de-Pointes (TdP has been responsible for the withdrawal of many drugs from the market and is therefore of major concern to global regulatory agencies and the pharmaceutical industry. The Comprehensive in vitro Proarrhythmia Assay (CiPA was proposed to improve prediction of TdP risk, using in silico models and in vitro multi-channel pharmacology data as integral parts of this initiative. Previously, we reported that combining dynamic interactions between drugs and the rapid delayed rectifier potassium current (IKr with multi-channel pharmacology is important for TdP risk classification, and we modified the original O'Hara Rudy ventricular cell mathematical model to include a Markov model of IKr to represent dynamic drug-IKr interactions (IKr-dynamic ORd model. We also developed a novel metric that could separate drugs with different TdP liabilities at high concentrations based on total electronic charge carried by the major inward ionic currents during the action potential. In this study, we further optimized the IKr-dynamic ORd model by refining model parameters using published human cardiomyocyte experimental data under control and drug block conditions. Using this optimized model and manual patch clamp data, we developed an updated version of the metric that quantifies the net electronic charge carried by major inward and outward ionic currents during the steady state action potential, which could classify the level of drug-induced TdP risk across a wide range of concentrations and pacing rates. We also established a framework to quantitatively evaluate a system's robustness against the induction of early afterdepolarizations (EADs, and demonstrated that the new metric is correlated with the cell's robustness to the pro-EAD perturbation of IKr conductance reduction. In summary, in this work we present an optimized model that is more consistent with experimental data, an improved metric that can classify drugs at

Economic analysis requirements in support of orbital debris regulatory policy

Science.gov (United States)

Greenberg, Joel S.

1996-10-01

As the number of Earth orbiting objects increases so does the potential for generating orbital debris with the consequent increase in the likelihood of impacting and damaging operating satellites. Various debris remediation approaches are being considered that encompass both in-orbit and return-to-Earth schema and have varying degrees of operations, cost, international competitiveness, and safety implications. Because of the diversity of issues, concerns and long-term impacts, there is a clear need for the setting of government policies that will lead to an orderly abatement of the potential orbital debris hazards. These policies may require the establishment of a supportive regulatory regime. The Department of Transportation is likely to have regulatory responsibilities relating to orbital debris stemming from its charge to protect the public health and safety, safety of property, and national security interests and foreign policy interests of the United States. This paper describes DOT's potential regulatory role relating to orbital debris remediation, the myriad of issues concerning the need for establishing government policies relating to orbital debris remediation and their regulatory implications, the proposed technological solutions and their economic and safety implications. Particular emphasis is placed upon addressing cost-effectiveness and economic analyses as they relate to economic impact analysis in support of regulatory impact analysis.

in silico identification of cross affinity towards Cry1Ac pesticidal protein with receptor enzyme in Bos taurus and sequence, structure analysis of crystal proteins for stability.

Science.gov (United States)

Ebenezer, King Solomon; Nachimuthu, Ramesh; Thiagarajan, Prabha; Velu, Rajesh Kannan

2013-01-01

Any novel protein introduced into the GM crops need to be evaluated for cross affinity on living organisms. Many researchers are currently focusing on the impact of Bacillus thuringiensis cotton on soil and microbial diversity by field experiments. In spite of this, in silico approach might be helpful to elucidate the impact of cry genes. The crystal a protein which was produced by Bt at the time of sporulation has been used as a biological pesticide to target the insectivorous pests like Cry1Ac for Helicoverpa armigera and Cry2Ab for Spodoptera sp. and Heliothis sp. Here, we present the comprehensive in silico analysis of Cry1Ac and Cry2Ab proteins with available in silico tools, databases and docking servers. Molecular docking of Cry1Ac with procarboxypeptidase from Helicoverpa armigera and Cry1Ac with Leucine aminopeptidase from Bos taurus has showed the 125(th) amino acid position to be the preference site of Cry1Ac protein. The structures were compared with each other and it showed 5% of similarity. The cross affinity of this toxin that have confirmed the earlier reports of ill effects of Bt cotton consumed by cattle.

Analysis of NRC Regulatory Guide 1.21 Revision 2

Energy Technology Data Exchange (ETDEWEB)

Kim, Sung Il; Yook, Dae Sik; Lee, Byung Soo [KINS, Daejeon (Korea, Republic of)

2015-05-15

It is essential to have a degree of uniformity in the methods used for measuring, evaluating, recording, and reporting data on radioactive material in effluents and solid wastes. For this purpose, the U.S. Nuclear Regulatory Commission (NRC) released a revised version of the Regulatory Guide 1.21 'Measuring, evaluating, and reporting radioactive material in liquid and gaseous effluents and solid waste' (revision 2) in 2009, updating the revision 1 version released in 1974. This study compares the previous revision 1 (1974) version with the revision 2 (2009) version to elaborate on the application of the guidelines to Korea. This study consists of an analysis of the 2009 Revision 2 version of the U.S. NRC Regulatory Guidelines 1.21 and an exposition of methods for its application in the domestic environment. Major revisions were made to allow for the adoption of a risk informed approach. Radionuclides with lower than 1% contribution to emission or radiation levels can be selected as principal radionuclides. Requirements for analysis of leaks and spills have been reinforced, with additional groundwater monitoring and hydrological data analysis becoming necessary.

An In silico approach for the evaluation of DNA barcodes

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Shehzad Wasim

2010-07-01

Full Text Available Abstract Background DNA barcoding is a key tool for assessing biodiversity in both taxonomic and environmental studies. Essential features of barcodes include their applicability to a wide spectrum of taxa and their ability to identify even closely related species. Several DNA regions have been proposed as barcodes and the region selected strongly influences the output of a study. However, formal comparisons between barcodes remained limited until now. Here we present a standard method for evaluating barcode quality, based on the use of a new bioinformatic tool that performs in silico PCR over large databases. We illustrate this approach by comparing the taxonomic coverage and the resolution of several DNA regions already proposed for the barcoding of vertebrates. To assess the relationship between in silico and in vitro PCR, we also developed specific primers amplifying different species of Felidae, and we tested them using both kinds of PCR Results Tests on specific primers confirmed the correspondence between in silico and in vitro PCR. Nevertheless, results of in silico and in vitro PCRs can be somehow different, also because tuning PCR conditions can increase the performance of primers with limited taxonomic coverage. The in silico evaluation of DNA barcodes showed a strong variation of taxonomic coverage (i.e., universality: barcodes based on highly degenerated primers and those corresponding to the conserved region of the Cyt-b showed the highest coverage. As expected, longer barcodes had a better resolution than shorter ones, which are however more convenient for ecological studies analysing environmental samples. Conclusions In silico PCR could be used to improve the performance of a study, by allowing the preliminary comparison of several DNA regions in order to identify the most appropriate barcode depending on the study aims.

Contribution of a fuzzy expert system to regulatory impact analysis

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Marco Antônio da Cunha

2015-09-01

Full Text Available Regulatory Impact Analysis (RIA has been consolidating in Brazilian regulatory agencies throughout the last decades. The RIA methodology aims to examine the regulatory process, measure the costs and benefits generated, as well as other effects of social, political or economic nature caused by a new or an existing regulation. By analysing each regulatory option, the expert or regulator faces a myriad of variables, usually of qualitative nature, that are difficult to measure and with a high degree of uncertainty. This research complements the existing literature, given the scarcity of decision support models in RIA that – regardless of the problem treated – incorporate the tacit knowledge of the regulation expert. This paper proposes an exploratory approach using a Fuzzy Expert System, which therefore helps to enrich the decision process in the final stage of comparison of the regulatory options.

In Silico Screening for Biothreat Countermeasures

National Research Council Canada - National Science Library

Westerhoff, Lance M

2006-01-01

The current state of the art of in silico drug discovery or computer aided drug discovery relies almost exclusively on molecular mechanics force fields, such as AMBER and CHARMM, and empirical potentials...

In silico panning for a non-competitive peptide inhibitor

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Ikebukuro Kazunori

2007-01-01

Full Text Available Abstract Background Peptide ligands have tremendous therapeutic potential as efficacious drugs. Currently, more than 40 peptides are available in the market for a drug. However, since costly and time-consuming synthesis procedures represent a problem for high-throughput screening, novel procedures to reduce the time and labor involved in screening peptide ligands are required. We propose the novel approach of 'in silico panning' which consists of a two-stage screening, involving affinity selection by docking simulation and evolution of the peptide ligand using genetic algorithms (GAs. In silico panning was successfully applied to the selection of peptide inhibitor for water-soluble quinoprotein glucose dehydrogenase (PQQGDH. Results The evolution of peptide ligands for a target enzyme was achieved by combining a docking simulation with evolution of the peptide ligand using genetic algorithms (GAs, which mimic Darwinian evolution. Designation of the target area as next to the substrate-binding site of the enzyme in the docking simulation enabled the selection of a non-competitive inhibitor. In all, four rounds of selection were carried out on the computer; the distribution of the docking energy decreased gradually for each generation and improvements in the docking energy were observed over the four rounds of selection. One of the top three selected peptides with the lowest docking energy, 'SERG' showed an inhibitory effect with Ki value of 20 μM. PQQGDH activity, in terms of the Vmax value, was 3-fold lower than that of the wild-type enzyme in the presence of this peptide. The mechanism of the SERG blockage of the enzyme was identified as non-competitive inhibition. We confirmed the specific binding of the peptide, and its equilibrium dissociation constant (KD value was calculated as 60 μM by surface plasmon resonance (SPR analysis. Conclusion We demonstrate an effective methodology of in silico panning for the selection of a non

Sociotechnical systems as a framework for regulatory system design and evaluation: Using Work Domain Analysis to examine a new regulatory system.

Science.gov (United States)

Carden, Tony; Goode, Natassia; Read, Gemma J M; Salmon, Paul M

2017-03-15

Like most work systems, the domain of adventure activities has seen a series of serious incidents and subsequent calls to improve regulation. Safety regulation systems aim to promote safety and reduce accidents. However, there is scant evidence they have led to improved safety outcomes. In fact there is some evidence that the poor integration of regulatory system components has led to adverse safety outcomes in some contexts. Despite this, there is an absence of methods for evaluating regulatory and compliance systems. This article argues that sociotechnical systems theory and methods provide a suitable framework for evaluating regulatory systems. This is demonstrated through an analysis of a recently introduced set of adventure activity regulations. Work Domain Analysis (WDA) was used to describe the regulatory system in terms of its functional purposes, values and priority measures, purpose-related functions, object-related processes and cognitive objects. This allowed judgement to be made on the nature of the new regulatory system and on the constraints that may impact its efficacy following implementation. Importantly, the analysis suggests that the new system's functional purpose of ensuring safe activities is not fully supported in terms of the functions and objects available to fulfil them. Potential improvements to the design of the system are discussed along with the implications for regulatory system design and evaluation across the safety critical domains generally. Copyright © 2017 Elsevier Ltd. All rights reserved.

Towards in silico prognosis using big data

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Ohs Nicholas

2016-09-01

Full Text Available Clinical diagnosis and prognosis usually rely on few or even single measurements despite clinical big data being available. This limits the exploration of complex diseases such as adolescent idiopathic scoliosis (AIS where the associated low bone mass remains unexplained. Observed low physical activity and increased RANKL/OPG, however, both indicate a mechanobiological cause. To deepen disease understanding, we propose an in silico prognosis approach using clinical big data, i.e. medical images, serum markers, questionnaires and live style data from mobile monitoring devices and explore the role of inadequate physical activity in a first AIS prototype. It employs a cellular automaton (CA to represent the medical image, micro-finite element analysis to calculate loading, and a Boolean network to integrate the other biomarkers. Medical images of the distal tibia, physical activity scores, and vitamin D and PTH levels were integrated as measured clinically while the time development of bone density and RANKL/OPG was observed. Simulation of an AIS patient with normal physical activity and patient-specific vitamin D and PTH levels showed minor changes in bone density whereas the simulation of the same AIS patient but with reduced physical activity led to low density. Both showed unchanged RANKL/OPG and considerable cortical resorption. We conclude that our integrative in silico approach allows to account for a variety of clinical big data to study complex diseases.

FORECAST: Regulatory effects cost analysis software manual -- Version 4.1. Revision 1

International Nuclear Information System (INIS)

Lopez, B.; Sciacca, F.W.

1996-07-01

The FORECAST program was developed to facilitate the preparation of the value-impact portion of NRC regulatory analyses. This PC program integrates the major cost and benefit considerations that may result from a proposed regulatory change. FORECAST automates much of the calculations typically needed in a regulatory analysis and thus reduces the time and labor required to perform these analyses. More importantly, its integrated and consistent treatment of the different value-impact considerations should help assure comprehensiveness, uniformity, and accuracy in the preparation of NRC regulatory analyses. The Current FORECAST Version 4.1 has been upgraded from the previous version and now includes an uncertainty package, an automatic cost escalation package, and other improvements. In addition, it now explicitly addresses public health impacts, occupational health impacts, onsite property damage, and government costs. Thus, FORECAST Version 4.1 can treat all attributes normally quantified in a regulatory analysis

Editorial: in silico drug design and medicinal chemistry).

Science.gov (United States)

Singla, Rajeev K

2015-01-01

Medicinal chemistry is not limited to molecules, their structures and design but also highly cohesive to pharmacological activities. The potency of a molecule varies by its structure. Hence structural activity relationship is the sub-branch which deals with the estimation of ability of a molecule in depicting any pharmacological activity. In silico drug design is a novel technique which is employed in designing a molecule by using computer aided software’s and bringing a superior and potent molecule. In recent years, in silico drug design has been merged with medicinal chemistry especially by the techniques like ligand based strategy to isolate the required structures. By such strategic techniques, there are high chances of delivering high throughput screening which involves of screening large number of molecules in a very less time. Involvement of such techniques would be a boon for development of new drug entity as it can aid in development of newer, safe, effective and potent drug molecules. Hence, the present issue is aimed to emphasize the cohesion between in silico drug design and it significance in medicinal chemistry. The articles which would be published will mainly focus on the role of in silico drug design techniques in the development of molecules to target various disease and disorders. Molecules can from natural/ synthetic/semi synthetic origin. Articles will be a treasure box consisting of employment of computational methods for unprecedented molecules. The issue will be sure an endorsement for international readership and researchers.

In Silico Ocular Pharmacokinetic Modeling: Delivery of Topical FK962 to Retina.

Science.gov (United States)

Mori, Ayumi; Yabuta, Chiho; Kishimoto, Yayoi; Kozai, Seiko; Ohtori, Akira; Shearer, Thomas R; Azuma, Mitsuyoshi

2017-09-01

To establish the in silico ocular pharmacokinetic modeling for eye drops, and to simulate the dose regimen for FK962 in human choroid/retinal diseases. Pharmacokinetics for FK962 in vivo was performed by a single instillation of drops containing 0.1% 14 C-FK962 in rabbit eyes. Permeation of FK962 across the cornea, sclera, and choroid/retina was measured in vitro. Neurite elongation by FK962 was measured in cultured rat retinal ganglion cells. Parameters from the experimental data were used in an improved in silico model of ocular pharmacokinetics of FK962 in man. The mean concentration of FK962 in ocular tissues predicted by in silico modeling was consistent with in vivo results, validating the in silico model. FK962 rapidly penetrated into the anterior and posterior segments of the eye and then diffused into the vitreous body. The in silico pharmacokinetic modeling also predicted that a dose regimen of 0.0054% FK962 twice per day would produce biologically effective concentrations of FK962 in the choroid/retina, where FK962 facilitates rat neurite elongation. Our in silico model for ocular pharmacokinetics is useful (1) for predicting drug concentrations in specific ocular tissues after topical instillation, and (2) for suggesting the optimal dose regimens for eye drops. The pharmacodynamics for FK962 produced by this model may be useful for clinical trials against retinal neuropathy.

Evolving phenotypic networks in silico.

Science.gov (United States)

François, Paul

2014-11-01

Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

Regulatory analysis for USI A-1, Water Hammer

International Nuclear Information System (INIS)

Serkiz, A.W.

1984-03-01

This is the staff's regulatory analysis dealing with the resolution of the Unresolved Safety Issue A-1, Water Hammer. This report contains the value-impact analysis for this issue, public comments received, and staff response, or action taken, in response to those comments. The staff's technical findings regarding water hammer in nuclear power plants are contained in NUREG-0927

Analytical workflow of double-digest restriction site-associated DNA sequencing based on empirical and in silico optimization in tomato.

Science.gov (United States)

Shirasawa, Kenta; Hirakawa, Hideki; Isobe, Sachiko

2016-04-01

Double-digest restriction site-associated DNA sequencing (ddRAD-Seq) enables high-throughput genome-wide genotyping with next-generation sequencing technology. Consequently, this method has become popular in plant genetics and breeding. Although computational in silico prediction of restriction sites from the genome sequence is recognized as an effective approach for choosing the restriction enzymes to be used, few reports have evaluated the in silico predictions in actual experimental data. In this study, we designed and demonstrated a workflow for in silico and empirical ddRAD-Seq analysis in tomato, as follows: (i)in silico prediction of optimum restriction enzymes from the reference genome, (ii) verification of the prediction by actual ddRAD-Seq data of four restriction enzyme combinations, (iii) establishment of a computational data processing pipeline for high-confidence single nucleotide polymorphism (SNP) calling, and (iv) validation of SNP accuracy by construction of genetic linkage maps. The quality of SNPs based on de novo assembly reference of the ddRAD-Seq reads was comparable with that of SNPs obtained using the published reference genome of tomato. Comparisons of SNP calls in diverse tomato lines revealed that SNP density in the genome influenced the detectability of SNPs by ddRAD-Seq. In silico prediction prior to actual analysis contributed to optimization of the experimental conditions for ddRAD-Seq, e.g. choices of enzymes and plant materials. Following optimization, this ddRAD-Seq pipeline could help accelerate genetics, genomics, and molecular breeding in both model and non-model plants, including crops. © The Author 2016. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Transcriptional Regulatory Network Analysis of MYB Transcription Factor Family Genes in Rice

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Shuchi eSmita

2015-12-01

Full Text Available MYB transcription factor (TF is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by top down and guide gene approaches. More than 50% of OsMYBs were strongly correlated under fifty experimental conditions with 51 hub genes via top down approach. Further, clusters were identified using Markov Clustering (MCL. To maximize the clustering performance, parameter evaluation of the MCL inflation score (I was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by guide gene approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought

In-silico-driven metabolic engineering of Pseudomonas putida for enhanced production of poly-hydroxyalkanoates

NARCIS (Netherlands)

Poblete-Castro, I.; Binger, D.; Rodrigues, A.; Becker, J.; Martins Dos Santos, V.A.P.; Wittmann, C.

2013-01-01

Here, we present systems metabolic engineering driven by in-silico modeling to tailor Pseudomonas putida for synthesis of medium chain length PHAs on glucose. Using physiological properties of the parent wild type as constraints, elementary flux mode analysis of a large-scale model of the metabolism

In silico identification of NF-kappaB-regulated genes in pancreatic beta-cells

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Eizirik Decio L

2007-02-01

Full Text Available Abstract Background Pancreatic beta-cells are the target of an autoimmune attack in type 1 diabetes mellitus (T1DM. This is mediated in part by cytokines, such as interleukin (IL-1β and interferon (IFN-γ. These cytokines modify the expression of hundreds of genes, leading to beta-cell dysfunction and death by apoptosis. Several of these cytokine-induced genes are potentially regulated by the IL-1β-activated transcription factor (TF nuclear factor (NF-κB, and previous studies by our group have shown that cytokine-induced NF-κB activation is pro-apoptotic in beta-cells. To identify NF-κB-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-κB responding genes on the basis of putative regulatory elements. Results The performance of linear and quadratic discriminant analysis (LDA, QDA in identifying NF-κB-responding genes was examined on a dataset of 240 positive and negative examples of NF-κB regulation, using stratified cross-validation with an internal leave-one-out cross-validation (LOOCV loop for automated feature selection and noise reduction. LDA performed slightly better than QDA, achieving 61% sensitivity, 91% specificity and 87% positive predictive value, and allowing the identification of 231, 251 and 580 NF-κB putative target genes in insulin-producing INS-1E cells, primary rat beta-cells and human pancreatic islets, respectively. Predicted NF-κB targets had a significant enrichment in genes regulated by cytokines (IL-1β or IL-1β + IFN-γ and double stranded RNA (dsRNA, as compared to genes not regulated by these NF-κB-dependent stimuli. We increased the confidence of the predictions by selecting only evolutionary stable genes, i.e. genes with homologs predicted as NF-κB targets in rat, mouse, human and chimpanzee. Conclusion The present in silico analysis allowed us to identify novel regulatory targets of NF-κB using a supervised classification method based on

In silico environmental chemical science: properties and processes from statistical and computational modelling

Energy Technology Data Exchange (ETDEWEB)

Tratnyek, P. G.; Bylaska, Eric J.; Weber, Eric J.

2017-01-01

Quantitative structure–activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with “in silico” results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs using descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for “in silico environmental chemical science” are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.

In silico tools used for compound selection during target-based drug discovery and development.

Science.gov (United States)

Caldwell, Gary W

2015-01-01

The target-based drug discovery process, including target selection, screening, hit-to-lead (H2L) and lead optimization stage gates, is the most common approach used in drug development. The full integration of in vitro and/or in vivo data with in silico tools across the entire process would be beneficial to R&D productivity by developing effective selection criteria and drug-design optimization strategies. This review focuses on understanding the impact and extent in the past 5 years of in silico tools on the various stage gates of the target-based drug discovery approach. There are a large number of in silico tools available for establishing selection criteria and drug-design optimization strategies in the target-based approach. However, the inconsistent use of in vitro and/or in vivo data integrated with predictive in silico multiparameter models throughout the process is contributing to R&D productivity issues. In particular, the lack of reliable in silico tools at the H2L stage gate is contributing to the suboptimal selection of viable lead compounds. It is suggested that further development of in silico multiparameter models and organizing biologists, medicinal and computational chemists into one team with a single accountable objective to expand the utilization of in silico tools in all phases of drug discovery would improve R&D productivity.

Integrated In Silico Analysis of Pathway Designs for Synthetic Photo-Electro-Autotrophy.

Directory of Open Access Journals (Sweden)

Michael Volpers

Full Text Available The strong advances in synthetic biology enable the engineering of novel functions and complex biological features in unprecedented ways, such as implementing synthetic autotrophic metabolism into heterotrophic hosts. A key challenge for the sustainable production of fuels and chemicals entails the engineering of synthetic autotrophic organisms that can effectively and efficiently fix carbon dioxide by using sustainable energy sources. This challenge involves the integration of carbon fixation and energy uptake systems. A variety of carbon fixation pathways and several types of photosystems and other energy uptake systems can be chosen and, potentially, modularly combined to design synthetic autotrophic metabolism. Prior to implementation, these designs can be evaluated by the combination of several computational pathway analysis techniques. Here we present a systematic, integrated in silico analysis of photo-electro-autotrophic pathway designs, consisting of natural and synthetic carbon fixation pathways, a proton-pumping rhodopsin photosystem for ATP regeneration and an electron uptake pathway. We integrated Flux Balance Analysis of the heterotrophic chassis Escherichia coli with kinetic pathway analysis and thermodynamic pathway analysis (Max-min Driving Force. The photo-electro-autotrophic designs are predicted to have a limited potential for anaerobic, autotrophic growth of E. coli, given the relatively low ATP regenerating capacity of the proton pumping rhodopsin photosystems and the high ATP maintenance of E. coli. If these factors can be tackled, our analysis indicates the highest growth potential for the natural reductive tricarboxylic acid cycle and the synthetic pyruvate synthase-pyruvate carboxylate -glyoxylate bicycle. Both carbon fixation cycles are very ATP efficient, while maintaining fast kinetics, which also results in relatively low estimated protein costs for these pathways. Furthermore, the synthetic bicycles are highly

Application of isotopic substitution for studing thermal decomposition of silico-12-tungstic acid

International Nuclear Information System (INIS)

Khakhinov, V.V.; Pinchuk, I.N.; Tumurova, L.V.; Mokhosoev, M.V.

1987-01-01

Using the methods of thermal analysis and isotopic substitution, the mechanism of dehydration and decomposition of silico-12-tungstic acid hydrate is studied. It is found that H-D exchange leads to elevation of temperature of heteropoly acid decomposition. The observed isotopic effect shows that proton transfer is the limiting stage of the reaction

Safety analysis in support of regulatory decision marking

International Nuclear Information System (INIS)

Pomier Baez, L.; Troncoso Fleitas, M.; Valhuerdi Debesa, C.; Valle Cepero, R.; Hernandez, J.L.

1996-01-01

Features of different safety analysis techniques by means of calculation thermohydraulic a probabilistic and severe accidents used in the safety assessment, as well as the development of these techniques in Cuba and their use in support of regulatory decision making are presented

Regulatory control analysis and design for sewer systems

DEFF Research Database (Denmark)

Mollerup, Ane Loft; Mikkelsen, Peter Steen; Thornberg, Dines

2015-01-01

A systematic methodology for regulatory control analysis and design is adapted for sewer system operation and evaluated. The main challenge with adapting the methodology is the handling of the stochastic and transient nature of the rainfall disturbances, inherent to sewer system operation...

In Silico Screening and In Vitro Activity Measurement of Javamide Analogues as Potential p38 MAPK Inhibitors

Directory of Open Access Journals (Sweden)

Jae B. Park

2017-12-01

Full Text Available p38 Mitogen-activated protein kinase (p38 MAPK is a protein kinase critically involved in the progress of inflammation/stress-associated diseases. Our data suggested that javamide analogues may contain strong anti-inflammation activities, but there is little information about their effects on p38 MAPK. Therefore, in this paper, the effects of thirty javamide analogues on p38 MAPK were investigated using in silico screening and in vitro p38 MAPK assay methods. The javamide analogues were synthesized and their chemical structures were confirmed using nuclear magnetic resonance (NMR spectroscopic methods. Then, the javamide analogues were screened using an in silico modeling program. The screened analogues demonstrated a wide range of binding energy (ΔE; −20 to −39 and several analogues with ΔE; −34 to −39 showed strong binding affinity to p38 MAPK. In vitro p38 MAPK assay, the kinase was significantly inhibited by the analogues with great binding energy (ΔE; −34 to −39 and in silico scores (Avg. score; −27.5 to −29.3. Furthermore, the comparative analysis of both assays showed a positive correlation between the in silico scores and p38 MAPK inhibition. In fact, the javamide analogues with top five in silico scores (Avg. score; −27.5 to −29.3 were found to inhibit p38 MAPK by 27–31% (p < 0.05 better than those with less scores (ΔE < −27.0. Especially, javamide-II-O-ethyl ester with relatively high in silico score (Avg. score; −29.2 inhibited p38 MAPK (IC50 = 9.9 μM a little better than its methyl ester with best in silico score (Avg. score; −29.3. To support the ability to inhibit p38 MAPK, the treatment of javamide-II-ethyl and -methyl esters could suppress the production of IL-8 and MCP-1 protein significantly by 22–73% (p < 0.05 in the differentiated THP-1 cells, and the inhibition was slightly stronger by the ethyl ester than the methyl ester. Altogether, this study suggests that javamide-II-O-ethyl ester may

XcisClique: analysis of regulatory bicliques

Directory of Open Access Journals (Sweden)

Grene Ruth

2006-04-01

Full Text Available Abstract Background Modeling of cis-elements or regulatory motifs in promoter (upstream regions of genes is a challenging computational problem. In this work, set of regulatory motifs simultaneously present in the promoters of a set of genes is modeled as a biclique in a suitably defined bipartite graph. A biologically meaningful co-occurrence of multiple cis-elements in a gene promoter is assessed by the combined analysis of genomic and gene expression data. Greater statistical significance is associated with a set of genes that shares a common set of regulatory motifs, while simultaneously exhibiting highly correlated gene expression under given experimental conditions. Methods XcisClique, the system developed in this work, is a comprehensive infrastructure that associates annotated genome and gene expression data, models known cis-elements as regular expressions, identifies maximal bicliques in a bipartite gene-motif graph; and ranks bicliques based on their computed statistical significance. Significance is a function of the probability of occurrence of those motifs in a biclique (a hypergeometric distribution, and on the new sum of absolute values statistic (SAV that uses Spearman correlations of gene expression vectors. SAV is a statistic well-suited for this purpose as described in the discussion. Results XcisClique identifies new motif and gene combinations that might indicate as yet unidentified involvement of sets of genes in biological functions and processes. It currently supports Arabidopsis thaliana and can be adapted to other organisms, assuming the existence of annotated genomic sequences, suitable gene expression data, and identified regulatory motifs. A subset of Xcis Clique functionalities, including the motif visualization component MotifSee, source code, and supplementary material are available at https://bioinformatics.cs.vt.edu/xcisclique/.

In Silico Identification of OncomiRs in Different Cancer Types

Science.gov (United States)

Bhattacharyya, Malay; Bandyopadhyay, Sanghamitra

2012-03-01

The diagnosis, prognosis and therapeutics of various kinds of cancers are challenging domains of research. Current landmark of cancer research at the molecular level mainly focuses on the regulation of genes for studying cancer pathways. Recent investigations highlight that there is a significant association of a class of short RNAs in the progression of different types of cancer. In this paper, the involvement of microRNAs (miRNAs), a type of small endogenous RNAs, is explored in two categories of cancers in human, one tumor-based and another non-tumorous. A new approach of in silico identification of the miRNAs that might be associated with these cancer types is proposed. The oncomiRs, miRNAs associated with cancer, are identified by analyzing the differentially co-expressed miRNAs and further exploring how they cooperate with each other. Extensive computational analysis on miRNA expression profiles for the discovery of novel oncomiRs is pursued. The results are found to be promising by going deep into the regulatory information available on oncogenes from the up-to-date literature. Some of the miRNAs as oncogenic are identified by the approach like hsa-miR-186 and hsa-miR-154 for leukemia and prostate cancer, respectively, which are not included in standard databases. However, some of the emerging studies give evidences to these findings. Statistical and biological studies, on the other hand, strengthen the effectiveness of the proposed method in futuristic investigations for the exploration of undiscovered oncomiRs. On the whole, these analyses provide insight into the discovery of miRNA markers.

Altered expression of circulating microRNA in plasma of patients with primary osteoarthritis and in silico analysis of their pathways.

Directory of Open Access Journals (Sweden)

Verónica M Borgonio Cuadra

Full Text Available OBJECTIVE: To analyze a set of circulating microRNA (miRNA in plasma from patients with primary Osteoarthritis (OA and describe the biological significance of altered miRNA in OA based on an in silico analysis of their target genes. METHODS: miRNA expression was analyzed using TaqMan Low Density Arrays and independent assays. The search for potential messenger RNA (mRNA targets of the differentially expressed miRNA was performed by means of the miRWalk and miRecords database; we conducted the biological relevance of the predicted miRNA targets by pathway analysis with the Reactome and DAVID databases. RESULTS: We measured the expression of 380 miRNA in OA; 12 miRNA were overexpressed under the OA condition (p value, ≤0.05; fold change, >2. These results were validated by the detection of some selected miRNA by quantitative PCR (qPCR. In silico analysis showed that target messenger RNA (mRNA were potentially regulated by these miRNA, including genes such as SMAD1, IL-1B, COL3A, VEGFA, and FGFR1, important in chondrocyte maintenance and differentiation. Some metabolic pathways affected by the miRNA: mRNA ratio are signaling Bone morphogenetic proteins (BMP, Platelet-derived growth factor (PDGF, and Nerve growth factor (NGF, these latter two involved in the process of pain. CONCLUSIONS: We identified 12 miRNA in the plasma of patients with primary OA. Specific miRNA that are altered in the disease could be released into plasma, either due to cartilage damage or to an inherent cellular mechanism. Several miRNA could regulate genes and pathways related with development of the disease; eight of these circulating miRNA are described, to our knowledge, for first time in OA.

Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias.

Science.gov (United States)

Clarke, Laurence J; Soubrier, Julien; Weyrich, Laura S; Cooper, Alan

2014-11-01

Studies of insect assemblages are suited to the simultaneous DNA-based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR-amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16S) with that of existing markers [16S and cytochrome oxidase c subunit I (COI)] and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico 90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR-amplification bias, typically amplifying a greater percentage of Lepidoptera and Diptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 insect orders and one arachnid. We PCR-amplified the blend using five primer sets, targeting either COI or 16S, with high-throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR and that researchers should be wary of potential bias when selecting metabarcoding markers. © 2014 John Wiley & Sons Ltd.

Identification of novel dipeptidyl peptidase-IV and angiotensin-I-converting enzyme inhibitory peptides from meat proteins using in silico analysis.

Science.gov (United States)

Lafarga, Tomas; O'Connor, Paula; Hayes, Maria

2014-09-01

Angiotensin-I-converting enzyme (ACE-I, EC 3.4.15.1), renin (EC 3.4.23.15), and dipeptidyl peptidase-IV (DPP-IV, EC 3.4.14.5) play key roles in the control of hypertension and the development of type-2 diabetes and other diseases associated with metabolic syndrome. The aim of this work was to utilize known in silico methodologies, peptide databases and software including ProtParam (http://web.expasy.org/protparam/), Basic Local Alignment Tool (BLAST), ExPASy PeptideCutter (http://web.expasy.org/peptide_cutter/) and BIOPEP (http://www.uwm.edu.pl/biochemia/index.php/pl/biopep) to assess the release of potentially bioactive DPP-IV, renin and ACE-I inhibitory peptides from bovine and porcine meat proteins including hemoglobin, collagen and serum albumin. These proteins were chosen as they are found commonly in meat by-products such as bone, blood and low-value meat cuts. In addition, the bioactivities of identified peptides were confirmed using chemical synthesis and in vitro bioassays. The concentration of peptide required to inhibit the activity of ACE-I and DPP-IV by 50% was determined for selected, active peptides. Novel ACE-I and DPP-IV inhibitory peptides were identified in this study using both in silico analysis and a literature search to streamline enzyme selection for peptide production. These novel peptides included the ACE-I inhibitory tri-peptide Ile-Ile-Tyr and the DPP-IV inhibitory tri-peptide Pro-Pro-Leu corresponding to sequences f (182-184) and f (326-328) of both porcine and bovine serum albumin which can be released following hydrolysis with the enzymes papain and pepsin, respectively. This work demonstrates that meat proteins are a suitable resource for the generation of bioactive peptides and further demonstrates the usefulness of in silico methodologies to streamline identification and generation of bioactive peptides. Copyright © 2014 Elsevier Inc. All rights reserved.

Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations.

Science.gov (United States)

Leong, Ivone U S; Stuckey, Alexander; Lai, Daniel; Skinner, Jonathan R; Love, Donald R

2015-05-13

Long QT syndrome (LQTS) is an autosomal dominant condition predisposing to sudden death from malignant arrhythmia. Genetic testing identifies many missense single nucleotide variants of uncertain pathogenicity. Establishing genetic pathogenicity is an essential prerequisite to family cascade screening. Many laboratories use in silico prediction tools, either alone or in combination, or metaservers, in order to predict pathogenicity; however, their accuracy in the context of LQTS is unknown. We evaluated the accuracy of five in silico programs and two metaservers in the analysis of LQTS 1-3 gene variants. The in silico tools SIFT, PolyPhen-2, PROVEAN, SNPs&GO and SNAP, either alone or in all possible combinations, and the metaservers Meta-SNP and PredictSNP, were tested on 312 KCNQ1, KCNH2 and SCN5A gene variants that have previously been characterised by either in vitro or co-segregation studies as either "pathogenic" (283) or "benign" (29). The accuracy, sensitivity, specificity and Matthews Correlation Coefficient (MCC) were calculated to determine the best combination of in silico tools for each LQTS gene, and when all genes are combined. The best combination of in silico tools for KCNQ1 is PROVEAN, SNPs&GO and SIFT (accuracy 92.7%, sensitivity 93.1%, specificity 100% and MCC 0.70). The best combination of in silico tools for KCNH2 is SIFT and PROVEAN or PROVEAN, SNPs&GO and SIFT. Both combinations have the same scores for accuracy (91.1%), sensitivity (91.5%), specificity (87.5%) and MCC (0.62). In the case of SCN5A, SNAP and PROVEAN provided the best combination (accuracy 81.4%, sensitivity 86.9%, specificity 50.0%, and MCC 0.32). When all three LQT genes are combined, SIFT, PROVEAN and SNAP is the combination with the best performance (accuracy 82.7%, sensitivity 83.0%, specificity 80.0%, and MCC 0.44). Both metaservers performed better than the single in silico tools; however, they did not perform better than the best performing combination of in silico

In Silico Medicine: Social, Technological and Symbolic Mediation

Directory of Open Access Journals (Sweden)

Annamaria Carusi

2016-06-01

Full Text Available In silico medicine is still forging a road for itself in the current biomedical landscape. Discursively and rhetorically, it is using a three-way positioning, first, deploying discourses of personalised medicine, second, extending the 3Rs from animal to clinical research, and third, aligning its methods with experimental methods. The discursive and rhetorical positioning in promotions and statements of the programme gives us insight into the sociability of the scientific labour of advancing the programme. Its progress depends on complex social, institutional and technological conditions which are not external to its epistemology, but intricately interwoven with it. This article sets out to show that this is the case through an analysis of the process of computational modelling that is at the core of its epistemology. In this paper I show that the very notion of ‘model’ needs to be re-thought for in silico medicine (as indeed, for most forms of computational modelling, and propose a replacement, in the form of the ‘Model-Simulation-Experiment-System’ or MSE-system, which is simultaneously an epistemological, social and technological system. I argue that the MSE-system is radically mediated by social relations, technologies and symbolic systems. We need now to understand how such mediations operate effectively in the construction of robust MSE-systems.

Bridging plant and human radiation response and DNA repair through an in silico approach

Czech Academy of Sciences Publication Activity Database

Nikitaki, Z.; Pavlopoulou, A.; Holá, Marcela; Donà, M.; Michalopoulos, I.; Balestrazzi, A.; Angelis, Karel; Georgakilas, A. G.

2017-01-01

Roč. 9, č. 6 (2017), č. článku 65. ISSN 2072-6694 R&D Projects: GA ČR GA16-01137S Institutional support: RVO:61389030 Keywords : Bioinformatics * DNA damage repair * In silico analysis * Ionizing radiation * Plant radiation biodosimeter * Ultraviolet radiation Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Oncology

Analysis of Worldwide Regulatory Framework for On-Line Maintenance

International Nuclear Information System (INIS)

Ahn, Sang Kyu; Oh, Kyu Myung; Lee, Chang Ju

2010-01-01

With the increasing economic pressures being faced and the potential for shortening outage times under the conditions of deregulated electricity markets in the world, licensees are motivated to get an increasing amount of online maintenance (OLM). OLM means a kind of planned maintenance of nuclear reactor facilities, including structure, systems, and components (SSCs), during power operation. In Korea, a similar situation is made up, so it needs to establish a regulatory framework for OLM. A few years ago, foreign countries' practices related to OLM were surveyed by the Working Group on Inspection Practices (WGIP) of OECD/NEA/CNRA. The survey results and additional new information of countries' status will be helpful to establish our own regulatory framework for OLM, which are analyzed in this paper. From the analysis, some considerable points to be addressed for establishing a regulatory framework for OLM are suggested

Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens by Using Proteomic Data from a Field Biostimulation Experiment

Science.gov (United States)

Fang, Yilin; Yabusaki, Steven B.; Lipton, Mary S.; Long, Philip E.

2012-01-01

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens—specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment. PMID:23042184

OncoPeptTUME – An in silico platform to study tumor micro-environment

Directory of Open Access Journals (Sweden)

Malini Manoharan

2017-12-01

We applied our in silico platform on the TCGA cancer samples. Our analysis showed that patients with higher CD8 score have better survival in bladder carcinoma, endocervical adenocarcinoma, head & neck, sarcoma, melanoma, thyroid, whereas, patients with higher monocyte score have poor survival in endocervical adenocarcinoma, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, lower grade glioma and liver hepatocellular carcinoma.

In silico toxicology: computational methods for the prediction of chemical toxicity

KAUST Repository

Raies, Arwa B.; Bajic, Vladimir B.

2016-01-01

Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models.

In silico toxicology: computational methods for the prediction of chemical toxicity

KAUST Repository

Raies, Arwa B.

2016-01-06

Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models.

Profiling of The Lemongrass Oil Aroma and Their Structure-Odor Relationship: In Silico Study

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Udrika Lailatul Qodri

2017-05-01

Full Text Available Structure-odor relationship (SOR has previously studied by semantic numerically in different Fragrance. We hypothesise that in silico method such as molecular dynamics, together with docking of the interaction between human olfactory receptor (OR1G1 and ligands, can offer extremely valuable tools of modelling SOR. Hence, the present study was carried out to express the SOR of citronellal oil fraction compare with reference smelling of floral, musk, green, wood, and fruit by employing docking and multiple discriminant analysis (MDA. Our study reveals that the number dissociation constant (Kd, bond distance, HOMO-LUMO (AE, dipole moment, kind of amino acids, Log P, surface area and hydropathy as the variable SOR from in silico anaysis. Our result has shown ligands and OR1G1 interacted with Van Der Waals and electrostatic model. MDA analysis shown molecule reference floral and fraction of lemongrass oil have similar correlation based on variable SOR with linier regression of all variable SOR to Kd value for every reference odor is R2 = 1.

Integration of in vitro biorelevant dissolution and in silico PBPK model of carvedilol to predict bioequivalence of oral drug products.

Science.gov (United States)

Ibarra, Manuel; Valiante, Cristian; Sopeña, Patricia; Schiavo, Alejandra; Lorier, Marianela; Vázquez, Marta; Fagiolino, Pietro

2018-06-15

Bioequivalence implementation in developing countries where a high proportion of similar drug products are being marketed has found several obstacles, impeding regulatory agencies to move forward with this policy. Biopharmaceutical quality of these products, several of which are massively prescribed, remains unknown. In this context, an in vitro-in silico-in vivo approach is proposed as a mean to screen product performance and target specific formulations for bioequivalence assessment. By coupling in vitro biorelevant dissolution testing in USP-4 Apparatus (flow-through cell) with physiologically-based pharmacokinetic (PBPK) modeling in PK-Sim® software (Bayer, Germany), the performance of seven similar products of carvedilol tablets containing 25 mg available in the Uruguayan market were compared with the brand-name drug Dilatrend®. In silico simulations for Dilatrend® were compared with published results of bioequivalence studies performed in fasting conditions allowing model development through a learning and confirming process. Single-dose pharmacokinetic profiles were then simulated for the brand-name drug and two similar drug products selected according to in vitro observations, in a virtual Caucasian population of 1000 subjects (50% male, aged between 18 and 50 years with standard body-weights). Population bioequivalence ratios were estimated revealing that in vitro differences in drug release would have a major impact in carvedilol maximum plasma concentration, leading to a non-bioequivalence outcome. Predictions support the need to perform in vivo bioequivalence for these products of extensive use. Application of the in vitro-in silico-in vivo approach stands as an interesting alternative to tackle and reduce drug product variability in biopharmaceutical quality. Copyright © 2018 Elsevier B.V. All rights reserved.

AutoClickChem: click chemistry in silico.

Directory of Open Access Journals (Sweden)

Jacob D Durrant

Full Text Available Academic researchers and many in industry often lack the financial resources available to scientists working in "big pharma." High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu.

AutoClickChem: click chemistry in silico.

Science.gov (United States)

Durrant, Jacob D; McCammon, J Andrew

2012-01-01

Academic researchers and many in industry often lack the financial resources available to scientists working in "big pharma." High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu.

The Reconstruction and Analysis of Gene Regulatory Networks.

Science.gov (United States)

Zheng, Guangyong; Huang, Tao

2018-01-01

In post-genomic era, an important task is to explore the function of individual biological molecules (i.e., gene, noncoding RNA, protein, metabolite) and their organization in living cells. For this end, gene regulatory networks (GRNs) are constructed to show relationship between biological molecules, in which the vertices of network denote biological molecules and the edges of network present connection between nodes (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). Biologists can understand not only the function of biological molecules but also the organization of components of living cells through interpreting the GRNs, since a gene regulatory network is a comprehensively physiological map of living cells and reflects influence of genetic and epigenetic factors (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). In this paper, we will review the inference methods of GRN reconstruction and analysis approaches of network structure. As a powerful tool for studying complex diseases and biological processes, the applications of the network method in pathway analysis and disease gene identification will be introduced.

Purely in silico BCS classification: science based quality standards for the world's drugs.

Science.gov (United States)

Dahan, Arik; Wolk, Omri; Kim, Young Hoon; Ramachandran, Chandrasekharan; Crippen, Gordon M; Takagi, Toshihide; Bermejo, Marival; Amidon, Gordon L

2013-11-04

BCS classification is a vital tool in the development of both generic and innovative drug products. The purpose of this work was to provisionally classify the world's top selling oral drugs according to the BCS, using in silico methods. Three different in silico methods were examined: the well-established group contribution (CLogP) and atom contribution (ALogP) methods, and a new method based solely on the molecular formula and element contribution (KLogP). Metoprolol was used as the benchmark for the low/high permeability class boundary. Solubility was estimated in silico using a thermodynamic equation that relies on the partition coefficient and melting point. The validity of each method was affirmed by comparison to reference data and literature. We then used each method to provisionally classify the orally administered, IR drug products found in the WHO Model list of Essential Medicines, and the top-selling oral drug products in the United States (US), Great Britain (GB), Spain (ES), Israel (IL), Japan (JP), and South Korea (KR). A combined list of 363 drugs was compiled from the various lists, and 257 drugs were classified using the different in silico permeability methods and literature solubility data, as well as BDDCS classification. Lastly, we calculated the solubility values for 185 drugs from the combined set using in silico approach. Permeability classification with the different in silico methods was correct for 69-72.4% of the 29 reference drugs with known human jejunal permeability, and for 84.6-92.9% of the 14 FDA reference drugs in the set. The correlations (r(2)) between experimental log P values of 154 drugs and their CLogP, ALogP and KLogP were 0.97, 0.82 and 0.71, respectively. The different in silico permeability methods produced comparable results: 30-34% of the US, GB, ES and IL top selling drugs were class 1, 27-36.4% were class 2, 22-25.5% were class 3, and 5.46-14% were class 4 drugs, while ∼8% could not be classified. The WHO list

Transcriptome mining and in silico structural and functional analysis of ascorbic acid and tartaric acid biosynthesis pathway enzymes in rose-scanted geranium.

Science.gov (United States)

Narnoliya, Lokesh K; Sangwan, Rajender S; Singh, Sudhir P

2018-06-01

Rose-scented geranium (Pelargonium sp.) is widely known as aromatic and medicinal herb, accumulating specialized metabolites of high economic importance, such as essential oils, ascorbic acid, and tartaric acid. Ascorbic acid and tartaric acid are multifunctional metabolites of human value to be used as vital antioxidants and flavor enhancing agents in food products. No information is available related to the structural and functional properties of the enzymes involved in ascorbic acid and tartaric acid biosynthesis in rose-scented geranium. In the present study, transcriptome mining was done to identify full-length genes, followed by their bioinformatic and molecular modeling investigations and understanding of in silico structural and functional properties of these enzymes. Evolutionary conserved domains were identified in the pathway enzymes. In silico physicochemical characterization of the catalytic enzymes revealed isoelectric point (pI), instability index, aliphatic index, and grand average hydropathy (GRAVY) values of the enzymes. Secondary structural prediction revealed abundant proportion of alpha helix and random coil confirmations in the pathway enzymes. Three-dimensional homology models were developed for these enzymes. The predicted structures showed significant structural similarity with their respective templates in root mean square deviation analysis. Ramachandran plot analysis of the modeled enzymes revealed that more than 84% of the amino acid residues were within the favored regions. Further, functionally important residues were identified corresponding to catalytic sites located in the enzymes. To, our best knowledge, this is the first report which provides a foundation on functional annotation and structural determination of ascorbic acid and tartaric acid pathway enzymes in rose-scanted geranium.

7 CFR 1700.32 - Program Accounting and Regulatory Analysis.

Science.gov (United States)

2010-01-01

... Administrator with respect to management, information systems, budgets, and other such matters. (a) The... 7 Agriculture 11 2010-01-01 2010-01-01 false Program Accounting and Regulatory Analysis. 1700.32... SERVICE, DEPARTMENT OF AGRICULTURE GENERAL INFORMATION Agency Organization and Functions § 1700.32 Program...

Molecular level in silico studies for oncology. Direct models review

Science.gov (United States)

Psakhie, S. G.; Tsukanov, A. A.

2017-09-01

The combination of therapy and diagnostics in one process "theranostics" is a trend in a modern medicine, especially in oncology. Such an approach requires development and usage of multifunctional hybrid nanoparticles with a hierarchical structure. Numerical methods and mathematical models play a significant role in the design of the hierarchical nanoparticles and allow looking inside the nanoscale mechanisms of agent-cell interactions. The current position of in silico approach in biomedicine and oncology is discussed. The review of the molecular level in silico studies in oncology, which are using the direct models, is presented.

Integrated in silico Analyses of Regulatory and Metabolic Networks of Synechococcus sp. PCC 7002 Reveal Relationships between Gene Centrality and Essentiality

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Hyun-Seob Song

2015-03-01

Full Text Available Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as “topologically important.” Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termed as “functionally important” genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.

In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods.

Science.gov (United States)

Cheng, Feixiong; Shen, Jie; Yu, Yue; Li, Weihua; Liu, Guixia; Lee, Philip W; Tang, Yun

2011-03-01

There is an increasing need for the rapid safety assessment of chemicals by both industries and regulatory agencies throughout the world. In silico techniques are practical alternatives in the environmental hazard assessment. It is especially true to address the persistence, bioaccumulative and toxicity potentials of organic chemicals. Tetrahymena pyriformis toxicity is often used as a toxic endpoint. In this study, 1571 diverse unique chemicals were collected from the literature and composed of the largest diverse data set for T. pyriformis toxicity. Classification predictive models of T. pyriformis toxicity were developed by substructure pattern recognition and different machine learning methods, including support vector machine (SVM), C4.5 decision tree, k-nearest neighbors and random forest. The results of a 5-fold cross-validation showed that the SVM method performed better than other algorithms. The overall predictive accuracies of the SVM classification model with radial basis functions kernel was 92.2% for the 5-fold cross-validation and 92.6% for the external validation set, respectively. Furthermore, several representative substructure patterns for characterizing T. pyriformis toxicity were also identified via the information gain analysis methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

Training needs for toxicity testing in the 21st century: a survey-informed analysis.

Science.gov (United States)

Lapenna, Silvia; Gabbert, Silke; Worth, Andrew

2012-12-01

Current training needs on the use of alternative methods in predictive toxicology, including new approaches based on mode-of-action (MoA) and adverse outcome pathway (AOP) concepts, are expected to evolve rapidly. In order to gain insight into stakeholder preferences for training, the European Commission's Joint Research Centre (JRC) conducted a single-question survey with twelve experts in regulatory agencies, industry, national research organisations, NGOs and consultancies. Stakeholder responses were evaluated by means of theory-based qualitative data analysis. Overall, a set of training topics were identified that relate both to general background information and to guidance for applying alternative testing methods. In particular, for the use of in silico methods, stakeholders emphasised the need for training on data integration and evaluation, in order to increase confidence in applying these methods for regulatory purposes. Although the survey does not claim to offer an exhaustive overview of the training requirements, its findings support the conclusion that the development of well-targeted and tailor-made training opportunities that inform about the usefulness of alternative methods, in particular those that offer practical experience in the application of in silico methods, deserves more attention. This should be complemented by transparent information and guidance on the interpretation of the results generated by these methods and software tools. 2012 FRAME.

Inducible nitric oxide synthase (iNOS) regulatory region variation in non-human primates.

Science.gov (United States)

Roodgar, Morteza; Ross, Cody T; Kenyon, Nicholas J; Marcelino, Gretchen; Smith, David Glenn

2015-04-01

Inducible nitric oxide synthase (iNOS) is an enzyme that plays a key role in intracellular immune response against respiratory infections. Since various species of nonhuman primates exhibit different levels of susceptibility to infectious respiratory diseases, and since variation in regulatory regions of genes is thought to play a key role in expression levels of genes, two candidate regulatory regions of iNOS were mapped, sequenced, and compared across five species of nonhuman primates: African green monkeys (Chlorocebus sabaeus), pig-tailed macaques (Macaca nemestrina), cynomolgus macaques (Macaca fascicularis), Indian rhesus macaques (Macaca mulatta), and Chinese rhesus macaques (M. mulatta). In addition, we conducted an in silico analysis of the transcription factor binding sites associated with genetic variation in these two candidate regulatory regions across species. We found that only one of the two candidate regions showed strong evidence of involvement in iNOS regulation. Specifically, we found evidence of 13 conserved binding site candidates linked to iNOS regulation: AP-1, C/EBPB, CREB, GATA-1, GATA-3, NF-AT, NF-AT5, NF-κB, KLF4, Oct-1, PEA3, SMAD3, and TCF11. Additionally, we found evidence of interspecies variation in binding sites for several regulatory elements linked to iNOS (GATA-3, GATA-4, KLF6, SRF, STAT-1, STAT-3, OLF-1 and HIF-1) across species, especially in African green monkeys relative to other species. Given the key role of iNOS in respiratory immune response, the findings of this study might help guide the direction of future studies aimed to uncover the molecular mechanisms underlying the increased susceptibility of African green monkeys to several viral and bacterial respiratory infections. Copyright © 2015 Elsevier B.V. All rights reserved.

Dipeptidyl peptidase IV inhibitors derived from a mangrove flora Rhizophora mucronata: An in silico approach

Directory of Open Access Journals (Sweden)

Selvaraj Gurudeeban

2012-08-01

Full Text Available Dipeptidyl peptidase IV (DPP IV is responsible for conversion of glucose tolerance (GLP-1, into inactive form. The inhibition of DPP IV would be beneficial in the treatment of diabetes mellitus. Therefore, the aim of the present study was to isolate and evaluate cystine, phenyl acetic acid, acrylamide, caprylone and oleic acid from Rhizophora mucronata inhibitory action on DPP IV inhibitors using in silico approach. In silico analysis of cystine, phenyl acetic acid, acrylamide, caprylone and oleic acid on human apo DPP IV protein was done by using Autodoc 4.0. Among the five compounds cysteine acts as an inhibitor with binding energy -5.89 kcal/mol, seven hydrogen bond interactions at residues VAL459, VAL 459, GLU408, GLU206, ARG358, GLU205 and SER209 to suppresses the action of DPP IV protein.

A flood-based information flow analysis and network minimization method for gene regulatory networks.

Science.gov (United States)

Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias

2013-04-24

Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.

Eucalyptus microsatellites mined in silico: survey and evaluation

Indian Academy of Sciences (India)

2008-04-01

Apr 1, 2008 ... Eucalyptus microsatellites mined in silico: survey and evaluation ... cific regions of the genome of different species (Marques et ..... Received 21 June 2007, in revised form 11 September 2007; accepted 12 September 2007.

Pre-salt new regulatory mark and the economic order: constitutionality analysis

International Nuclear Information System (INIS)

Pinheiro, Marcela Brasil Pedrosa; Araujo, Mayara de Carvalho; Xavier, Yanko Marcius; Guimaraes, Patricia Borba Vilar

2010-01-01

The discovery of vast reserves of hydrocarbons in the pre-salt layer that extends from Espirito Santo to Santa Catarina, added with the economic and strategic value of oil and natural gas, has brought discussion about the reasonableness of the regulatory model adopted so far. Would be prudent to explore these resources through the concession model? From detailed analysis of the doctrinal and bills that aim to inaugurate the new regulatory bills, we sought to answer this question, based majorly on the principles of economic activity applied in our constitutional system. Motivated by the analysis of these constitutional principles proposed, the State is seen as a regulating agent of the economic activities, fulfilling its role to supervise, encourage and plan the direction of national economic system. The sharing model gives greater state involvement and is able to convert the wealth of pre-salt in citizenship, but only if well implemented. Thus, based on constitutional principles and the notion of development as freedom, the conclusion of this paperwork is for the constitutionality of the new regulatory bills. (author)

Regulatory reforms and productivity: An empirical analysis of the Japanese electricity industry

International Nuclear Information System (INIS)

Nakano, Makiko; Managi, Shunsuke

2008-01-01

The Japanese electricity industry has experienced regulatory reforms since the mid-1990s. This article measures productivity in Japan's steam power-generation sector and examines the effect of reforms on the productivity of this industry over the period 1978-2003. We estimate the Luenberger productivity indicator, which is a generalization of the commonly used Malmquist productivity index, using a data envelopment analysis approach. Factors associated with productivity change are investigated through dynamic generalized method of moments (GMM) estimation of panel data. Our empirical analysis shows that the regulatory reforms have contributed to productivity growth in the steam power-generation sector in Japan

In silico studies in drug research against neurodegenerative diseases.

Science.gov (United States)

Makhouri, Farahnaz Rezaei; Ghasemi, Jahan B

2017-08-22

Neurodegenerative diseases such as Alzheimer's disease (AD), progressive neurodegenerative forms of Huntington's disease, Parkinson's disease (PD), amyotrophic lateral sclerosis, spinal cerebellar ataxias, and spinal and bulbar muscular atrophy are described by slow and selective dysfunction and degeneration of neurons and axons in the central nervous system (CNS). Computer-aided or in silico design methods have matured into powerful tools for reducing the number of ligands that should be screened in experimental assays. In the present review, the authors provide a basic background about neurodegenerative diseases and in silico techniques in the drug research. Furthermore, they review the various in silico studies reported against various targets in neurodegenerative diseases, including homology modeling, molecular docking, virtual high-throughput screening, quantitative structure activity relationship (QSAR), hologram quantitative structure activity relationship (HQSAR), 3D pharmacophore mapping, proteochemometrics modeling (PCM), fingerprints, fragment-based drug discovery, Monte Carlo simulation, molecular dynamic (MD) simulation, quantum-mechanical methods for drug design, support vector machines, and machine learning approaches. Neurodegenerative diseases have a multifactorial pathoetiological origin, so scientists have become persuaded that a multi-target therapeutic strategy aimed at the simultaneous targeting of multiple proteins (and therefore etiologies) involved in the development of a disease is recommended in future. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Reconstruction and in silico analysis of metabolic network for an oleaginous yeast, Yarrowia lipolytica.

Directory of Open Access Journals (Sweden)

Pengcheng Pan

Full Text Available With the emergence of energy scarcity, the use of renewable energy sources such as biodiesel is becoming increasingly necessary. Recently, many researchers have focused their minds on Yarrowia lipolytica, a model oleaginous yeast, which can be employed to accumulate large amounts of lipids that could be further converted to biodiesel. In order to understand the metabolic characteristics of Y. lipolytica at a systems level and to examine the potential for enhanced lipid production, a genome-scale compartmentalized metabolic network was reconstructed based on a combination of genome annotation and the detailed biochemical knowledge from multiple databases such as KEGG, ENZYME and BIGG. The information about protein and reaction associations of all the organisms in KEGG and Expasy-ENZYME database was arranged into an EXCEL file that can then be regarded as a new useful database to generate other reconstructions. The generated model iYL619_PCP accounts for 619 genes, 843 metabolites and 1,142 reactions including 236 transport reactions, 125 exchange reactions and 13 spontaneous reactions. The in silico model successfully predicted the minimal media and the growing abilities on different substrates. With flux balance analysis, single gene knockouts were also simulated to predict the essential genes and partially essential genes. In addition, flux variability analysis was applied to design new mutant strains that will redirect fluxes through the network and may enhance the production of lipid. This genome-scale metabolic model of Y. lipolytica can facilitate system-level metabolic analysis as well as strain development for improving the production of biodiesels and other valuable products by Y. lipolytica and other closely related oleaginous yeasts.

In Silico Meets In Vivo: Towards Computational CRISPR-Based sgRNA Design.

Science.gov (United States)

Chuai, Guo-Hui; Wang, Qi-Long; Liu, Qi

2017-01-01

CRISPR-based genome editing has been widely implemented in various cell types. In silico single guide RNA (sgRNA) design is a key step for successful gene editing using the CRISPR system, and continuing efforts are aimed at refining in silico sgRNA design with high on-target efficacy and reduced off-target effects. Many sgRNA design tools are available, but careful assessments of their application scenarios and performance benchmarks across different types of genome-editing data are needed. Efficient in silico models can be built that integrate current heterogeneous genome-editing data to derive unbiased sgRNA design rules and identify key features for improving sgRNA design. Comprehensive evaluation of on-target and off-target effects of sgRNA will allow more precise genome editing and gene therapies using the CRISPR system. Copyright © 2016 Elsevier Ltd. All rights reserved.

Regulatory activities

International Nuclear Information System (INIS)

2001-01-01

This publication, compiled in 8 chapters, presents the regulatory system developed by the Nuclear Regulatory Authority (NRA) of the Argentine Republic. The following activities and developed topics in this document describe: the evolution of the nuclear regulatory activity in Argentina; the Argentine regulatory system; the nuclear regulatory laws and standards; the inspection and safeguards of nuclear facilities; the emergency systems; the environmental systems; the environmental monitoring; the analysis laboratories on physical and biological dosimetry, prenatal irradiation, internal irradiation, radiation measurements, detection techniques on nuclear testing, medical program on radiation protection; the institutional relations with national and international organization; the training courses and meeting; the technical information

In Silico Medicine: The Practitioners’ Points of View Medicine: The Practitioners’ Points of View Medicine:

Directory of Open Access Journals (Sweden)

Matteo Cerri

2016-06-01

Full Text Available In this article, which is assembled from interviews, the main issues of in silico medicine, present and future, are discussed by three scientists who are directly involved in the implementation and development of in silico techniques.

In silico identification of anthropogenic chemicals as ligands of zebrafish sex hormone binding globulin

International Nuclear Information System (INIS)

Thorsteinson, Nels; Ban, Fuqiang; Santos-Filho, Osvaldo; Tabaei, Seyed M.H.; Miguel-Queralt, Solange; Underhill, Caroline; Cherkasov, Artem; Hammond, Geoffrey L.

2009-01-01

Anthropogenic compounds with the capacity to interact with the steroid-binding site of sex hormone binding globulin (SHBG) pose health risks to humans and other vertebrates including fish. Building on studies of human SHBG, we have applied in silico drug discovery methods to identify potential binders for SHBG in zebrafish (Danio rerio) as a model aquatic organism. Computational methods, including; homology modeling, molecular dynamics simulations, virtual screening, and 3D QSAR analysis, successfully identified 6 non-steroidal substances from the ZINC chemical database that bind to zebrafish SHBG (zfSHBG) with low-micromolar to nanomolar affinities, as determined by a competitive ligand-binding assay. We also screened 80,000 commercial substances listed by the European Chemicals Bureau and Environment Canada, and 6 non-steroidal hits from this in silico screen were tested experimentally for zfSHBG binding. All 6 of these compounds displaced the [ 3 H]5α-dihydrotestosterone used as labeled ligand in the zfSHBG screening assay when tested at a 33 μM concentration, and 3 of them (hexestrol, 4-tert-octylcatechol, and dihydrobenzo(a)pyren-7(8H)-one) bind to zfSHBG in the micromolar range. The study demonstrates the feasibility of large-scale in silico screening of anthropogenic compounds that may disrupt or highjack functionally important protein:ligand interactions. Such studies could increase the awareness of hazards posed by existing commercial chemicals at relatively low cost

Transcriptome Profiling and In Silico Analysis of the Antimicrobial Peptides of the Grasshopper Oxya chinensis sinuosa.

Science.gov (United States)

Kim, In-Woo; Markkandan, Kesavan; Lee, Joon Ha; Subramaniyam, Sathiyamoorthy; Yoo, Seungil; Park, Junhyung; Hwang, Jae Sam

2016-11-28

Antimicrobial peptides/proteins (AMPs) are present in all types of organisms, from microbes and plants to vertebrates and invertebrates such as insects. The grasshopper Oxya chinensis sinuosa is an insect species that is widely consumed around the world for its broad medicinal value. However, the lack of available genetic information for this species is an obstacle to understanding the full potential of its AMPs. Analysis of the O. chinensis sinuosa transcriptome and expression profile is essential for extending the available genetic information resources. In this study, we determined the whole-body transcriptome of O. chinensis sinuosa and analyzed the potential AMPs induced by bacterial immunization. A high-throughput RNA-Seq approach generated 94,348 contigs and 66,555 unigenes. Of these unigenes, 36,032 (54.14%) matched known proteins in the NCBI database in a BLAST search. Functional analysis demonstrated that 38,219 unigenes were clustered into 5,499 gene ontology terms. In addition, 26 cDNAs encoding novel AMPs were identified by an in silico approach using public databases. Our transcriptome dataset and AMP profile greatly improve our understanding of O. chinensis sinuosa genetics and provide a huge number of gene sequences for further study, including genes of known importance and genes of unknown function.

Genome-wide comparative analysis reveals human-mouse regulatory landscape and evolution.

Science.gov (United States)

Denas, Olgert; Sandstrom, Richard; Cheng, Yong; Beal, Kathryn; Herrero, Javier; Hardison, Ross C; Taylor, James

2015-02-14

Because species-specific gene expression is driven by species-specific regulation, understanding the relationship between sequence and function of the regulatory regions in different species will help elucidate how differences among species arise. Despite active experimental and computational research, relationships among sequence, conservation, and function are still poorly understood. We compared transcription factor occupied segments (TFos) for 116 human and 35 mouse TFs in 546 human and 125 mouse cell types and tissues from the Human and the Mouse ENCODE projects. We based the map between human and mouse TFos on a one-to-one nucleotide cross-species mapper, bnMapper, that utilizes whole genome alignments (WGA). Our analysis shows that TFos are under evolutionary constraint, but a substantial portion (25.1% of mouse and 25.85% of human on average) of the TFos does not have a homologous sequence on the other species; this portion varies among cell types and TFs. Furthermore, 47.67% and 57.01% of the homologous TFos sequence shows binding activity on the other species for human and mouse respectively. However, 79.87% and 69.22% is repurposed such that it binds the same TF in different cells or different TFs in the same cells. Remarkably, within the set of repurposed TFos, the corresponding genome regions in the other species are preferred locations of novel TFos. These events suggest exaptation of some functional regulatory sequences into new function. Despite TFos repurposing, we did not find substantial changes in their predicted target genes, suggesting that CRMs buffer evolutionary events allowing little or no change in the TFos - target gene associations. Thus, the small portion of TFos with strictly conserved occupancy underestimates the degree of conservation of regulatory interactions. We mapped regulatory sequences from an extensive number of TFs and cell types between human and mouse using WGA. A comparative analysis of this correspondence unveiled the

Development of Regulatory Thermal-Hydraulic Analysis System (RETAS)

Energy Technology Data Exchange (ETDEWEB)

Ahn, Seung-Hoon; Kim, In-Goo; Kim, Hho-Jung; Cho, Yong Jin [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

2007-10-15

A review is provided of the reasons why the Korea Institute of Nuclear Safety needs improvement of the existing codes employed for a regulatory audit. The proposed new organization of the codes, developed or to be developed, is presented together with illustrative applications. Inspection of the quality assurance activities is planned to ensure the robustness of MARS (Multi-dimensional Analysis for Reactor Safety) code, served as a pivot of the organization.

Development of Regulatory Thermal-Hydraulic Analysis System (RETAS)

International Nuclear Information System (INIS)

Ahn, Seung-Hoon; Kim, In-Goo; Kim, Hho-Jung; Cho, Yong Jin

2007-01-01

A review is provided of the reasons why the Korea Institute of Nuclear Safety needs improvement of the existing codes employed for a regulatory audit. The proposed new organization of the codes, developed or to be developed, is presented together with illustrative applications. Inspection of the quality assurance activities is planned to ensure the robustness of MARS (Multi-dimensional Analysis for Reactor Safety) code, served as a pivot of the organization

Cloning and bioinformatic analysis of lovastatin biosynthesis regulatory gene lovE.

Science.gov (United States)

Huang, Xin; Li, Hao-ming

2009-08-05

Lovastatin is an effective drug for treatment of hyperlipidemia. This study aimed to clone lovastatin biosynthesis regulatory gene lovE and analyze the structure and function of its encoding protein. According to the lovastatin synthase gene sequence from genebank, primers were designed to amplify and clone the lovastatin biosynthesis regulatory gene lovE from Aspergillus terrus genomic DNA. Bioinformatic analysis of lovE and its encoding animo acid sequence was performed through internet resources and software like DNAMAN. Target fragment lovE, almost 1500 bp in length, was amplified from Aspergillus terrus genomic DNA and the secondary and three-dimensional structures of LovE protein were predicted. In the lovastatin biosynthesis process lovE is a regulatory gene and LovE protein is a GAL4-like transcriptional factor.

Pharmacological validation of in-silico guided novel nootropic potential of Achyranthes aspera L.

Science.gov (United States)

Gawande, Dinesh Yugraj; Goel, Rajesh Kumar

2015-12-04

Achyranthes aspera (A. aspera) has been used as a brain tonic in folk medicine. Although, ethnic use of medicinal plant has been basis for drug discovery from medicinal plants, but the available in-silico tools can be useful to find novel pharmacological uses of medicinal plants beyond their ethnic use. To validate in-silico prediction for novel nootropic effect of A. aspera by employing battery of tests in mice. Phytoconstituents of A. aspera reported in Dictionary of Natural Product were subjected to in-silico prediction using PASS and Pharmaexpert. The nootropic activity predicted for A. aspera was assessed using radial arm maze, passive shock avoidance and novel object recognition tests in mice. After behavioral evaluation animals were decapitated and their brains were collected and stored for estimation of glutamate levels and acetylcholinesterase activity. In-silico activity spectrum for majority of A. aspera phytoconstituents exhibited excellent prediction score for nootropic activity of this plant. A. aspera extract treatment significantly improved the learning and memory as evident by decreased working memory errors, reference memory errors and latency time in radial arm maze, step through latency in passive shock avoidance and increased recognition index in novel object recognition were observed, moreover significantly enhanced glutamate levels and reduced acetylcholinesterase activity in hippocampus and cortex were observed as compared to the saline treated group. In-silico and in-vivo results suggest that A. aspera plant may improve the learning and memory by modulating the brain glutamatergic and cholinergic neurotransmission. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Toxicological evaluation in silico and in vivo of secondary metabolites of Cissampelos sympodialis in Mus musculus mice following inhalation.

Science.gov (United States)

Alves, Mateus Feitosa; Ferreira, Larissa Adilis Maria Paiva; Gadelha, Francisco Allysson Assis Ferreira; Ferreira, Laércia Karla Diega Paiva; Felix, Mayara Barbalho; Scotti, Marcus Tullius; Scotti, Luciana; de Oliveira, Kardilândia Mendes; Dos Santos, Sócrates Golzio; Diniz, Margareth de Fátima Formiga Melo

2017-12-04

The ethanolic extract of the leaves of Cissampelos sympodialis showed great pharmacological potential, with inflammatory and immunomodulatory activities, however, it showed some toxicological effects. Therefore, this study aims to verify the toxicological potential of alkaloids of the genus Cissampelos through in silico methodologies, to develop a method in LC-MS/MS verifying the presence of alkaloids in the infusion and to evaluate the toxicity of the infusion of the leaves of C. sympodialis when inhaled by Swiss mice. Results in silico showed that alkaloid 93 presented high toxicological potential along with the products of its metabolism. LC-MS/MS results showed that the infusion of the leaves of this plant contained the alkaloids warifteine and methylwarifteine. Finally, the in vivo toxicological analysis of the C. sympodialis infusion showed results, both in biochemistry, organ weights and histological analysis, that the infusion of C. sympodialis leaves presents a low toxicity.

Guideline for regulatory agencies in evaluating contents of root cause analysis by operators

International Nuclear Information System (INIS)

Hata, Takaya; Makino, Maomi; Kosaka, Atsuhiko

2008-01-01

'Guideline for Regulatory Agencies in Evaluating Contents of Root cause Analysis by Operators' was enacted as the policy for new inspection system in Japan. The objective is to indicate the view point to verify the appropriateness of the corrective actions and preventive actions implemented by operators based on root cause analysis and its analysis results. This guideline is leading to take four points into special consideration for adequate application. They are encouragement of further activities of the operators, flexible interpretation of the intention, versatility of the analysis methods and concepts and consideration of no blame culture. Moreover, as view point for regulatory agencies, it indicates with special emphasis that neutrality of the analyzing party, objectivity of analysis result, and logicality of the analysis method are ensured. This guideline shall be continuously reviewed through integration of lessons learned from active use in future. (author)

In silico Identifikation von Abszisinsaeure-regulierten Genen in Arabidopsis thaliana (L.) Heynh.

OpenAIRE

Gómez-Porras, Judith Lucia

2006-01-01

Abscisic acid (ABA) is a major plant hormone that plays an important role during plant growth and development. During vegetative growth ABA mediates (in part) responses to various environmental stresses such as cold, drought and high salinity. The response triggered by ABA includes changes in the transcript level of genes involved in stress tolerance. The aim of this project was the In silico identification of genes putatively regulated by ABA in A. thaliana. In silico predictions were combin...

In Silico Analysis of Putrefaction Pathways in Bacteria and Its Implication in Colorectal Cancer

Directory of Open Access Journals (Sweden)

Harrisham Kaur

2017-11-01

Full Text Available Fermentation of undigested proteins in human gastrointestinal tract (gut by the resident microbiota, a process called bacterial putrefaction, can sometimes disrupt the gut homeostasis. In this process, essential amino acids (e.g., histidine, tryptophan, etc. that are required by the host may be utilized by the gut microbes. In addition, some of the products of putrefaction, like ammonia, putrescine, cresol, indole, phenol, etc., have been implicated in the disease pathogenesis of colorectal cancer (CRC. We have investigated bacterial putrefaction pathways that are known to be associated with such metabolites. Results of the comprehensive in silico analysis of the selected putrefaction pathways across bacterial genomes revealed presence of these pathways in limited bacterial groups. Majority of these bacteria are commonly found in human gut. These include Bacillus, Clostridium, Enterobacter, Escherichia, Fusobacterium, Salmonella, etc. Interestingly, while pathogens utilize almost all the analyzed pathways, commensals prefer putrescine and H2S production pathways for metabolizing the undigested proteins. Further, comparison of the putrefaction pathways in the gut microbiomes of healthy, carcinoma and adenoma datasets indicate higher abundances of putrefying bacteria in the carcinoma stage of CRC. The insights obtained from the present study indicate utilization of possible microbiome-based therapies to minimize the adverse effects of gut microbiome in enteric diseases.

Integrative Genetic and Epigenetic Analysis Uncovers Regulatory Mechanisms of Autoimmune Disease.

Science.gov (United States)

Shooshtari, Parisa; Huang, Hailiang; Cotsapas, Chris

2017-07-06

Genome-wide association studies in autoimmune and inflammatory diseases (AID) have uncovered hundreds of loci mediating risk. These associations are preferentially located in non-coding DNA regions and in particular in tissue-specific DNase I hypersensitivity sites (DHSs). While these analyses clearly demonstrate the overall enrichment of disease risk alleles on gene regulatory regions, they are not designed to identify individual regulatory regions mediating risk or the genes under their control, and thus uncover the specific molecular events driving disease risk. To do so we have departed from standard practice by identifying regulatory regions which replicate across samples and connect them to the genes they control through robust re-analysis of public data. We find significant evidence of regulatory potential in 78/301 (26%) risk loci across nine autoimmune and inflammatory diseases, and we find that individual genes are targeted by these effects in 53/78 (68%) of these. Thus, we are able to generate testable mechanistic hypotheses of the molecular changes that drive disease risk. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

Science.gov (United States)

Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-01

Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723

Diversity and plasticity of Th cell types predicted from regulatory network modelling.

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Aurélien Naldi

Full Text Available Alternative cell differentiation pathways are believed to arise from the concerted action of signalling pathways and transcriptional regulatory networks. However, the prediction of mammalian cell differentiation from the knowledge of the presence of specific signals and transcriptional factors is still a daunting challenge. In this respect, the vertebrate hematopoietic system, with its many branching differentiation pathways and cell types, is a compelling case study. In this paper, we propose an integrated, comprehensive model of the regulatory network and signalling pathways controlling Th cell differentiation. As most available data are qualitative, we rely on a logical formalism to perform extensive dynamical analyses. To cope with the size and complexity of the resulting network, we use an original model reduction approach together with a stable state identification algorithm. To assess the effects of heterogeneous environments on Th cell differentiation, we have performed a systematic series of simulations considering various prototypic environments. Consequently, we have identified stable states corresponding to canonical Th1, Th2, Th17 and Treg subtypes, but these were found to coexist with other transient hybrid cell types that co-express combinations of Th1, Th2, Treg and Th17 markers in an environment-dependent fashion. In the process, our logical analysis highlights the nature of these cell types and their relationships with canonical Th subtypes. Finally, our logical model can be used to explore novel differentiation pathways in silico.

In Silico Pooling of ChIP-seq Control Experiments

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Sun, Guannan; Srinivasan, Rajini; Lopez-Anido, Camila; Hung, Holly A.; Svaren, John; Keleş, Sündüz

2014-01-01

As next generation sequencing technologies are becoming more economical, large-scale ChIP-seq studies are enabling the investigation of the roles of transcription factor binding and epigenome on phenotypic variation. Studying such variation requires individual level ChIP-seq experiments. Standard designs for ChIP-seq experiments employ a paired control per ChIP-seq sample. Genomic coverage for control experiments is often sacrificed to increase the resources for ChIP samples. However, the quality of ChIP-enriched regions identifiable from a ChIP-seq experiment depends on the quality and the coverage of the control experiments. Insufficient coverage leads to loss of power in detecting enrichment. We investigate the effect of in silico pooling of control samples within multiple biological replicates, multiple treatment conditions, and multiple cell lines and tissues across multiple datasets with varying levels of genomic coverage. Our computational studies suggest guidelines for performing in silico pooling of control experiments. Using vast amounts of ENCODE data, we show that pairwise correlations between control samples originating from multiple biological replicates, treatments, and cell lines/tissues can be grouped into two classes representing whether or not in silico pooling leads to power gain in detecting enrichment between the ChIP and the control samples. Our findings have important implications for multiplexing samples. PMID:25380244

Identification and in silico analysis of the Citrus HSP70 molecular chaperone gene family

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Luciano G. Fietto

2007-01-01

Full Text Available The completion of the genome sequencing of the Arabidopsis thaliana model system provided a powerful molecular tool for comparative analysis of gene families present in the genome of economically relevant plant species. In this investigation, we used the sequences of the Arabidopsis Hsp70 gene family to identify and annotate the Citrus Hsp70 genes represented in the CitEST database. Based on sequence comparison analysis, we identified 18 clusters that were further divided into 5 subgroups encoding four mitochondrial mtHsp70s, three plastid csHsp70s, one ER luminal Hsp70 BiP, two HSP110/SSE-related proteins and eight cytosolic Hsp/Hsc70s. We also analyzed the expression profile by digital Northern of each Hsp70 transcript in different organs and in response to stress conditions. The EST database revealed a distinct population distribution of Hsp70 ESTs among isoforms and across the organs surveyed. The Hsp70-5 isoform was highly expressed in seeds, whereas BiP, mitochondrial and plastid HSp70 mRNAs displayed a similar expression profile in the organs analyzed, and were predominantly represented in flowers. Distinct Hsp70 mRNAs were also differentially expressed during Xylella infection and Citrus tristeza viral infection as well as during water deficit. This in silico study sets the groundwork for future investigations to fully characterize functionally the Citrus Hsp70 family and underscores the relevance of Hsp70s in response to abiotic and biotic stresses in Citrus.

Identification of putative and potential cross-reactive chickpea (Cicer arietinum) allergens through an in silico approach.

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Kulkarni, Anuja; Ananthanarayan, Laxmi; Raman, Karthik

2013-12-01

Allergy has become a key cause of morbidity worldwide. Although many legumes (plants in the Fabaceae family) are healthy foods, they may have a number of allergenic proteins. A number of allergens have been identified and characterized in Fabaceae family, such as soybean and peanut, on the basis of biochemical and molecular biological approaches. However, our understanding of the allergens from chickpea (Cicer arietinum L.), belonging to this family, is very limited. In this study, we aimed to identify putative and cross-reactive allergens from Chickpea (C. arietinum) by means of in silico analysis of the chickpea protein sequences and allergens sequences from Fabaceae family. We retrieved known allergen sequences in Fabaceae family from the IUIS Allergen Nomenclature Database. We performed a protein BLAST (BLASTp) on these sequences to retrieve the similar sequences from chickpea. We further analyzed the retrieved chickpea sequences using a combination of in silico tools, to assess them for their allergenicity potential. Following this, we built structure models using FUGUE: Sequence-structure homology; these models generated by the recognition tool were viewed in Swiss-PDB viewer. Through this in silico approach, we identified seven novel putative allergens from chickpea proteome sequences on the basis of similarity of sequence, structure and physicochemical properties with the known reported legume allergens. Four out of seven putative allergens may also show cross reactivity with reported allergens since potential allergens had common sequence and structural features with the reported allergens. The in silico proteomic identification of the allergen proteins in chickpea provides a basis for future research on developing hypoallergenic foods containing chickpea. Such bioinformatics approaches, combined with experimental methodology, will help delineate an efficient and comprehensive approach to assess allergenicity and pave the way for a better understanding of

Supplementary data: Eucalyptus microsatellites mined in silico ...

Indian Academy of Sciences (India)

Supplementary data: Eucalyptus microsatellites mined in silico: survey and evaluation. R. Yasodha, R. Sumathi, P. Chezhian, S. Kavitha and M. Ghosh. J. Genet. 87, XX-XX. Tm. CT. 2222. NA. 60 125. 192. Table 1. List of EST-SSR primers developed for E. globulus. No. of. Tm Product. Acc. no. SSR repeats. Forward primer.

Probabilistic risk analysis and its role in regulatory activity in a developing country

International Nuclear Information System (INIS)

Arredondo-Sanchez, C.

1985-01-01

The author discusses the criterion adopted for regulatory activity in a developing country with a nuclear power plant. He describes the problems that have to be overcome as a result of changes in the regulations during construction of the plant. There is discussion of the action taken by the regulatory body when introducing the method of probabilistic risk analysis. The part played by this form of analysis in quantifying the safety objectives proposed in the USA together with its limitations and the problems involved in this methodology are examined. Lastly, the author gives an opinion on the use that probabilistic risk analysis should be put to in developing countries such as Mexico. (author)

Meta-Analysis of Single-Case Design Research on Self-Regulatory Interventions for Academic Performance

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Perry, Valerie; Albeg, Loren; Tung, Catherine

2012-01-01

The current study examined the effects of self-regulatory interventions on reading, writing, and math by conducting a meta-analysis of single-case design research. Self-regulatory interventions have promise as an effective approach that is both minimally invasive and involves minimal resources. Effects of the interventions were analyzed by…

In-Silico Computing of the Most Deleterious nsSNPs in HBA1 Gene.

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Sayed AbdulAzeez

Full Text Available α-Thalassemia (α-thal is a genetic disorder caused by the substitution of single amino acid or large deletions in the HBA1 and/or HBA2 genes.Using modern bioinformatics tools as a systematic in-silico approach to predict the deleterious SNPs in the HBA1 gene and its significant pathogenic impact on the functions and structure of HBA1 protein was predicted.A total of 389 SNPs in HBA1 were retrieved from dbSNP database, which includes: 201 non-coding synonymous (nsSNPs, 43 human active SNPs, 16 intronic SNPs, 11 mRNA 3' UTR SNPs, 9 coding synonymous SNPs, 9 5' UTR SNPs and other types. Structural homology-based method (PolyPhen and sequence homology-based tool (SIFT, SNPs&Go, PROVEAN and PANTHER revealed that 2.4% of the nsSNPs are pathogenic.A total of 5 nsSNPs (G60V, K17M, K17T, L92F and W15R were predicted to be responsible for the structural and functional modifications of HBA1 protein. It is evident from the deep comprehensive in-silico analysis that, two nsSNPs such as G60V and W15R in HBA1 are highly deleterious. These "2 pathogenic nsSNPs" can be considered for wet-lab confirmatory analysis.

Fumaric acid production in Saccharomyces cerevisiae by in silico aided metabolic engineering.

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Guoqiang Xu

Full Text Available Fumaric acid (FA is a promising biomass-derived building-block chemical. Bio-based FA production from renewable feedstock is a promising and sustainable alternative to petroleum-based chemical synthesis. Here we report on FA production by direct fermentation using metabolically engineered Saccharomyces cerevisiae with the aid of in silico analysis of a genome-scale metabolic model. First, FUM1 was selected as the target gene on the basis of extensive literature mining. Flux balance analysis (FBA revealed that FUM1 deletion can lead to FA production and slightly lower growth of S. cerevisiae. The engineered S. cerevisiae strain obtained by deleting FUM1 can produce FA up to a concentration of 610±31 mg L(-1 without any apparent change in growth in fed-batch culture. FT-IR and (1H and (13C NMR spectra confirmed that FA was synthesized by the engineered S. cerevisiae strain. FBA identified pyruvate carboxylase as one of the factors limiting higher FA production. When the RoPYC gene was introduced, S. cerevisiae produced 1134±48 mg L(-1 FA. Furthermore, the final engineered S. cerevisiae strain was able to produce 1675±52 mg L(-1 FA in batch culture when the SFC1 gene encoding a succinate-fumarate transporter was introduced. These results demonstrate that the model shows great predictive capability for metabolic engineering. Moreover, FA production in S. cerevisiae can be efficiently developed with the aid of in silico metabolic engineering.

In silico identification, phylogeny and expression analysis of expansin superfamily in Medicago truncatula

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Ying Liu

2016-01-01

Full Text Available Expansins are important components of plant cell walls, which are involved in the process of cell wall loosening under low extracellular pH. By using a combinational method for homology search and protein domain analysis, a total of 42 expansin genes were identified from Medicago truncatula genome in this study. They were divided into four families, based on sequence alignment and phylogenetic analysis. Gene duplication events were identified in the expansins superfamily, especially in the extension of α-expansin family. By analysis of RNA-sequencing data from National Center for Biotechnology Information, the expansin (EXP genes expressed during tissues development were characterized. Meanwhile, lots of cis-acting regulatory DNA elements in the EXP superfamily were identified, which were mainly related to plant growth and development processes. The results presented in this study are expected to facilitate further research works on this gene superfamily and provide new insights about the molecular mechanisms of expansins in M. truncatula.

An integrated in silico approach to analyze the involvement of single amino acid polymorphisms in FANCD1/BRCA2-PALB2 and FANCD1/BRCA2-RAD51 complex.

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Doss, C George Priya; Nagasundaram, N

2014-11-01

Fanconi anemia (FA) is an autosomal recessive human disease characterized by genomic instability and a marked increase in cancer risk. The importance of FANCD1 gene is manifested by the fact that deleterious amino acid substitutions were found to confer susceptibility to hereditary breast and ovarian cancers. Attaining experimental knowledge about the possible disease-associated substitutions is laborious and time consuming. The recent introduction of genome variation analyzing in silico tools have the capability to identify the deleterious variants in an efficient manner. In this study, we conducted in silico variation analysis of deleterious non-synonymous SNPs at both functional and structural level in the breast cancer and FA susceptibility gene BRCA2/FANCD1. To identify and characterize deleterious mutations in this study, five in silico tools based on two different prediction methods namely pathogenicity prediction (SIFT, PolyPhen, and PANTHER), and protein stability prediction (I-Mutant 2.0 and MuStab) were analyzed. Based on the deleterious scores that overlap in these in silico approaches, and the availability of three-dimensional structures, structure analysis was carried out with the major mutations that occurred in the native protein coded by FANCD1/BRCA2 gene. In this work, we report the results of the first molecular dynamics (MD) simulation study performed to analyze the structural level changes in time scale level with respect to the native and mutated protein complexes (G25R, W31C, W31R in FANCD1/BRCA2-PALB2, and F1524V, V1532F in FANCD1/BRCA2-RAD51). Analysis of the MD trajectories indicated that predicted deleterious variants alter the structural behavior of BRCA2-PALB2 and BRCA2-RAD51 protein complexes. In addition, statistical analysis was employed to test the significance of these in silico tool predictions. Based on these predictions, we conclude that the identification of disease-related SNPs by in silico methods, in combination with MD

Carotid artery wall motion analysis from B-mode ultrasound using adaptive block matching: in silico evaluation and in vivo application

International Nuclear Information System (INIS)

Gastounioti, A; Stoitsis, J S; Nikita, K S; Golemati, S

2013-01-01

Valid risk stratification for carotid atherosclerotic plaques represents a crucial public health issue toward preventing fatal cerebrovascular events. Although motion analysis (MA) provides useful information about arterial wall dynamics, the identification of motion-based risk markers remains a significant challenge. Considering that the ability of a motion estimator (ME) to handle changes in the appearance of motion targets has a major effect on accuracy in MA, we investigated the potential of adaptive block matching (ABM) MEs, which consider changes in image intensities over time. To assure the validity in MA, we optimized and evaluated the ABM MEs in the context of a specially designed in silico framework. ABM FIRF2 , which takes advantage of the periodicity characterizing the arterial wall motion, was the most effective ABM algorithm, yielding a 47% accuracy increase with respect to the conventional block matching. The in vivo application of ABM FIRF2 revealed five potential risk markers: low movement amplitude of the normal part of the wall adjacent to the plaques in the radial (RMA PWL ) and longitudinal (LMA PWL ) directions, high radial motion amplitude of the plaque top surface (RMA PTS ), and high relative movement, expressed in terms of radial strain (RSI PL ) and longitudinal shear strain (LSSI PL ), between plaque top and bottom surfaces. The in vivo results were reproduced by OF LK(WLS) and ABM KF-K2 , MEs previously proposed by the authors and with remarkable in silico performances, thereby reinforcing the clinical values of the markers and the potential of those MEs. Future in vivo studies will elucidate with confidence the full potential of the markers. (paper)

In silico ADME in drug design – enhancing the impact

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Susanne Winiwarter

2018-03-01

Full Text Available Each year the pharmaceutical industry makes thousands of compounds, many of which do not meet the desired efficacy or pharmacokinetic properties, describing the absorption, distribution, metabolism and excretion (ADME behavior. Parameters such as lipophilicity, solubility and metabolic stability can be measured in high throughput in vitro assays. However, a compound needs to be synthesized in order to be tested. In silico models for these endpoints exist, although with varying quality. Such models can be used before synthesis and, together with a potency estimation, influence the decision to make a compound. In practice, it appears that often only one or two predicted properties are considered prior to synthesis, usually including a prediction of lipophilicity. While it is important to use all information when deciding which compound to make, it is somewhat challenging to combine multiple predictions unambiguously. This work investigates the possibility of combining in silico ADME predictions to define the minimum required potency for a specified human dose with sufficient confidence. Using a set of drug discovery compounds,in silico predictions were utilized to compare the relative ranking based on minimum potency calculation with the outcomes from the selection of lead compounds. The approach was also tested on a set of marketed drugs and the influence of the input parameters investigated.

Learning Gene Regulatory Networks Computationally from Gene Expression Data Using Weighted Consensus

KAUST Repository

Fujii, Chisato

2015-04-16

Gene regulatory networks analyze the relationships between genes allowing us to un- derstand the gene regulatory interactions in systems biology. Gene expression data from the microarray experiments is used to obtain the gene regulatory networks. How- ever, the microarray data is discrete, noisy and non-linear which makes learning the networks a challenging problem and existing gene network inference methods do not give consistent results. Current state-of-the-art study uses the average-ranking-based consensus method to combine and average the ranked predictions from individual methods. However each individual method has an equal contribution to the consen- sus prediction. We have developed a linear programming-based consensus approach which uses learned weights from linear programming among individual methods such that the methods have di↵erent weights depending on their performance. Our result reveals that assigning di↵erent weights to individual methods rather than giving them equal weights improves the performance of the consensus. The linear programming- based consensus method is evaluated and it had the best performance on in silico and Saccharomyces cerevisiae networks, and the second best on the Escherichia coli network outperformed by Inferelator Pipeline method which gives inconsistent results across a wide range of microarray data sets.

An in silico platform for the design of heterologous pathways in nonnative metabolite production

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Chatsurachai Sunisa

2012-05-01

Full Text Available Abstract Background Microorganisms are used as cell factories to produce valuable compounds in pharmaceuticals, biofuels, and other industrial processes. Incorporating heterologous metabolic pathways into well-characterized hosts is a major strategy for obtaining these target metabolites and improving productivity. However, selecting appropriate heterologous metabolic pathways for a host microorganism remains difficult owing to the complexity of metabolic networks. Hence, metabolic network design could benefit greatly from the availability of an in silico platform for heterologous pathway searching. Results We developed an algorithm for finding feasible heterologous pathways by which nonnative target metabolites are produced by host microorganisms, using Escherichia coli, Corynebacterium glutamicum, and Saccharomyces cerevisiae as templates. Using this algorithm, we screened heterologous pathways for the production of all possible nonnative target metabolites contained within databases. We then assessed the feasibility of the target productions using flux balance analysis, by which we could identify target metabolites associated with maximum cellular growth rate. Conclusions This in silico platform, designed for targeted searching of heterologous metabolic reactions, provides essential information for cell factory improvement.

Protecting innovation in bioinformatics and in-silico biology.

Science.gov (United States)

Harrison, Robert

2003-01-01

Commercial success or failure of innovation in bioinformatics and in-silico biology requires the appropriate use of legal tools for protecting and exploiting intellectual property. These tools include patents, copyrights, trademarks, design rights, and limiting information in the form of 'trade secrets'. Potentially patentable components of bioinformatics programmes include lines of code, algorithms, data content, data structure and user interfaces. In both the US and the European Union, copyright protection is granted for software as a literary work, and most other major industrial countries have adopted similar rules. Nonetheless, the grant of software patents remains controversial and is being challenged in some countries. Current debate extends to aspects such as whether patents can claim not only the apparatus and methods but also the data signals and/or products, such as a CD-ROM, on which the programme is stored. The patentability of substances discovered using in-silico methods is a separate debate that is unlikely to be resolved in the near future.

In silico SNP analysis of the breast cancer antigen NY-BR-1.

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Kosaloglu, Zeynep; Bitzer, Julia; Halama, Niels; Huang, Zhiqin; Zapatka, Marc; Schneeweiss, Andreas; Jäger, Dirk; Zörnig, Inka

2016-11-18

Breast cancer is one of the most common malignancies with increasing incidences every year and a leading cause of death among women. Although early stage breast cancer can be effectively treated, there are limited numbers of treatment options available for patients with advanced and metastatic disease. The novel breast cancer associated antigen NY-BR-1 was identified by SEREX analysis and is expressed in the majority (>70%) of breast tumors as well as metastases, in normal breast tissue, in testis and occasionally in prostate tissue. The biological function and regulation of NY-BR-1 is up to date unknown. We performed an in silico analysis on the genetic variations of the NY-BR-1 gene using data available in public SNP databases and the tools SIFT, Polyphen and Provean to find possible functional SNPs. Additionally, we considered the allele frequency of the found damaging SNPs and also analyzed data from an in-house sequencing project of 55 breast cancer samples for recurring SNPs, recorded in dbSNP. Over 2800 SNPs are recorded in the dbSNP and NHLBI ESP databases for the NY-BR-1 gene. Of these, 65 (2.07%) are synonymous SNPs, 191 (6.09%) are non-synoymous SNPs, and 2430 (77.48%) are noncoding intronic SNPs. As a result, 69 non-synoymous SNPs were predicted to be damaging by at least two, and 16 SNPs were predicted as damaging by all three of the used tools. The SNPs rs200639888, rs367841401 and rs377750885 were categorized as highly damaging by all three tools. Eight damaging SNPs are located in the ankyrin repeat domain (ANK), a domain known for its frequent involvement in protein-protein interactions. No distinctive features could be observed in the allele frequency of the analyzed SNPs. Considering these results we expect to gain more insights into the variations of the NY-BR-1 gene and their possible impact on giving rise to splice variants and therefore influence the function of NY-BR-1 in healthy tissue as well as in breast cancer.

In silico models for development of insect repellents

Science.gov (United States)

In silico modeling a common term to describe computer-assisted molecular modeling has been used to make remarkable advances in mechanistic drug design and in the discovery of new potential bioactive chemical entities in recent years. The goal of this chapter will be to focus on new, next-generation ...

Toward a Run-to-Run Adaptive Artificial Pancreas: In Silico Results.

Science.gov (United States)

Toffanin, Chiara; Visentin, Roberto; Messori, Mirko; Palma, Federico Di; Magni, Lalo; Cobelli, Claudio

2018-03-01

Contemporary and future outpatient long-term artificial pancreas (AP) studies need to cope with the well-known large intra- and interday glucose variability occurring in type 1 diabetic (T1D) subjects. Here, we propose an adaptive model predictive control (MPC) strategy to account for it and test it in silico. A run-to-run (R2R) approach adapts the subcutaneous basal insulin delivery during the night and the carbohydrate-to-insulin ratio (CR) during the day, based on some performance indices calculated from subcutaneous continuous glucose sensor data. In particular, R2R aims, first, to reduce the percentage of time in hypoglycemia and, secondarily, to improve the percentage of time in euglycemia and average glucose. In silico simulations are performed by using the University of Virginia/Padova T1D simulator enriched by incorporating three novel features: intra- and interday variability of insulin sensitivity, different distributions of CR at breakfast, lunch, and dinner, and dawn phenomenon. After about two months, using the R2R approach with a scenario characterized by a random 30% variation of the nominal insulin sensitivity the time in range and the time in tight range are increased by 11.39% and 44.87%, respectively, and the time spent above 180 mg/dl is reduced by 48.74%. An adaptive MPC algorithm based on R2R shows in silico great potential to capture intra- and interday glucose variability by improving both overnight and postprandial glucose control without increasing hypoglycemia. Making an AP adaptive is key for long-term real-life outpatient studies. These good in silico results are very encouraging and worth testing in vivo.

In Silico Systems Biology Analysis of Variants of Uncertain Significance in Lynch Syndrome Supports the Prioritization of Functional Molecular Validation.

Science.gov (United States)

Borras, Ester; Chang, Kyle; Pande, Mala; Cuddy, Amanda; Bosch, Jennifer L; Bannon, Sarah A; Mork, Maureen E; Rodriguez-Bigas, Miguel A; Taggart, Melissa W; Lynch, Patrick M; You, Y Nancy; Vilar, Eduardo

2017-10-01

Lynch syndrome (LS) is a genetic condition secondary to germline alterations in the DNA mismatch repair (MMR) genes with 30% of changes being variants of uncertain significance (VUS). Our aim was to perform an in silico reclassification of VUS from a large single institutional cohort that will help prioritizing functional validation. A total of 54 VUS were detected with 33 (61%) novel variants. We integrated family history, pathology, and genetic information along with supporting evidence from eight different in silico tools at the RNA and protein level. Our assessment allowed us to reclassify 54% (29/54) of the VUS as probably damaging, 13% (7/54) as possibly damaging, and 28% (15/54) as probably neutral. There are more than 1,000 VUS reported in MMR genes and our approach facilitates the prioritization of further functional efforts to assess the pathogenicity to those classified as probably damaging. Cancer Prev Res; 10(10); 580-7. ©2017 AACR . ©2017 American Association for Cancer Research.

An ensemble model of QSAR tools for regulatory risk assessment.

Science.gov (United States)

Pradeep, Prachi; Povinelli, Richard J; White, Shannon; Merrill, Stephen J

2016-01-01

Quantitative structure activity relationships (QSARs) are theoretical models that relate a quantitative measure of chemical structure to a physical property or a biological effect. QSAR predictions can be used for chemical risk assessment for protection of human and environmental health, which makes them interesting to regulators, especially in the absence of experimental data. For compatibility with regulatory use, QSAR models should be transparent, reproducible and optimized to minimize the number of false negatives. In silico QSAR tools are gaining wide acceptance as a faster alternative to otherwise time-consuming clinical and animal testing methods. However, different QSAR tools often make conflicting predictions for a given chemical and may also vary in their predictive performance across different chemical datasets. In a regulatory context, conflicting predictions raise interpretation, validation and adequacy concerns. To address these concerns, ensemble learning techniques in the machine learning paradigm can be used to integrate predictions from multiple tools. By leveraging various underlying QSAR algorithms and training datasets, the resulting consensus prediction should yield better overall predictive ability. We present a novel ensemble QSAR model using Bayesian classification. The model allows for varying a cut-off parameter that allows for a selection in the desirable trade-off between model sensitivity and specificity. The predictive performance of the ensemble model is compared with four in silico tools (Toxtree, Lazar, OECD Toolbox, and Danish QSAR) to predict carcinogenicity for a dataset of air toxins (332 chemicals) and a subset of the gold carcinogenic potency database (480 chemicals). Leave-one-out cross validation results show that the ensemble model achieves the best trade-off between sensitivity and specificity (accuracy: 83.8 % and 80.4 %, and balanced accuracy: 80.6 % and 80.8 %) and highest inter-rater agreement [kappa ( κ ): 0

The transcriptional regulatory network of Corynebacterium jeikeium K411 and its interaction with metabolic routes contributing to human body odor formation.

Science.gov (United States)

Barzantny, Helena; Schröder, Jasmin; Strotmeier, Jasmin; Fredrich, Eugenie; Brune, Iris; Tauch, Andreas

2012-06-15

Lipophilic corynebacteria are involved in the generation of volatile odorous products in the process of human body odor formation by degrading skin lipids and specific odor precursors. Therefore, these bacteria represent appropriate model systems for the cosmetic industry to examine axillary malodor formation on the molecular level. To understand the transcriptional control of metabolic pathways involved in this process, the transcriptional regulatory network of the lipophilic axilla isolate Corynebacterium jeikeium K411 was reconstructed from the complete genome sequence. This bioinformatic approach detected a gene-regulatory repertoire of 83 candidate proteins, including 56 DNA-binding transcriptional regulators, nine two-component systems, nine sigma factors, and nine regulators with diverse physiological functions. Furthermore, a cross-genome comparison among selected corynebacterial species of the taxonomic cluster 3 revealed a common gene-regulatory repertoire of 44 transcriptional regulators, including the MarR-like regulator Jk0257, which is exclusively encoded in the genomes of this taxonomical subline. The current network reconstruction comprises 48 transcriptional regulators and 674 gene-regulatory interactions that were assigned to five interconnected functional modules. Most genes involved in lipid degradation are under the combined control of the global cAMP-sensing transcriptional regulator GlxR and the LuxR-family regulator RamA, probably reflecting the essential role of lipid degradation in C. jeikeium. This study provides the first genome-scale in silico analysis of the transcriptional regulation of metabolism in a lipophilic bacterium involved in the formation of human body odor. Copyright © 2012 Elsevier B.V. All rights reserved.

In silico modelling of radiation effects towards personalised treatment in radiotherapy

Science.gov (United States)

Marcu, Loredana G.; Marcu, David

2017-12-01

In silico models applied in medical physics are valuable tools to assist in treatment optimization and personalization, which represent the ultimate goal of today's radiotherapy. Next to several biological and biophysical factors that influence tumour response to ionizing radiation, hypoxia and cancer stem cells are critical parameters that dictate the final outcome. The current work presents the results of an in silico model of tumour growth and response to radiation developed using Monte Carlo techniques. We are presenting the impact of partial oxygen tension and repopulation via cancer stem cells on tumour control after photon irradiation, highlighting some of the gaps that clinical research needs to fill for better customized treatment.

Bioprospecção dos potenciais farmacológicos do monoterpeno 7-hidroxicitronelal: Ensaios in silico

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Marcus Antônio Bezerra da Silva

2017-03-01

Full Text Available Os óleos essenciais de plantas, bem como os compostos derivados destes óleos como os terpenos, têm atraído cada vez mais interesse por causa das suas propriedades antioxidantes. O 7-hidroxicitronelal é um monoterpeno derivado do citronelal, apresentando fórmula molecular C10H20O2. Objetivou-se avaliar as atividades farmacológicas in silico do monoterpeno, entre elas a atividade antioxidante. Para isso, utilizou-se as técnicas in silico através do programa: PASS® online, para avaliação das propriedades farmacológicas teóricas da substância. Os resultados mostraram amplo espectro de atividades farmacológicas in silico, entre elas efeito antioxidante. Assim conclui-se que o monoterpeno é portador de atividade antioxidante teórica in silico. Contudo mais estudos in vitro e em organismos vivos devem ser realizados para corroborar essas atividades.

The identification of functional motifs in temporal gene expression analysis

Directory of Open Access Journals (Sweden)

Michael G. Surette

2005-01-01

Full Text Available The identification of transcription factor binding sites is essential to the understanding of the regulation of gene expression and the reconstruction of genetic regulatory networks. The in silico identification of cis-regulatory motifs is challenging due to sequence variability and lack of sufficient data to generate consensus motifs that are of quantitative or even qualitative predictive value. To determine functional motifs in gene expression, we propose a strategy to adopt false discovery rate (FDR and estimate motif effects to evaluate combinatorial analysis of motif candidates and temporal gene expression data. The method decreases the number of predicted motifs, which can then be confirmed by genetic analysis. To assess the method we used simulated motif/expression data to evaluate parameters. We applied this approach to experimental data for a group of iron responsive genes in Salmonella typhimurium 14028S. The method identified known and potentially new ferric-uptake regulator (Fur binding sites. In addition, we identified uncharacterized functional motif candidates that correlated with specific patterns of expression. A SAS code for the simulation and analysis gene expression data is available from the first author upon request.

Transcription regulatory networks analysis using CAGE

KAUST Repository

Tegnér, Jesper N.

2009-10-01

Mapping out cellular networks in general and transcriptional networks in particular has proved to be a bottle-neck hampering our understanding of biological processes. Integrative approaches fusing computational and experimental technologies for decoding transcriptional networks at a high level of resolution is therefore of uttermost importance. Yet, this is challenging since the control of gene expression in eukaryotes is a complex multi-level process influenced by several epigenetic factors and the fine interplay between regulatory proteins and the promoter structure governing the combinatorial regulation of gene expression. In this chapter we review how the CAGE data can be integrated with other measurements such as expression, physical interactions and computational prediction of regulatory motifs, which together can provide a genome-wide picture of eukaryotic transcriptional regulatory networks at a new level of resolution. © 2010 by Pan Stanford Publishing Pte. Ltd. All rights reserved.

In Silico Characterization of Hras Pathway for Therapeutic Implications Against Cancer

International Nuclear Information System (INIS)

Amjad, S.; Naz, A.; Malik, M. F. A.

2015-01-01

Hras (v-Ha-ras Harvey rat sarcoma viral oncogene homolog) plays a pivotal role in breast tumorigenesis. Expressional aberrations in Hras has significantly been correlated with patient's poor overall survival. In the present study, in silico characterization of Hras to trigger downstream effectors including raf, mek, erk has been explored. Three mutational hotspots for Hras (condons12, 13, 61) have been retrieved from the literature. Promoter modelling using Proscan software revealed a promoter region lacking TATA sequence. To study the epigenetic modifications, methylation analysis of promoter lacking TATA box was done using Methylator software. Methylation is directly correlated with tumor targeting therapies as it represses expression of certain oncogenes. Five candidate sites for hypermethylation of Hras were predicted. Analysis of protein residues involved in interlocking with its downstream effector proteins was also uncovered. In addition to this, a diagnostic and therapeutic relevance of micro RNAs (miRNAs/miRs) specifically acting either as oncogene or tumor suppressors on Hras mediated pathway have been identified. Seven micro RNAs (Let-7, miR-195, miR-497, miR-184, miR-34a, miR-34c, miR-155) found to be responsible for down regulating expression of proteins involved in ressignalling cascade while miR-372 and miR373, miR-212, miR206/21 and miR-17-92 cluster are known to elevate rassignalling pathway. Interestingly, dysregulated expression of Let-7, miR-195, miR-497, miR-184, miR-34, miR-155 co-related with poor prognosis in different cancers has also supported these in silico findings. (author)

Development of regulatory technology for thermal-hydraulic safety analysis

International Nuclear Information System (INIS)

Bang, Young Seok; Lee, S. H.; Ryu, Y. H.

2001-02-01

The present study aims to develop the regulation capability in thermal-hydraulic safety analysis which was required for the reasonable safety regulation in the current NPP, the next generation reactors, and the future-type reactors. The fourth fiscal year of the first phase of the research was focused on the following research topics: Investigation on the current status of the thermal-hydraulic safety analysis technology outside and inside of the country; Review on the improved features of the thermal-hydraulic safety analysis regulatory audit code, RELAP5/MOD3; Assessments of code with LOFT L9-3 ATWS experiment and LSTF SB-SG-10 multiple SGTR experiment; Application of the RELAP5/CANDU code to analyses of SLB and LBLOCA and evaluation of its effect on safety; Application of the code to IAEA PHWR ISP analysis; Assessments of RELAP5 and TRAC with UPTF downcomer injection test and Analysis of LBLOCA with RELAP5 for the performance evaluation of KNGR DVI; Setup of a coupled 3-D kinetics and thermal-hydraulics and application it to a reactivity accident analysis; and Extension of database and improvement of plant input decks. For supporting the resolution of safety issues, loss of RHR event during midloop operation was analyzed for Kori Unit 3, issues on high burnup fuel were reviewed and performance of FRAPCON-3 assessed. Also MSLB was analyzed to figure out the sensitivity of downcomer temperature supporting the PTS risk evaluation of Kori Unit 1. Thermal stratification in pipe was analyzed using the method proposed. And a method predicting the thermal-hydraulic performance of IRWST of KNGR was explored. The PWR ECCS performance criteria was issued as a MOST Article 200-19.and a regulatory guide on evaluation methodology was improved to cover concerns raised from the related licensing review process

In silico and in vitro prediction of gastrointestinal absorption from potential drug eremantholide C.

Science.gov (United States)

Caldeira, Tamires G; Saúde-Guimarães, Dênia A; Dezani, André B; Serra, Cristina Helena Dos Reis; de Souza, Jacqueline

2017-11-01

Analysis of the biopharmaceutical properties of eremantholide C, sesquiterpene lactone with proven pharmacological activity and low toxicity, is required to evaluate its potential to become a drug. Preliminary analysis of the physicochemical characteristics of eremantholide C was performed in silico. Equilibrium solubility was evaluated using the shake-flask method, at 37.0 °C, 100 rpm during 72 h in biorelevant media. The permeability was analysed using parallel artificial membrane permeability assay, at 37.0 °C, 50 rpm for 5 h. The donor compartment was composed of an eremantholide C solution in intestinal fluid simulated without enzymes, while the acceptor compartment consisted of phosphate buffer. Physicochemical characteristics predicted in silico indicated that eremantholide C has a low solubility and high permeability. In-vitro data of eremantholide C showed low solubility, with values for the dose/solubility ratio (ml): 9448.82, 10 389.61 e 15 000.00 for buffers acetate (pH 4.5), intestinal fluid simulated without enzymes (pH 6.8) and phosphate (pH 7.4), respectively. Also, it showed high permeability, with effective permeability of 30.4 × 10 -6 cm/s, a higher result compared with propranolol hydrochloride (9.23 × 10 -6 cm/s). The high permeability combined with its solubility, pharmacological activity and low toxicity demonstrate the importance of eremantholide C as a potential drug candidate. © 2017 Royal Pharmaceutical Society.

Clinical implications of in silico mathematical modeling for glioblastoma: a critical review.

Science.gov (United States)

Protopapa, Maria; Zygogianni, Anna; Stamatakos, Georgios S; Antypas, Christos; Armpilia, Christina; Uzunoglu, Nikolaos K; Kouloulias, Vassilis

2018-01-01

Glioblastoma remains a clinical challenge in spite of years of extensive research. Novel approaches are needed in order to integrate the existing knowledge. This is the potential role of mathematical oncology. This paper reviews mathematical models on glioblastoma from the clinical doctor's point of view, with focus on 3D modeling approaches of radiation response of in vivo glioblastomas based on contemporary imaging techniques. As these models aim to provide a clinically useful tool in the era of personalized medicine, the integration of the latest advances in molecular and imaging science and in clinical practice by the in silico models is crucial for their clinical relevance. Our aim is to indicate areas of GBM research that have not yet been addressed by in silico models and to point out evidence that has come up from in silico experiments, which may be worth considering in the clinic. This review examines how close these models have come in predicting the outcome of treatment protocols and in shaping the future of radiotherapy treatments.

In Silico Identification, Phylogenetic and Bioinformatic Analysis of Argonaute Genes in Plants

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Khaled Mirzaei

2014-01-01

Full Text Available Argonaute protein family is the key players in pathways of gene silencing and small regulatory RNAs in different organisms. Argonaute proteins can bind small noncoding RNAs and control protein synthesis, affect messenger RNA stability, and even participate in the production of new forms of small RNAs. The aim of this study was to characterize and perform bioinformatic analysis of Argonaute proteins in 32 plant species that their genome was sequenced. A total of 437 Argonaute genes were identified and were analyzed based on lengths, gene structure, and protein structure. Results showed that Argonaute proteins were highly conserved across plant kingdom. Phylogenic analysis divided plant Argonautes into three classes. Argonaute proteins have three conserved domains PAZ, MID and PIWI. In addition to three conserved domains namely, PAZ, MID, and PIWI, we identified few more domains in AGO of some plant species. Expression profile analysis of Argonaute proteins showed that expression of these genes varies in most of tissues, which means that these proteins are involved in regulation of most pathways of the plant system. Numbers of alternative transcripts of Argonaute genes were highly variable among the plants. A thorough analysis of large number of putative Argonaute genes revealed several interesting aspects associated with this protein and brought novel information with promising usefulness for both basic and biotechnological applications.

GABAA receptor binding molecules from traditional Chinese Medicine: An in silico approach

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Meng Lv

2014-12-01

Full Text Available The advents of how anesthesia works have helped in the discovery of anesthetic target protein. One such target protein named ϒ-aminobutyric acid (GABAA, which is the chief inhibitory neurotransmitter in the mammalian central nervous system. Asparagine at 289 position of GABAA protein within TM2 is important for its anesthetic function. This study explores Traditional Chinese Medicine (TCM against ASN 289 of GABAA for novel anesthetic compounds. The in silico approach showed gastrodin out of all compounds to be the best compound to start further analysis. It is a potential anesthetic compound suitable for the development of new drug.

GIS-assisted spatial analysis for urban regulatory detailed planning: designer's dimension in the Chinese code system

Science.gov (United States)

Yu, Yang; Zeng, Zheng

2009-10-01

By discussing the causes behind the high amendments ratio in the implementation of urban regulatory detailed plans in China despite its law-ensured status, the study aims to reconcile conflict between the legal authority of regulatory detailed planning and the insufficient scientific support in its decision-making and compilation by introducing into the process spatial analysis based on GIS technology and 3D modeling thus present a more scientific and flexible approach to regulatory detailed planning in China. The study first points out that the current compilation process of urban regulatory detailed plan in China employs mainly an empirical approach which renders it constantly subjected to amendments; the study then discusses the need and current utilization of GIS in the Chinese system and proposes the framework of a GIS-assisted 3D spatial analysis process from the designer's perspective which can be regarded as an alternating processes between the descriptive codes and physical design in the compilation of regulatory detailed planning. With a case study of the processes and results from the application of the framework, the paper concludes that the proposed framework can be an effective instrument which provides more rationality, flexibility and thus more efficiency to the compilation and decision-making process of urban regulatory detailed plan in China.

PK/DB: database for pharmacokinetic properties and predictive in silico ADME models.

Science.gov (United States)

Moda, Tiago L; Torres, Leonardo G; Carrara, Alexandre E; Andricopulo, Adriano D

2008-10-01

The study of pharmacokinetic properties (PK) is of great importance in drug discovery and development. In the present work, PK/DB (a new freely available database for PK) was designed with the aim of creating robust databases for pharmacokinetic studies and in silico absorption, distribution, metabolism and excretion (ADME) prediction. Comprehensive, web-based and easy to access, PK/DB manages 1203 compounds which represent 2973 pharmacokinetic measurements, including five models for in silico ADME prediction (human intestinal absorption, human oral bioavailability, plasma protein binding, blood-brain barrier and water solubility). http://www.pkdb.ifsc.usp.br

An overview of the UK regulatory expectation for design basis accident analysis

International Nuclear Information System (INIS)

Trimble, Andy

2013-01-01

The UK Health and Safety Executive published its most recent regulatory expectations in the 2006 version of it's safety assessment principles (SAPs). This built on experience regulating the full range of facilities for which it is responsible. Thus the principles underpinning all regulatory safety case assessment are the same but the implementation differs depending on the application. This paper will describe the published design basis accident analysis (DBAA) logic in context with other technical aspects of the regulatory expectation for safety cases. It will further illustrate the DBAA methodology with practical examples from actual experience on reprocessing plant gained over the last 15 years or so. Among the examples will be the relevance of conventional safety fault initiators to nuclear safety assessment. It will further demonstrate the derivation of facility limits and conditions necessary for nuclear safety. (authors)

In-silico approach to the development of a prototype clinical ...

African Journals Online (AJOL)

International Journal of Natural and Applied Sciences ... In-silico approaches to information management of pediatrics sections of hospitals could ... This study was aimed at developing a prototype clinic information system for keeping track of ...

Prediction of pharmacokinetic and toxicological parameters of a 4-phenylcoumarin isolated from geopropolis: In silico and in vitro approaches.

Science.gov (United States)

da Cunha, Marcos Guilherme; Franco, Gilson César Nobre; Franchin, Marcelo; Beutler, John A; de Alencar, Severino Matias; Ikegaki, Masaharu; Rosalen, Pedro Luiz

2016-11-30

In silico and in vitro methodologies have been used as important tools in the drug discovery process, including from natural sources. The aim of this study was to predict pharmacokinetic and toxicity (ADME/Tox) properties of a coumarin isolated from geopropolis using in silico and in vitro approaches. Cinnamoyloxy-mammeisin (CNM) isolated from Brazilian M. scutellaris geopropolis was evaluated for its pharmacokinetic parameters by in silico models (ACD/Percepta™ and MetaDrug™ software). Genotoxicity was assessed by in vitro DNA damage signaling PCR array. CNM did not pass all parameters of Lipinski's rule of five, with a predicted low oral bioavailability and high plasma protein binding, but with good predicted blood brain barrier penetration. CNM was predicted to show low affinity to cytochrome P450 family members. Furthermore, the predicted Ames test indicated potential mutagenicity of CNM. Also, the probability of toxicity for organs and tissues was classified as moderate and high for liver and kidney, and moderate and low for skin and eye irritation, respectively. The PCR array analysis showed that CNM significantly upregulated about 7% of all DNA damage-related genes. By exploring the biological function of these genes, it was found that the predicted CNM genotoxicity is likely to be mediated by apoptosis. The predicted ADME/Tox profile suggests that external use of CNM may be preferable to systemic exposure, while its genotoxicity was characterized by the upregulation of apoptosis-related genes after treatment. The combined use of in silico and in vitro approaches to evaluate these parameters generated useful hypotheses to guide further preclinical studies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

In silico Mechano-Chemical Model of Bone Healing for the Regeneration of Critical Defects: The Effect of BMP-2.

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Frederico O Ribeiro

Full Text Available The healing of bone defects is a challenge for both tissue engineering and modern orthopaedics. This problem has been addressed through the study of scaffold constructs combined with mechanoregulatory theories, disregarding the influence of chemical factors and their respective delivery devices. Of the chemical factors involved in the bone healing process, bone morphogenetic protein-2 (BMP-2 has been identified as one of the most powerful osteoinductive proteins. The aim of this work is to develop and validate a mechano-chemical regulatory model to study the effect of BMP-2 on the healing of large bone defects in silico. We first collected a range of quantitative experimental data from the literature concerning the effects of BMP-2 on cellular activity, specifically proliferation, migration, differentiation, maturation and extracellular matrix production. These data were then used to define a model governed by mechano-chemical stimuli to simulate the healing of large bone defects under the following conditions: natural healing, an empty hydrogel implanted in the defect and a hydrogel soaked with BMP-2 implanted in the defect. For the latter condition, successful defect healing was predicted, in agreement with previous in vivo experiments. Further in vivo comparisons showed the potential of the model, which accurately predicted bone tissue formation during healing, bone tissue distribution across the defect and the quantity of bone inside the defect. The proposed mechano-chemical model also estimated the effect of BMP-2 on cells and the evolution of healing in large bone defects. This novel in silico tool provides valuable insight for bone tissue regeneration strategies.

In silico prediction of potential chemical reactions mediated by human enzymes.

Science.gov (United States)

Yu, Myeong-Sang; Lee, Hyang-Mi; Park, Aaron; Park, Chungoo; Ceong, Hyithaek; Rhee, Ki-Hyeong; Na, Dokyun

2018-06-13

Administered drugs are often converted into an ineffective or activated form by enzymes in our body. Conventional in silico prediction approaches focused on therapeutically important enzymes such as CYP450. However, there are more than thousands of different cellular enzymes that potentially convert administered drug into other forms. We developed an in silico model to predict which of human enzymes including metabolic enzymes as well as CYP450 family can catalyze a given chemical compound. The prediction is based on the chemical and physical similarity between known enzyme substrates and a query chemical compound. Our in silico model was developed using multiple linear regression and the model showed high performance (AUC = 0.896) despite of the large number of enzymes. When evaluated on a test dataset, it also showed significantly high performance (AUC = 0.746). Interestingly, evaluation with literature data showed that our model can be used to predict not only enzymatic reactions but also drug conversion and enzyme inhibition. Our model was able to predict enzymatic reactions of a query molecule with a high accuracy. This may foster to discover new metabolic routes and to accelerate the computational development of drug candidates by enabling the prediction of the potential conversion of administered drugs into active or inactive forms.

Solvates of silico-12-molybdic acid with alcohols

International Nuclear Information System (INIS)

Punchuk, I.N.; Chuvaev, V.F.

1984-01-01

With the aim of investigating interaction processes of solid heteropolyacids and organic compounds, solvates are prepared. Solvates are products of adding gaseous methanol, ethanol and isopropanol to silico-12-molybdic acid. The compounds are studied by IR and PMR spectroscopy methods. Possible models for solvate structure are considered, as well as their connection with solvate properties and thermal decomposition

In silico characterization and evolution studies of alcohol ...

African Journals Online (AJOL)

The aim of our study was to isolate the alcohol dehydrogenase (ADH) mRNA from Phoenix dactifera, and examine the molecular evolutionary history of this nuclear gene with others ADH genes from palms and other plants species. The DnADH gene has been isolated in silico by BLAST2GO from a cDNA library of date palm ...

An integrated in silico/in vitro approach to assess the xenoestrogenic potential of Alternaria mycotoxins and metabolites.

Science.gov (United States)

Dellafiora, Luca; Warth, Benedikt; Schmidt, Verena; Del Favero, Giorgia; Mikula, Hannes; Fröhlich, Johannes; Marko, Doris

2018-05-15

Xenoestrogenic mycotoxins may contaminate food and feed posing a public health issue. Besides the zearalenone group, the Alternaria toxin alternariol (AOH) has been described as a potential mycoestrogen. However, the estrogenicity of Alternaria toxins is still largely overlooked and further data are needed to better describe the group toxicity. In the frame of risk assessment, mixed in silico/in vitro approaches already proved to be effective first-line analytical tools. An integrated in silico/in vitro approach was used to investigate the effects of metabolic and chemical modifications on the estrogenicity of AOH. Among the considered modifications, methylation was found critical for enhancing estrogenicity (as seen for alternariol monomethyl ether (AME)) while hydroxylation and glucuronidation had the opposite effect (as seen for 4-hydroxy AOH and 4-hydroxy AME). The structure-activity relationship analysis provided the structural rationale. Our results provide insights to design more efficient risk assessment studies expanding knowledge over the group toxicity. Copyright © 2017 Elsevier Ltd. All rights reserved.

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

Energy Technology Data Exchange (ETDEWEB)

Pandi, Narayanan Sathiya, E-mail: sathiyapandi@gmail.com; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-10-04

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC.

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

International Nuclear Information System (INIS)

Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-01-01

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC

AMMOS: A Software Platform to Assist in silico Screening

Directory of Open Access Journals (Sweden)

Lagorce D.

2009-12-01

Full Text Available Three software packages based on the common platform of AMMOS (Automated Molecular Mechanics Optimization tool for in silico Screening for assisting virtual ligand screening purposes have been recently developed. DG-AMMOS allows generation of 3D conformations of small molecules using distance geometry and molecular mechanics optimization. AMMOS_SmallMol is a package for structural refinement of compound collections that can be used prior to docking experiments. AMMOS_ProtLig is a package for energy minimization of protein-ligand complexes. It performs an automatic procedure for molecular mechanics minimization at different levels of flexibility - from rigid to fully flexible structures of both the ligand and the receptor. The packages have been tested on small molecules with a high structural diversity and proteins binding sites of completely different geometries and physicochemical properties. The platform is developed as an open source software and can be used in a broad range of in silico drug design studies.

Sheep skeletal muscle transcriptome analysis reveals muscle growth regulatory lncRNAs.

Science.gov (United States)

Chao, Tianle; Ji, Zhibin; Hou, Lei; Wang, Jin; Zhang, Chunlan; Wang, Guizhi; Wang, Jianmin

2018-01-01

As widely distributed domestic animals, sheep are an important species and the source of mutton. In this study, we aimed to evaluate the regulatory lncRNAs associated with muscle growth and development between high production mutton sheep (Dorper sheep and Qianhua Mutton Merino sheep) and low production mutton sheep (Small-tailed Han sheep). In total, 39 lncRNAs were found to be differentially expressed. Using co-expression analysis and functional annotation, 1,206 co-expression interactions were found between 32 lncRNAs and 369 genes, and 29 of these lncRNAs were found to be associated with muscle development, metabolism, cell proliferation and apoptosis. lncRNA-mRNA interactions revealed 6 lncRNAs as hub lncRNAs. Moreover, three lncRNAs and their associated co-expressed genes were demonstrated by cis-regulatory gene analyses, and we also found a potential regulatory relationship between the pseudogene lncRNA LOC101121401 and its parent gene FTH1. This study provides a genome-wide resolution of lncRNA and mRNA regulation in muscles from mutton sheep.

In-silico design of novel myocilin inhibitors for glaucoma therapy

African Journals Online (AJOL)

AutoDock based molecular docking simulation. Results: Out of ten ... Conclusion: In-silico virtual screening of molecular libraries containing a large number of ligands is very useful for .... sized cluster, number of hydrogen bonds with active site ...

Silico-tuberculosis and associated risk factors in central province of ...

African Journals Online (AJOL)

tuberculosis. This article review the frequency of silicosis and tuberculosis in workers who exposed to silica and evaluate influencing factors that may increase the risk of silico-tuberculosis. Methods: an analytical cross-sectional study was performed in ...

78 FR 39284 - Technical Guidance for Assessing Environmental Justice in Regulatory Analysis

Science.gov (United States)

2013-07-01

... ENVIRONMENTAL PROTECTION AGENCY [EPA-HQ-OA-2013-0320; FRL-9830-1] Technical Guidance for Assessing Environmental Justice in Regulatory Analysis AGENCY: Environmental Protection Agency (EPA). ACTION: Notice... Environmental Protection Agency (EPA) issued for public comment a document entitled, ``Technical Guidance for...

In silico analysis of compounds characterized from ethanolic extract of Cucurbita pepo with NF-κB-inhibitory potential

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Solomon O. Rotimi

2014-12-01

Full Text Available NF-κB controls cellular growth properties of cells and its regulation is key to the management of disease like cancer. Although plant-derived bioactives have been reported to inhibit NF-κB, there is limited knowledge on the interactions between the phytochemicals and NF-κB. In this study, we identified the phytochemicals in ethanolic extract of Cucurbita pepo using Gas Chromatography-Mass Spectroscopy technique and used in silico approach to understand the interaction between the identified phytochemicals and NF-κB using Molegro Virtual Docker. The docking algorithm showed that nine phytochemicals fit well into the pocket on NF-κB. Our analysis showed that Lys144 is a prominent residue by involving in the binding of 9-octadecenoic acid (Z-, methyl ester, hexadecanoic acid, methyl ester and octadecanoic acid, methyl ester with the moldock score of -55.5264, -57.4634 and -61.1258 respectively. Hence, the binding of these phytochemicals to NF-κB could be responsible for the anti-inflammatory and anti-cancer property of C. pepo.

In Silico screening for functional candidates amongst hypothetical proteins

DEFF Research Database (Denmark)

Desler, Claus; Suravajhala, Prashanth; Sanderhoff, May

2009-01-01

eukaryotes. With the general belief that the majority of hypothetical proteins are the product of pseudogenes, it is essential to have a tool with the ability of pinpointing the minority of hypothetical proteins with a high probability of being expressed. RESULTS: Here, we present an in silico selection...

In silico analysis of single nucleotide polymorphism (SNPs in human β-globin gene.

Directory of Open Access Journals (Sweden)

Mohammed Alanazi

Full Text Available Single amino acid substitutions in the globin chain are the most common forms of genetic variations that produce hemoglobinopathies--the most widespread inherited disorders worldwide. Several hemoglobinopathies result from homozygosity or compound heterozygosity to beta-globin (HBB gene mutations, such as that producing sickle cell hemoglobin (HbS, HbC, HbD and HbE. Several of these mutations are deleterious and result in moderate to severe hemolytic anemia, with associated complications, requiring lifelong care and management. Even though many hemoglobinopathies result from single amino acid changes producing similar structural abnormalities, there are functional differences in the generated variants. Using in silico methods, we examined the genetic variations that can alter the expression and function of the HBB gene. Using a sequence homology-based Sorting Intolerant from Tolerant (SIFT server we have searched for the SNPs, which showed that 200 (80% non-synonymous polymorphism were found to be deleterious. The structure-based method via PolyPhen server indicated that 135 (40% non-synonymous polymorphism may modify protein function and structure. The Pupa Suite software showed that the SNPs will have a phenotypic consequence on the structure and function of the altered protein. Structure analysis was performed on the key mutations that occur in the native protein coded by the HBB gene that causes hemoglobinopathies such as: HbC (E→K, HbD (E→Q, HbE (E→K and HbS (E→V. Atomic Non-Local Environment Assessment (ANOLEA, Yet Another Scientific Artificial Reality Application (YASARA, CHARMM-GUI webserver for macromolecular dynamics and mechanics, and Normal Mode Analysis, Deformation and Refinement (NOMAD-Ref of Gromacs server were used to perform molecular dynamics simulations and energy minimization calculations on β-Chain residue of the HBB gene before and after mutation. Furthermore, in the native and altered protein models, amino acid

Atividades farmacológicas do monoterpeno 1,8-cineol: um estudo in silico

Directory of Open Access Journals (Sweden)

Ingrid Carneiro Cavalcante Souto

2016-10-01

Full Text Available Os óleos essenciais são os principais compostos de uso terapêutico derivados de plantas, amplamente utilizados na produção de perfumes e cosméticos, apresentando também efeito farmacológico. Dentre os vários componentes dos óleos essenciais estão os terpenos; estes resultam do metabolismo secundário das plantas. O 1,8-cineol ou eucaliptol, é um monoterpeno de grande índice terapêutico segundo a literatura. O presente estudo objetiva realizar uma análise in silico do 1,8- cineol para atividade anti-hipertensiva, antiasmática e analgésica. Com a análise in silico do monoterpeno pode-se observar que este composto apresenta maiores valores de Probabilidade de ser ativos ara as atividades estudadas, em relação aos valores de Probabilidade de ser inativo. Portanto, conclui-se que o 1,8-cineol é um potente candidato a fármaco com várias atividades terapêuticas, de acordo com os estudos in silico.

In Silico Synthesis of Synthetic Receptors: A Polymerization Algorithm.

Science.gov (United States)

Cowen, Todd; Busato, Mirko; Karim, Kal; Piletsky, Sergey A

2016-12-01

Molecularly imprinted polymer (MIP) synthetic receptors have proposed and applied applications in chemical extraction, sensors, assays, catalysis, targeted drug delivery, and direct inhibition of harmful chemicals and pathogens. However, they rely heavily on effective design for success. An algorithm has been written which mimics radical polymerization atomistically, accounting for chemical and spatial discrimination, hybridization, and geometric optimization. Synthetic ephedrine receptors were synthesized in silico to demonstrate the accuracy of the algorithm in reproducing polymers structures at the atomic level. Comparative analysis in the design of a synthetic ephedrine receptor demonstrates that the new method can effectively identify affinity trends and binding site selectivities where commonly used alternative methods cannot. This new method is believed to generate the most realistic models of MIPs thus produced. This suggests that the algorithm could be a powerful new tool in the design and analysis of various polymers, including MIPs, with significant implications in areas of biotechnology, biomimetics, and the materials sciences more generally. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recovering uranium and/or aluminium from refractory silico-aluminous material

International Nuclear Information System (INIS)

Livesey-Goldblatt, E.; Nagy, I.F.; Tunley, T.H.

1983-01-01

A process for recovering uranium and/or aluminium from a refractory silico-aluminous material comprises leaching the material in one or more stages, obtaining a pregnant solution which contains little or no acid and recovering the desired metal from the solution

Essential pathway identification: from in silico analysis to potential antifungal targets in Aspergillus fumigatus

DEFF Research Database (Denmark)

Thykær, Jette; Andersen, Mikael Rørdam; Baker, S. E.

2009-01-01

with the reactions, we identified orthologous candidate essential genes in Aspergillus fumigatus. Our predictions are validated in part by the modes of action for some antifungal drugs and by molecular genetic studies of essential genes in A. fumigatus and other fungi. The use of metabolic models to predict...... of 1190 biochemically unique reactions that are associated with 871 open reading frames. Through a systematic in silico deletion of single metabolic reactions using this model, several essential metabolic pathways were identified for A. niger. A total of 138 reactions were identified as being essential...... biochemical reactions during growth on a minimal glucose medium. The majority of the reactions grouped into essential biochemical pathways covering cell wall biosynthesis, amino acid biosynthesis, energy metabolism and purine and pyrimidine metabolism. Based on the A. niger open reading frames associated...

Strengthening Regulatory Competence in a Changing Nuclear Regulatory Environment

International Nuclear Information System (INIS)

Illizastigui, P.F.

2016-01-01

The paper addresses the approach followed by the Cuban National Center for Nuclear Safety for the management of current and new competences of its regulatory staff with the aim of allowing those staff to effectively fulfill their core regulatory functions. The approach is realized through an Integrated System for Competence Building, which is based on the IAEA recommendations, shown to be effective in ensuring the necessary competence in the relevant areas. In the author’s opinion, competence of the regulatory staff in the area of human and organizational factors is of paramount importance and needs to be further strengthened in order to be able to assess safety performance at the facilities and detect early signs of deteriorating safety performance. The former is defined by the author as the core regulatory function “Analysis” which covers the entire spectrum of assessment tasks carried out by the regulatory staff to: a) detect declining safety performance, b) diagnose latent weaknesses (root causes) and c) make effective safety culture interventions. The author suggests that competence associated with the fulfillment of the analysis function is distinctly identified and dealt with separately in the current system of managing regulatory competence. (author)

Regulatory activities; Actividades regulatorias

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-07-01

This publication, compiled in 8 chapters, presents the regulatory system developed by the Nuclear Regulatory Authority (NRA) of the Argentine Republic. The following activities and developed topics in this document describe: the evolution of the nuclear regulatory activity in Argentina; the Argentine regulatory system; the nuclear regulatory laws and standards; the inspection and safeguards of nuclear facilities; the emergency systems; the environmental systems; the environmental monitoring; the analysis laboratories on physical and biological dosimetry, prenatal irradiation, internal irradiation, radiation measurements, detection techniques on nuclear testing, medical program on radiation protection; the institutional relations with national and international organization; the training courses and meeting; the technical information.

Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

Energy Technology Data Exchange (ETDEWEB)

Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov [Science and Research Staff, Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993–0002 (United States); Cross, Kevin P. [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)

2012-05-01

Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive

Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

International Nuclear Information System (INIS)

Valerio, Luis G.; Cross, Kevin P.

2012-01-01

Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive performance.

Cadmium effects on sperm morphology and semenogelin with relates to increased ROS in infertile smokers: An in vitro and in silico approach.

Science.gov (United States)

Ranganathan, Parameswari; Rao, Kamini A; Sudan, Jesu Jaya; Balasundaram, Sridharan

2018-06-01

Smoking releases cadmium (Cd), the metal toxicant which causes an imbalance in reactive oxygen species level in seminal plasma. This imbalance is envisaged to impair the sperm DNA morphology and thereby result in male infertility. In order to correlate this association, we performed in vitro and in silico studies and evaluated the influence of reactive oxygen species imbalance on sperm morphology impairments due to smoking. The study included 76 infertile smokers, 72 infertile non-smokers, 68 fertile smokers and 74 fertile non-smokers (control). Semen samples were collected at regular intervals from all the subjects. Semen parameters were examined by computer assisted semen analysis, quantification of metal toxicant by atomic absorption spectrophotometer, assessment of antioxidants through enzymatic and non-enzymatic methods, diagnosis of reactive oxygen species by nitro blue tetrazolium method and Cd influence on sperm protein by in vitro and in silico methods. Our analysis revealed that the levels of cigarette toxicants in semen were high, accompanied by low levels of antioxidants in seminal plasma of infertile smoker subjects. In addition the investigation of Cd treated sperm cells through scanning electronic microscope showed the mid piece damage of spermatozoa. The dispersive X-ray analysis to identify the elemental composition further confirmed the presence of Cd. Finally, the in-silico analysis on semenogelin sequences revealed the D-H-D motif which represents a favourable binding site for Cd coordination. Our findings clearly indicated the influence of Cd on reactive oxygen species leading to impaired sperm morphology leading to male infertility. Copyright © 2018 Society for Biology of Reproduction & the Institute of Animal Reproduction and Food Research of Polish Academy of Sciences in Olsztyn. Published by Elsevier B.V. All rights reserved.

Genome semantics, in silico multicellular systems and the Central Dogma.

Science.gov (United States)

Werner, Eric

2005-03-21

Genomes with their complexity and size present what appears to be an impossible challenge. Scientists speak in terms of decades or even centuries before we will understand how genomes and their hosts the cell and the city of cells that make up the multicellular context function. We believe that there will be surprisingly quick progress made in our understanding of genomes. The key is to stop taking the Central Dogma as the only direction in which genome research can scale the semantics of genomes. Instead a top-down approach coupled with a bottom-up approach may snare the unwieldy beast and make sense of genomes. The method we propose is to take in silico biology seriously. By developing in silico models of genomes cells and multicellular systems, we position ourselves to develop a theory of meaning for artificial genomes. Then using that develop a natural semantics of genomes.

In Silico Analysis of the Structural and Biochemical Features of the NMD Factor UPF1 in Ustilago maydis.

Directory of Open Access Journals (Sweden)

Nancy Martínez-Montiel

Full Text Available The molecular mechanisms regulating the accuracy of gene expression are still not fully understood. Among these mechanisms, Nonsense-mediated Decay (NMD is a quality control process that detects post-transcriptionally abnormal transcripts and leads them to degradation. The UPF1 protein lays at the heart of NMD as shown by several structural and functional features reported for this factor mainly for Homo sapiens and Saccharomyces cerevisiae. This process is highly conserved in eukaryotes but functional diversity can be observed in various species. Ustilago maydis is a basidiomycete and the best-known smut, which has become a model to study molecular and cellular eukaryotic mechanisms. In this study, we performed in silico analysis to investigate the structural and biochemical properties of the putative UPF1 homolog in Ustilago maydis. The putative homolog for UPF1 was recognized in the annotated genome for the basidiomycete, exhibiting 66% identity with its human counterpart at the protein level. The known structural and functional domains characteristic of UPF1 homologs were also found. Based on the crystal structures available for UPF1, we constructed different three-dimensional models for umUPF1 in order to analyze the secondary and tertiary structural features of this factor. Using these models, we studied the spatial arrangement of umUPF1 and its capability to interact with UPF2. Moreover, we identified the critical amino acids that mediate the interaction of umUPF1 with UPF2, ATP, RNA and with UPF1 itself. Mutating these amino acids in silico showed an important effect over the native structure. Finally, we performed molecular dynamic simulations for UPF1 proteins from H. sapiens and U. maydis and the results obtained show a similar behavior and physicochemical properties for the protein in both organisms. Overall, our results indicate that the putative UPF1 identified in U. maydis shows a very similar sequence, structural organization

In Silico Analysis of the Structural and Biochemical Features of the NMD Factor UPF1 in Ustilago maydis.

Science.gov (United States)

Martínez-Montiel, Nancy; Morales-Lara, Laura; Hernández-Pérez, Julio M; Martínez-Contreras, Rebeca D

2016-01-01

The molecular mechanisms regulating the accuracy of gene expression are still not fully understood. Among these mechanisms, Nonsense-mediated Decay (NMD) is a quality control process that detects post-transcriptionally abnormal transcripts and leads them to degradation. The UPF1 protein lays at the heart of NMD as shown by several structural and functional features reported for this factor mainly for Homo sapiens and Saccharomyces cerevisiae. This process is highly conserved in eukaryotes but functional diversity can be observed in various species. Ustilago maydis is a basidiomycete and the best-known smut, which has become a model to study molecular and cellular eukaryotic mechanisms. In this study, we performed in silico analysis to investigate the structural and biochemical properties of the putative UPF1 homolog in Ustilago maydis. The putative homolog for UPF1 was recognized in the annotated genome for the basidiomycete, exhibiting 66% identity with its human counterpart at the protein level. The known structural and functional domains characteristic of UPF1 homologs were also found. Based on the crystal structures available for UPF1, we constructed different three-dimensional models for umUPF1 in order to analyze the secondary and tertiary structural features of this factor. Using these models, we studied the spatial arrangement of umUPF1 and its capability to interact with UPF2. Moreover, we identified the critical amino acids that mediate the interaction of umUPF1 with UPF2, ATP, RNA and with UPF1 itself. Mutating these amino acids in silico showed an important effect over the native structure. Finally, we performed molecular dynamic simulations for UPF1 proteins from H. sapiens and U. maydis and the results obtained show a similar behavior and physicochemical properties for the protein in both organisms. Overall, our results indicate that the putative UPF1 identified in U. maydis shows a very similar sequence, structural organization, mechanical stability

Characterization of the bovine pregnancy-associated glycoprotein gene family – analysis of gene sequences, regulatory regions within the promoter and expression of selected genes

Directory of Open Access Journals (Sweden)

Walker Angela M

2009-04-01

Full Text Available Abstract Background The Pregnancy-associated glycoproteins (PAGs belong to a large family of aspartic peptidases expressed exclusively in the placenta of species in the Artiodactyla order. In cattle, the PAG gene family is comprised of at least 22 transcribed genes, as well as some variants. Phylogenetic analyses have shown that the PAG family segregates into 'ancient' and 'modern' groupings. Along with sequence differences between family members, there are clear distinctions in their spatio-temporal distribution and in their relative level of expression. In this report, 1 we performed an in silico analysis of the bovine genome to further characterize the PAG gene family, 2 we scrutinized proximal promoter sequences of the PAG genes to evaluate the evolution pressures operating on them and to identify putative regulatory regions, 3 we determined relative transcript abundance of selected PAGs during pregnancy and, 4 we performed preliminary characterization of the putative regulatory elements for one of the candidate PAGs, bovine (bo PAG-2. Results From our analysis of the bovine genome, we identified 18 distinct PAG genes and 14 pseudogenes. We observed that the first 500 base pairs upstream of the translational start site contained multiple regions that are conserved among all boPAGs. However, a preponderance of conserved regions, that harbor recognition sites for putative transcriptional factors (TFs, were found to be unique to the modern boPAG grouping, but not the ancient boPAGs. We gathered evidence by means of Q-PCR and screening of EST databases to show that boPAG-2 is the most abundant of all boPAG transcripts. Finally, we provided preliminary evidence for the role of ETS- and DDVL-related TFs in the regulation of the boPAG-2 gene. Conclusion PAGs represent a relatively large gene family in the bovine genome. The proximal promoter regions of these genes display differences in putative TF binding sites, likely contributing to observed

Introduction to the Unified Agenda of Federal Regulatory and Deregulatory Actions

Science.gov (United States)

2010-04-26

... Regulatory Commission Federal Housing Finance Agency Federal Maritime Commission Federal Mediation and... that the Regulatory Flexibility Act may require a Regulatory Flexibility Analysis, actions selected for.... Regulatory Flexibility Analysis Required -- whether an analysis is required by the Regulatory Flexibility Act...

Hydroxyurea-Lactose Interaction Study: In Silico and In Vitro Evaluation.

Science.gov (United States)

Bachchhao, Kunal B; Patil, R R; Patil, C R; Patil, Dipak D

2017-11-01

The Maillard reaction between hydroxyurea (a primary amine-containing drug) and lactose (used as an excipient) was explored. The adduct of these compounds was synthesized by heating hydroxyurea with lactose monohydrate at 60 °C in borate buffer (pH 9.2) for 12 h. Synthesis of the adduct was confirmed using UV-visible spectroscopy and Fourier transform infrared, differential scanning calorimetry, high-pressure liquid chromatography, and liquid chromatography-mass spectrometry studies. An in silico investigation of how the adduct formation affected the interactions of hydroxyurea with its biological target oxyhemoglobin, to which it binds to generate nitric oxide and regulates fetal hemoglobin synthesis, was carried out. The in silico evaluations were complemented by an in vitro assay of the anti-sickling activity. Co-incubation of hydroxyurea with deoxygenated blood samples reduced the percentage of sickled cells from 38% to 12 ± 1.6%, whereas the percentage of sickled cells in samples treated with the adduct was 17 ± 1.2%. This indicated loss of anti-sickling activity in the case of the adduct. This study confirmed that hydroxyurea can participate in a Maillard reaction if lactose is used as a diluent. Although an extended study at environmentally feasible temperatures was not carried out in the present investigation, the partial loss of the anti-sickling activity of hydroxyurea was investigated along with the in silico drug-target interactions. The results indicated that the use of lactose in hydroxyurea formulations needs urgent reconsideration and that lactose must be replaced by other diluents that do not form Maillard adducts.

In Silico screening for functional candidates amongst hypothetical proteins

Directory of Open Access Journals (Sweden)

Sanderhoff May

2009-09-01

Full Text Available Abstract Background The definition of a hypothetical protein is a protein that is predicted to be expressed from an open reading frame, but for which there is no experimental evidence of translation. Hypothetical proteins constitute a substantial fraction of proteomes of human as well as of other eukaryotes. With the general belief that the majority of hypothetical proteins are the product of pseudogenes, it is essential to have a tool with the ability of pinpointing the minority of hypothetical proteins with a high probability of being expressed. Results Here, we present an in silico selection strategy where eukaryotic hypothetical proteins are sorted according to two criteria that can be reliably identified in silico: the presence of subcellular targeting signals and presence of characterized protein domains. To validate the selection strategy we applied it on a database of human hypothetical proteins dating to 2006 and compared the proteins predicted to be expressed by our selecting strategy, with their status in 2008. For the comparison we focused on mitochondrial proteins, since considerable amounts of research have focused on this field in between 2006 and 2008. Therefore, many proteins, defined as hypothetical in 2006, have later been characterized as mitochondrial. Conclusion Among the total amount of human proteins hypothetical in 2006, 21% have later been experimentally characterized and 6% of those have been shown to have a role in a mitochondrial context. In contrast, among the selected hypothetical proteins from the 2006 dataset, predicted by our strategy to have a mitochondrial role, 53-62% have later been experimentally characterized, and 85% of these have actually been assigned a role in mitochondria by 2008. Therefore our in silico selection strategy can be used to select the most promising candidates for subsequent in vitro and in vivo analyses.

In-silico smart library design to engineer a xylosetolerant ...

African Journals Online (AJOL)

In the current study, in-silico investigation was done aiming to select the amino acids in ScHxk2 that can be targeted in an engineering experiment. Using Autodock Vina, xylose binding to ScHxk2 structure (PDB 1IG8) was predicted. The information available about hexokinase family in the publicly available hexokinase ...

Regulatory analysis for final rule on nuclear power plant license renewal

International Nuclear Information System (INIS)

1991-12-01

This regulatory analysis provides the supporting information for the final rule (10 CFR Part 54) that defines the Nuclear Regulatory Commission's requirements for renewing the operating licenses of commercial nuclear power plants. A set of four specific alternatives for the safety review of license renewal applications is defined and evaluated. These are: Alternative A-current licensing basis; Alternative B-extension of Alternative A to require assessment and managing of aging; Alternative C -- extension of Alternative B to require assessment of design differences against selected new-plant standards using probabilistic risk assessment; and Alternative D -- extension of Alternative B to require compliance with all new-plant standards. A quantitative comparison of the four alternatives in terms of impact-to-value ratio is presented, and Alternative B is the most cost-beneficial safety review alternative

In silico characterization of a novel pathogenic deletion mutation identified in XPA gene in a Pakistani family with severe xeroderma pigmentosum.

Science.gov (United States)

Nasir, Muhammad; Ahmad, Nafees; Sieber, Christian M K; Latif, Amir; Malik, Salman Akbar; Hameed, Abdul

2013-09-24

Xeroderma Pigmentosum (XP) is a rare skin disorder characterized by skin hypersensitivity to sunlight and abnormal pigmentation. The aim of this study was to investigate the genetic cause of a severe XP phenotype in a consanguineous Pakistani family and in silico characterization of any identified disease-associated mutation. The XP complementation group was assigned by genotyping of family for known XP loci. Genotyping data mapped the family to complementation group A locus, involving XPA gene. Mutation analysis of the candidate XP gene by DNA sequencing revealed a novel deletion mutation (c.654del A) in exon 5 of XPA gene. The c.654del A, causes frameshift, which pre-maturely terminates protein and result into a truncated product of 222 amino acid (aa) residues instead of 273 (p.Lys218AsnfsX5). In silico tools were applied to study the likelihood of changes in structural motifs and thus interaction of mutated protein with binding partners. In silico analysis of mutant protein sequence, predicted to affect the aa residue which attains coiled coil structure. The coiled coil structure has an important role in key cellular interactions, especially with DNA damage-binding protein 2 (DDB2), which has important role in DDB-mediated nucleotide excision repair (NER) system. Our findings support the fact of genetic and clinical heterogeneity in XP. The study also predicts the critical role of DDB2 binding region of XPA protein in NER pathway and opens an avenue for further research to study the functional role of the mutated protein domain.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

Science.gov (United States)

Lepoivre, Cyrille; Bergon, Aurélie; Lopez, Fabrice; Perumal, Narayanan B; Nguyen, Catherine; Imbert, Jean; Puthier, Denis

2012-01-31

Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information

Singular Perturbation Analysis and Gene Regulatory Networks with Delay

Science.gov (United States)

Shlykova, Irina; Ponosov, Arcady

2009-09-01

There are different ways of how to model gene regulatory networks. Differential equations allow for a detailed description of the network's dynamics and provide an explicit model of the gene concentration changes over time. Production and relative degradation rate functions used in such models depend on the vector of steeply sloped threshold functions which characterize the activity of genes. The most popular example of the threshold functions comes from the Boolean network approach, where the threshold functions are given by step functions. The system of differential equations becomes then piecewise linear. The dynamics of this system can be described very easily between the thresholds, but not in the switching domains. For instance this approach fails to analyze stationary points of the system and to define continuous solutions in the switching domains. These problems were studied in [2], [3], but the proposed model did not take into account a time delay in cellular systems. However, analysis of real gene expression data shows a considerable number of time-delayed interactions suggesting that time delay is essential in gene regulation. Therefore, delays may have a great effect on the dynamics of the system presenting one of the critical factors that should be considered in reconstruction of gene regulatory networks. The goal of this work is to apply the singular perturbation analysis to certain systems with delay and to obtain an analog of Tikhonov's theorem, which provides sufficient conditions for constracting the limit system in the delay case.

In Silico Screening Hepatitis B Virus DNA Polymerase Inhibitors from Medicinal Plants

Directory of Open Access Journals (Sweden)

Mokhtar Nosrati

2017-08-01

Full Text Available Abstract Background: Hepatitis B virus infection (HBV is a significant global health problem and is a major cause of morbidity and mortality worldwide. Therefore, currently, introducing novel anti Hepatitis B drugs is taken into consideration. This study was planned to in silico screening novel Hepatitis B virus DNA polymerase inhibitors from two medicinal plants Terminalis chebula and Caesalpinia sappan. Materials and Methods: This is a descriptive-analytic study. In the study, three-dimensional structure of the Hepatitis B virus DNA polymerase was predicted using homology modeling method. A set of phytochemicals from mentioned plants were retrieved from Pubchem database in SDF format. In silico screening was carried out using molecular docking between mentioned phytochemicals and modeled polymerase by iGemdock 2.1 software. Results: Results of the study confirmed that all evaluated ligands have appropriate interactions to the polymerase with least toxicity and without genotoxicity potential. Results also showed that most interactions occur in reverse transcriptase domain which located in 354-694 area in the amino acid sequence of tested polymerase. Analysis of energy and amino acids involved in ligand-polymerase interaction revealed that Terchebin, Chebulinic Acid and Terflavin A have more effective interaction with the polymerase in compared to other ligands. Conclusion: Based on the results it can be concluded that evaluated compounds could be good candidates for in vitro and in vivo research in order to develop novel anti- Hepatitis B drugs.

In silico analysis and experimental validation of azelastine hydrochloride (N4) targeting sodium taurocholate co-transporting polypeptide (NTCP) in HBV therapy.

Science.gov (United States)

Fu, L-L; Liu, J; Chen, Y; Wang, F-T; Wen, X; Liu, H-Q; Wang, M-Y; Ouyang, L; Huang, J; Bao, J-K; Wei, Y-Q

2014-08-01

The aim of this study was to explore sodium taurocholate co-transporting polypeptide (NTCP) exerting its function with hepatitis B virus (HBV) and its targeted candidate compounds, in HBV therapy. Identification of NTCP as a novel HBV target for screening candidate small molecules, was used by phylogenetic analysis, network construction, molecular modelling, molecular docking and molecular dynamics (MD) simulation. In vitro virological examination, q-PCR, western blotting and cytotoxicity studies were used for validating efficacy of the candidate compound. We used the phylogenetic analysis of NTCP and constructed its protein-protein network. Also, we screened compounds from Drugbank and ZINC, among which five were validated for their authentication in HepG 2.2.15 cells. Then, we selected compound N4 (azelastine hydrochloride) as the most potent of them. This showed good inhibitory activity against HBsAg (IC50 = 7.5 μm) and HBeAg (IC50 = 3.7 μm), as well as high SI value (SI = 4.68). Further MD simulation results supported good interaction between compound N4 and NTCP. In silico analysis and experimental validation together demonstrated that compound N4 can target NTCP in HepG2.2.15 cells, which may shed light on exploring it as a potential anti-HBV drug. © 2014 John Wiley & Sons Ltd.

In Silico Theoretical Molecular Modeling for Alzheimer’s Disease: The Nicotine-Curcumin Paradigm in Neuroprotection and Neurotherapy

Directory of Open Access Journals (Sweden)

Yahya E. Choonara

2011-01-01

Full Text Available The aggregation of the amyloid-β-peptide (AβP into well-ordered fibrils has been considered as the key pathological marker of Alzheimer’s disease. Molecular attributes related to the specific binding interactions, covalently and non-covalently, of a library of compounds targeting of conformational scaffolds were computed employing static lattice atomistic simulations and array constructions. A combinatorial approach using isobolographic analysis was stochastically modeled employing Artificial Neural Networks and a Design of Experiments approach, namely an orthogonal Face-Centered Central Composite Design for small molecules, such as curcumin and glycosylated nornicotine exhibiting concentration-dependent behavior on modulating AβP aggregation and oligomerization. This work provides a mathematical and in silico approach that constitutes a new frontier in providing neuroscientists with a template for in vitro and in vivo experimentation. In future this could potentially allow neuroscientists to adopt this in silico approach for the development of novel therapeutic interventions in the neuroprotection and neurotherapy of Alzheimer’s disease. In addition, the neuroprotective entities identified in this study may also be valuable in this regard.

In Silico-Based High-Throughput Screen for Discovery of Novel Combinations for Tuberculosis Treatment

Science.gov (United States)

Singh, Ragini; Ramachandran, Vasanthi; Shandil, Radha; Sharma, Sreevalli; Khandelwal, Swati; Karmarkar, Malancha; Kumar, Naveen; Solapure, Suresh; Saralaya, Ramanatha; Nanduri, Robert; Panduga, Vijender; Reddy, Jitendar; Prabhakar, K. R.; Rajagopalan, Swaminathan; Rao, Narasimha; Narayanan, Shridhar; Anandkumar, Anand; Datta, Santanu

2015-01-01

There are currently 18 drug classes for the treatment of tuberculosis, including those in the development pipeline. An in silico simulation enabled combing the innumerably large search space to derive multidrug combinations. Through the use of ordinary differential equations (ODE), we constructed an in silico kinetic platform in which the major metabolic pathways in Mycobacterium tuberculosis and the mechanisms of the antituberculosis drugs were integrated into a virtual proteome. The optimized model was used to evaluate 816 triplets from the set of 18 drugs. The experimentally derived cumulative fractional inhibitory concentration (∑FIC) value was within twofold of the model prediction. Bacterial enumeration revealed that a significant number of combinations that were synergistic for growth inhibition were also synergistic for bactericidal effect. The in silico-based screen provided new starting points for testing in a mouse model of tuberculosis, in which two novel triplets and five novel quartets were significantly superior to the reference drug triplet of isoniazid, rifampin, and ethambutol (HRE) or the quartet of HRE plus pyrazinamide (HREZ). PMID:26149995

77 FR 8082 - Regulatory Flexibility Agenda

Science.gov (United States)

2012-02-13

... Required: Yes. Agency Contact: Alicia Goldin, Division of Trading and Markets, Securities and Exchange.../01/11 Regulatory Flexibility Analysis Required: Yes. Agency Contact: Alicia Goldin, Division of... Withdrawn 10/01/11 Regulatory Flexibility Analysis Required: Yes. Agency Contact: Alicia Goldin, Division of...

Solid-phase reduction of silico-12-molybdic acid H4SiMo12O40 by some organic oxygen containing compounds

International Nuclear Information System (INIS)

Chuvaev, V.F.; Pinchuk, I.N.; Spitsyn, V.I.

1982-01-01

A study is made on reduction reactions of anhydrous silico-12-molybdic acid by vapors of organic oxygen-containing compounds at 170 deg C: alcohols, simple carbonyl compounds. Methods of thermal analysis, electron paramagnetic resonance, paramagnetic resonance were used to established that depending on the nature of organic reagent and temperature, H 6 SiMo 2 5 Mo 10 6 O 40 two-electron or H 8 SiMo 4 5 Mo 8 6 O 40 four-electron flues form. It is shown that the increase of heterogeneous reduction temperature can lead to formation of anhydrous phases of SiMo 12 O 38 -(n/2), able to attach water reversibly with formation of corresponding blue. Characteristics of blues, prepared during solid-phase reduction of silico-12-molybdic acid and mixed valent forms with corresponding reduction degree, separated from water solutions, were compared

Large-scale identification of polymorphic microsatellites using an in silico approach

NARCIS (Netherlands)

Tang, J.; Baldwin, S.J.; Jacobs, J.M.E.; Linden, van der C.G.; Voorrips, R.E.; Leunissen, J.A.M.; Eck, van H.J.; Vosman, B.

2008-01-01

Background - Simple Sequence Repeat (SSR) or microsatellite markers are valuable for genetic research. Experimental methods to develop SSR markers are laborious, time consuming and expensive. In silico approaches have become a practicable and relatively inexpensive alternative during the last

In-silico design of novel myocilin inhibitors for glaucoma therapy ...

African Journals Online (AJOL)

Purpose: To explore newer computational approaches in the design of novel myocilin inhibitors for the treatment of glaucoma. Methods: An in-silico virtual screening technique based on simulation of molecular docking was utilised to design a novel myocilin inhibitors for the treatment of glaucoma. The designed novel ...

Flow cytometric analysis of regulatory T cells during hyposensitization of acquired allergic contact dermatitis.

Science.gov (United States)

Fraser, Kathleen; Abbas, Mariam; Hull, Peter R

2014-01-01

We previously demonstrated that repeated intradermal steroid injections administered at weekly intervals into positive patch-test sites induce hyposensitization and desensitization. To examine changes in CD4CD25CD127lo/ regulatory T cells during the attenuation of the patch-test response. Ten patients with known allergic contact dermatitis were patch tested weekly for 10 weeks. The patch-test site was injected intradermally with 2 mg triamcinolone. At weeks 1 and 7, a biopsy was performed on the patch-test site in 6 patients, and flow cytometry was performed assessing CD4CD25CD127lo/ regulatory T cells. Secondary outcomes were clinical score, reaction size, erythema, and temperature. Statistical analysis included regression, correlation, and repeated-measures analysis of variance. The percentage of CD4CD25CD127lo/ regulatory T cells, measured by flow cytometry, increased from week 1 to week 7 by an average of 19.2%. The average grade of patch-test reaction decreased from +++ (vesicular reaction) to ++ (palpable erythema). The mean drop in temperature following treatment was 0.28°C per week. The mean area decreased 8.6 mm/wk over 10 weeks. Intradermal steroid injections of weekly patch-test reactions resulted in hyposensitization of the allergic contact dermatitis reaction. CD4CD25CD127lo/ regulatory T cells showed a tendency to increase; however, further studies are needed to determine if this is significant.

In silico analysis of the polygalacturonase inhibiting protein 1 from apple, Malus domestica.

Science.gov (United States)

Matsaunyane, Lerato Bt; Oelofse, Dean; Dubery, Ian A

2015-03-11

The Malus domestica polygalacturonase inhibiting protein 1 (MdPGIP1) gene, encoding the M. domestica polygalacturonase inhibiting protein 1 (MdPGIP1), was isolated from the Granny Smith apple cultivar (GenBank accession no. DQ185063). The gene was used to transform tobacco and potato for enhanced resistance against fungal diseases. Analysis of the MdPGIP1 nucleotide sequence revealed that the gene comprises 993 nucleotides that encode a 330 amino acid polypeptide. In silico characterization of the MdPGIP1 polypeptide revealed domains typical of PGIP proteins, which include a 24 amino acid putative signal peptide, a potential cleavage site [Alanine-Leucine-Serine (ALS)] for the signal peptide, a 238 amino acid leucine-rich repeat (LRR) domain, a 46 amino acid N-terminal domain and a 22 amino acid C-terminal domain. The hydropathic evaluation of MdPGIP1 indicated a repetitive hydrophobic motif in the LRR domain and a hydrophilic surface area consistent with a globular protein. The typical consensus glycosylation sequence of Asn-X-Ser/Thr was identified in MdPGIP1, indicating potential N-linked glycosylation of MdPGIP1. The molecular mass of non-glycosylated MdPGIP1 was calculated as 36.615 kDa and the theoretical isoelectric point as 6.98. Furthermore, the secondary and tertiary structure of MdPGIP1 was modelled, and revealed that MdPGIP1 is a curved and elongated molecule that contains sheet B1, sheet B2 and 310-helices on its LRR domain. The overall properties of the MdPGIP1 protein is similar to that of the prototypical Phaseolus vulgaris PGIP 2 (PvPGIP2), and the detected differences supported its use in biotechnological applications as an inhibitor of targeted fungal polygalacturonases (PGs).

Evaluation and optimized selection of supersaturating drug delivery systems of posaconazole (BCS class 2b) in the gastrointestinal simulator (GIS): An in vitro-in silico-in vivo approach.

Science.gov (United States)

Hens, Bart; Bermejo, Marival; Tsume, Yasuhiro; Gonzalez-Alvarez, Isabel; Ruan, Hao; Matsui, Kazuki; Amidon, Gregory E; Cavanagh, Katie L; Kuminek, Gislaine; Benninghoff, Gail; Fan, Jianghong; Rodríguez-Hornedo, Naír; Amidon, Gordon L

2018-03-30

Supersaturating drug delivery systems (SDDS) have been put forward in the recent decades in order to circumvent the issue of low aqueous solubility. Prior to the start of clinical trials, these enabling formulations should be adequately explored in in vitro/in silico studies in order to understand their in vivo performance and to select the most appropriate and effective formulation in terms of oral bioavailability and therapeutic outcome. The purpose of this work was to evaluate the in vivo performance of four different oral formulations of posaconazole (categorized as a biopharmaceutics classification system (BCS) class 2b compound) based on the in vitro concentrations in the gastrointestinal simulator (GIS), coupled with an in silico pharmacokinetic model to predict their systemic profiles. Recently published intraluminal and systemic concentrations of posaconazole for these formulations served as a reference to validate the in vitro and in silico results. Additionally, the morphology of the formed precipitate of posaconazole was visualized and characterized by optical microscopy studies and thermal analysis. This multidisciplinary work demonstrates an in vitro-in silico-in vivo approach that provides a scientific basis for screening SDDS by a user-friendly formulation predictive dissolution (fPD) device in order to rank these formulations towards their in vivo performance. Copyright © 2018. Published by Elsevier B.V.

In silico imaging: Definition, possibilities and challenges

International Nuclear Information System (INIS)

Badano, Aldo

2011-01-01

The capability to simulate the imaging performance of new detector concepts is crucial to develop the next generation of medical imaging systems. Proper modeling tools allow for optimal designs that maximize image quality while minimizing patient and occupational radiation doses. In this context, in silico imaging has become an emerging field of imaging research. This paper reviews current progress and challenges in the simulation of imaging systems with a focus on Monte Carlo approaches to X-ray detector modeling, acceleration approaches, and validation strategies.

Analysis and evaluation of regulatory uncertainties in 10 CFR 60 subparts B and E

International Nuclear Information System (INIS)

Weiner, R.F.; Patrick, W.C.

1990-01-01

This paper presents an attribute analysis scheme for prioritizing the resolution of regulatory uncertainties. Attributes are presented which assist in identifying the need for timeliness and durability of the resolution of an uncertainty

Protein expression of Myt272-3 recombinant clone and in silico ...

African Journals Online (AJOL)

Usman et al. Trop J Pharm Res, July ... silico prediction of a possible vaccine candidate against .... standard methods described by Bringans et al. [12]. ..... Payan J, Francisco-Cruz A, Valdivia JA, Hernández- ... Nat Protoc 2006; 1: 16-. 22. 12.

Identification of a cis-regulatory element by transient analysis of co-ordinately regulated genes

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Allan Andrew C

2008-07-01

Full Text Available Abstract Background Transcription factors (TFs co-ordinately regulate target genes that are dispersed throughout the genome. This co-ordinate regulation is achieved, in part, through the interaction of transcription factors with conserved cis-regulatory motifs that are in close proximity to the target genes. While much is known about the families of transcription factors that regulate gene expression in plants, there are few well characterised cis-regulatory motifs. In Arabidopsis, over-expression of the MYB transcription factor PAP1 (PRODUCTION OF ANTHOCYANIN PIGMENT 1 leads to transgenic plants with elevated anthocyanin levels due to the co-ordinated up-regulation of genes in the anthocyanin biosynthetic pathway. In addition to the anthocyanin biosynthetic genes, there are a number of un-associated genes that also change in expression level. This may be a direct or indirect consequence of the over-expression of PAP1. Results Oligo array analysis of PAP1 over-expression Arabidopsis plants identified genes co-ordinately up-regulated in response to the elevated expression of this transcription factor. Transient assays on the promoter regions of 33 of these up-regulated genes identified eight promoter fragments that were transactivated by PAP1. Bioinformatic analysis on these promoters revealed a common cis-regulatory motif that we showed is required for PAP1 dependent transactivation. Conclusion Co-ordinated gene regulation by individual transcription factors is a complex collection of both direct and indirect effects. Transient transactivation assays provide a rapid method to identify direct target genes from indirect target genes. Bioinformatic analysis of the promoters of these direct target genes is able to locate motifs that are common to this sub-set of promoters, which is impossible to identify with the larger set of direct and indirect target genes. While this type of analysis does not prove a direct interaction between protein and DNA

In Vivo and In Silico Investigation Into Mechanisms of Frequency Dependence of Repolarization Alternans in Human Ventricular Cardiomyocytes.

Science.gov (United States)

Zhou, Xin; Bueno-Orovio, Alfonso; Orini, Michele; Hanson, Ben; Hayward, Martin; Taggart, Peter; Lambiase, Pier D; Burrage, Kevin; Rodriguez, Blanca

2016-01-22

Repolarization alternans (RA) are associated with arrhythmogenesis. Animal studies have revealed potential mechanisms, but human-focused studies are needed. RA generation and frequency dependence may be determined by cell-to-cell variability in protein expression, which is regulated by genetic and external factors. To characterize in vivo RA in human and to investigate in silico using human models, the ionic mechanisms underlying the frequency-dependent differences in RA behavior identified in vivo. In vivo electrograms were acquired at 240 sites covering the epicardium of 41 patients at 6 cycle lengths (600-350 ms). In silico investigations were conducted using a population of biophysically detailed human models incorporating variability in protein expression and calibrated using in vivo recordings. Both in silico and in vivo, 2 types of RA were identified, with Fork- and Eye-type restitution curves, based on RA persistence or disappearance, respectively, at fast pacing rates. In silico simulations show that RA are strongly correlated with fluctuations in sarcoplasmic reticulum calcium, because of strong release and weak reuptake. Large L-type calcium current conductance is responsible for RA disappearance at fast frequencies in Eye-type (30% larger in Eye-type versus Fork-type; Psilico, 2 types of RA are identified, with RA persistence/disappearance as frequency increases. In silico, L-type calcium current and Na(+)/Ca(2+) exchanger current determine RA human cell-to-cell differences through intracellular and sarcoplasmic reticulum calcium regulation. © 2015 The Authors.

In Vitro and In Silico Risk Assessment in Acquired Long QT Syndrome: The Devil Is in the Details.

Science.gov (United States)

Lee, William; Windley, Monique J; Vandenberg, Jamie I; Hill, Adam P

2017-01-01

Acquired long QT syndrome, mostly as a result of drug block of the Kv11. 1 potassium channel in the heart, is characterized by delayed cardiac myocyte repolarization, prolongation of the T interval on the ECG, syncope and sudden cardiac death due to the polymorphic ventricular arrhythmia Torsade de Pointes (TdP). In recent years, efforts are underway through the Comprehensive in vitro proarrhythmic assay (CiPA) initiative, to develop better tests for this drug induced arrhythmia based in part on in silico simulations of pharmacological disruption of repolarization. However, drug binding to Kv11.1 is more complex than a simple binary molecular reaction, meaning simple steady state measures of potency are poor surrogates for risk. As a result, there is a plethora of mechanistic detail describing the drug/Kv11.1 interaction-such as drug binding kinetics, state preference, temperature dependence and trapping-that needs to be considered when developing in silico models for risk prediction. In addition to this, other factors, such as multichannel pharmacological profile and the nature of the ventricular cell models used in simulations also need to be considered in the search for the optimum in silico approach. Here we consider how much of mechanistic detail needs to be included for in silico models to accurately predict risk and further, how much of this detail can be retrieved from protocols that are practical to implement in high throughout screens as part of next generation of preclinical in silico drug screening approaches?

In silico modeling for tumor growth visualization.

Science.gov (United States)

Jeanquartier, Fleur; Jean-Quartier, Claire; Cemernek, David; Holzinger, Andreas

2016-08-08

Cancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models. Research on tumor growth involves a plethora of models each emphasizing isolated aspects of benign and malignant neoplasms. Biologists and clinical scientists are often overwhelmed by the mathematical background knowledge necessary to grasp and to apply a model to their own research. We aim to provide a comprehensive and expandable simulation tool to visualizing tumor growth. This novel Web-based application offers the advantage of a user-friendly graphical interface with several manipulable input variables to correlate different aspects of tumor growth. By refining model parameters we highlight the significance of heterogeneous intercellular interactions on tumor progression. Within this paper we present the implementation of the Cellular Potts Model graphically presented through Cytoscape.js within a Web application. The tool is available under the MIT license at https://github.com/davcem/cpm-cytoscape and http://styx.cgv.tugraz.at:8080/cpm-cytoscape/ . In-silico methods overcome the lack of wet experimental possibilities and as dry method succeed in terms of reduction, refinement and replacement of animal experimentation, also known as the 3R principles. Our visualization approach to simulation allows for more flexible usage and easy extension to facilitate understanding and gain novel insight. We believe that biomedical research in general and research on tumor growth in particular will benefit from the systems biology perspective.

Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics.

Science.gov (United States)

Ernst, Corinna; Hahnen, Eric; Engel, Christoph; Nothnagel, Michael; Weber, Jonas; Schmutzler, Rita K; Hauke, Jan

2018-03-27

prediction tools are not suitable to predict pathogenicity of variants of uncertain significance in BRCA1/2. Thus, clinical consequences should never be based solely on in silico forecasts. However, our data suggests that SIFT and MutationTaster2 could be suitable to predict benignity, as both tools did not result in false negative predictions in our analysis.

Alzheimer’s Disease and HLA-A2: Linking Neurodegenerative to Immune Processes through an In Silico Approach

Directory of Open Access Journals (Sweden)

Ricardo A. Cifuentes

2014-01-01

Full Text Available There is a controversial relationship between HLA-A2 and Alzheimer’s disease (AD. It has been suggested a modifier effect on the risk that depends on genetic loadings. Thus, the aims of this study were to evaluate this relationship and to reveal genes associated with both concepts the HLA-A gene and AD. Consequently, we did first a classical systematic review and a meta-analysis of case-control studies. Next, by means of an in silico approach, we used experimental knowledge of protein-protein interactions to evaluate the top ranked genes shared by both concepts, previously found through text mining. The meta-analysis did not show a significant pooled OR (1.11, 95% CI: 0.98 to 1.24 in Caucasians, in spite of the fact that four of the included studies had a significant OR > 1 and none of them a significant OR < 1. In contrast, the in silico approach retrieved nonrandomly shared genes by both concepts (P = 0.02, which additionally encode truly interacting proteins. The network of proteins encoded by APP, ICAM-1, ITGB2, ITGAL, SELP, SELL, IL2, IL1B, CD4, and CD8A linked immune to neurodegenerative processes and highlighted the potential roles in AD pathogenesis of endothelial regulation, infectious diseases, specific antigen presentation, and HLA-A2 in maintaining synapses.

Discordance between in silico & in vitro analyses of ACE inhibitory & antioxidative peptides from mixed milk tryptic whey protein hydrolysate.

Science.gov (United States)

Chatterjee, Alok; Kanawjia, S K; Khetra, Yogesh; Saini, Prerna

2015-09-01

ACE inhibitory and antioxidative peptides identified by LCMS/MS, from mixed milk (Bubalus bubalis and Bos taurus) tryptic whey protein hydrolysate, were compared with the in silico predictions. α la and ß lg sequences, both from Bubalus bubalis and Bos taurus, were used for in silico study. SWISS-PROT and BIOPEP protein libraries were accessed for prediction of peptide generation. Study observed gaps in the prediction versus actual results, which remain unaddressed in the literature. Many peptides obtained in vitro, were not reflected in in silico predictions. Differences in identified peptides in separate libraries were observed too. In in silico prediction, peptides with known biological activities were also not reflected. Predictions, towards generation of bioactive peptides, based upon in silico release of proteins and amino acid sequences from different sources and thereupon validation in relation to actual results has often been reported in research literature. Given that computer aided simulation for prediction purposes is an effective research direction, regular updating of protein libraries and an effectual integration, for more precise results, is critical. The gaps addressed between these two techniques of research, have not found any address in literature. Inclusion of more flexibility with the variables, within the tools being used for prediction, and a hierarchy based database with search options for various peptides, will further enhance the scope and strength of research.

A new in silico classification model for ready biodegradability, based on molecular fragments.

Science.gov (United States)

Lombardo, Anna; Pizzo, Fabiola; Benfenati, Emilio; Manganaro, Alberto; Ferrari, Thomas; Gini, Giuseppina

2014-08-01

Regulations such as the European REACH (Registration, Evaluation, Authorization and restriction of Chemicals) often require chemicals to be evaluated for ready biodegradability, to assess the potential risk for environmental and human health. Because not all chemicals can be tested, there is an increasing demand for tools for quick and inexpensive biodegradability screening, such as computer-based (in silico) theoretical models. We developed an in silico model starting from a dataset of 728 chemicals with ready biodegradability data (MITI-test Ministry of International Trade and Industry). We used the novel software SARpy to automatically extract, through a structural fragmentation process, a set of substructures statistically related to ready biodegradability. Then, we analysed these substructures in order to build some general rules. The model consists of a rule-set made up of the combination of the statistically relevant fragments and of the expert-based rules. The model gives good statistical performance with 92%, 82% and 76% accuracy on the training, test and external set respectively. These results are comparable with other in silico models like BIOWIN developed by the United States Environmental Protection Agency (EPA); moreover this new model includes an easily understandable explanation. Copyright © 2014 Elsevier Ltd. All rights reserved.

An in-silico investigation of anti-Chagas phytochemicals.

Science.gov (United States)

McCulley, Stephanie F; Setzer, William N

2014-01-01

Over 18 million people in tropical and subtropical America are afflicted by American trypanosomiasis or Chagas disease. In humans, symptoms of the disease include fever, swelling, and heart and brain damage, usually leading to death. There is currently no effective treatment for this disease. Plant products continue to be rich sources of clinically useful drugs, and the biodiversity of the Neotropics suggests great phytomedicinal potential. Screening programs have revealed numerous plant species and phytochemical agents that have shown in-vitro or in-vivo antitrypanosomal activity, but the biochemical targets of these phytochemicals are not known. In this work, we present a molecular docking analysis of Neotropical phytochemicals, which have already demonstrated antiparasitic activity against Trypanosoma cruzi, with potential druggable protein targets of the parasite. Several protein targets showed in-silico selectivity for trypanocidal phytochemicals, including trypanothione reductase, pteridine reductase 2, lipoamide dehydrogenase, glucokinase, dihydroorotate dehydrogenase, cruzain, dihydrofolate-reductase/thymidylate-synthase, and farnesyl diphosphate synthase. Some of the phytochemical ligands showed notable docking preference for trypanothione reductase, including flavonoids, fatty-acid-derived oxygenated hydrocarbons, geranylgeraniol and the lignans ganschisandrine and eupomatenoid-6.

Regulatory agencies and regulatory risk

OpenAIRE

Knieps, Günter; Weiß, Hans-Jörg

2008-01-01

The aim of this paper is to show that regulatory risk is due to the discretionary behaviour of regulatory agencies, caused by a too extensive regulatory mandate provided by the legislator. The normative point of reference and a behavioural model of regulatory agencies based on the positive theory of regulation are presented. Regulatory risk with regard to the future behaviour of regulatory agencies is modelled as the consequence of the ex ante uncertainty about the relative influence of inter...

In Silico Assigned Resistance Genes Confer Bifidobacterium with Partial Resistance to Aminoglycosides but Not to Β-Lactams

Science.gov (United States)

Fouhy, Fiona; O’Connell Motherway, Mary; Fitzgerald, Gerald F.; Ross, R. Paul; Stanton, Catherine; van Sinderen, Douwe; Cotter, Paul D.

2013-01-01

Bifidobacteria have received significant attention due to their contribution to human gut health and the use of specific strains as probiotics. It is thus not surprising that there has also been significant interest with respect to their antibiotic resistance profile. Numerous culture-based studies have demonstrated that bifidobacteria are resistant to the majority of aminoglycosides, but are sensitive to β-lactams. However, limited research exists with respect to the genetic basis for the resistance of bifidobacteria to aminoglycosides. Here we performed an in-depth in silico analysis of putative Bifidobacterium-encoded aminoglycoside resistance proteins and β-lactamases and assess the contribution of these proteins to antibiotic resistance. The in silico-based screen detected putative aminoglycoside and β-lactam resistance proteins across the Bifidobacterium genus. Laboratory-based investigations of a number of representative bifidobacteria strains confirmed that despite containing putative β-lactamases, these strains were sensitive to β-lactams. In contrast, all strains were resistant to the aminoglycosides tested. To assess the contribution of genes encoding putative aminoglycoside resistance proteins in Bifidobacterium sp. two genes, namely Bbr_0651 and Bbr_1586, were targeted for insertional inactivation in B. breve UCC2003. As compared to the wild-type, the UCC2003 insertion mutant strains exhibited decreased resistance to gentamycin, kanamycin and streptomycin. This study highlights the associated risks of relying on the in silico assignment of gene function. Although several putative β-lactam resistance proteins are located in bifidobacteria, their presence does not coincide with resistance to these antibiotics. In contrast however, this approach has resulted in the identification of two loci that contribute to the aminoglycoside resistance of B. breve UCC2003 and, potentially, many other bifidobacteria. PMID:24324818

In silico assigned resistance genes confer Bifidobacterium with partial resistance to aminoglycosides but not to β-lactams.

Directory of Open Access Journals (Sweden)

Fiona Fouhy

Full Text Available Bifidobacteria have received significant attention due to their contribution to human gut health and the use of specific strains as probiotics. It is thus not surprising that there has also been significant interest with respect to their antibiotic resistance profile. Numerous culture-based studies have demonstrated that bifidobacteria are resistant to the majority of aminoglycosides, but are sensitive to β-lactams. However, limited research exists with respect to the genetic basis for the resistance of bifidobacteria to aminoglycosides. Here we performed an in-depth in silico analysis of putative Bifidobacterium-encoded aminoglycoside resistance proteins and β-lactamases and assess the contribution of these proteins to antibiotic resistance. The in silico-based screen detected putative aminoglycoside and β-lactam resistance proteins across the Bifidobacterium genus. Laboratory-based investigations of a number of representative bifidobacteria strains confirmed that despite containing putative β-lactamases, these strains were sensitive to β-lactams. In contrast, all strains were resistant to the aminoglycosides tested. To assess the contribution of genes encoding putative aminoglycoside resistance proteins in Bifidobacterium sp. two genes, namely Bbr_0651 and Bbr_1586, were targeted for insertional inactivation in B. breve UCC2003. As compared to the wild-type, the UCC2003 insertion mutant strains exhibited decreased resistance to gentamycin, kanamycin and streptomycin. This study highlights the associated risks of relying on the in silico assignment of gene function. Although several putative β-lactam resistance proteins are located in bifidobacteria, their presence does not coincide with resistance to these antibiotics. In contrast however, this approach has resulted in the identification of two loci that contribute to the aminoglycoside resistance of B. breve UCC2003 and, potentially, many other bifidobacteria.

A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Non-Small Cell Lung Cancer.

Science.gov (United States)

Raju, G K; Gurumurthi, K; Domike, R; Kazandjian, D; Blumenthal, G; Pazdur, R; Woodcock, J

2016-12-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analyses. There is much interest in quantifying regulatory approaches to benefit and risk. In this work the use of a quantitative benefit-risk analysis was applied to regulatory decision-making about new drugs to treat advanced non-small cell lung cancer (NSCLC). Benefits and risks associated with 20 US Food and Drug Administration (FDA) decisions associated with a set of candidate treatments submitted between 2003 and 2015 were analyzed. For benefit analysis, the median overall survival (OS) was used where available. When not available, OS was estimated based on overall response rate (ORR) or progression-free survival (PFS). Risks were analyzed based on magnitude (or severity) of harm and likelihood of occurrence. Additionally, a sensitivity analysis was explored to demonstrate analysis of systematic uncertainty. FDA approval decision outcomes considered were found to be consistent with the benefit-risk logic. © 2016 American Society for Clinical Pharmacology and Therapeutics.

78 FR 44275 - Semiannual Regulatory Agenda

Science.gov (United States)

2013-07-23

... Rights. National Park Service--Completed Actions Regulation Sequence No. Title Identifier No. 200 Winter.... Timetable: Action Date FR Cite NPRM 07/00/13 Final Action 05/00/14 Regulatory Flexibility Analysis Required...: Action Date FR Cite NPRM 10/00/14 Final Action 10/00/14 Regulatory Flexibility Analysis Required: Yes...

Rapid in silico cloning of genes using expressed sequence tags (ESTs).

Science.gov (United States)

Gill, R W; Sanseau, P

2000-01-01

Expressed sequence tags (ESTs) are short single-pass DNA sequences obtained from either end of cDNA clones. These ESTs are derived from a vast number of cDNA libraries obtained from different species. Human ESTs are the bulk of the data and have been widely used to identify new members of gene families, as markers on the human chromosomes, to discover polymorphism sites and to compare expression patterns in different tissues or pathologies states. Information strategies have been devised to query EST databases. Since most of the analysis is performed with a computer, the term "in silico" strategy has been coined. In this chapter we will review the current status of EST databases, the pros and cons of EST-type data and describe possible strategies to retrieve meaningful information.

Role of Alternative Polyadenylation during Adipogenic Differentiation: An In Silico Approach

Science.gov (United States)

Spangenberg, Lucía; Correa, Alejandro; Dallagiovanna, Bruno; Naya, Hugo

2013-01-01

Post-transcriptional regulation of stem cell differentiation is far from being completely understood. Changes in protein levels are not fully correlated with corresponding changes in mRNAs; the observed differences might be partially explained by post-transcriptional regulation mechanisms, such as alternative polyadenylation. This would involve changes in protein binding, transcript usage, miRNAs and other non-coding RNAs. In the present work we analyzed the distribution of alternative transcripts during adipogenic differentiation and the potential role of miRNAs in post-transcriptional regulation. Our in silico analysis suggests a modest, consistent, bias in 3′UTR lengths during differentiation enabling a fine-tuned transcript regulation via small non-coding RNAs. Including these effects in the analyses partially accounts for the observed discrepancies in relative abundance of protein and mRNA. PMID:24143171

Russian regulatory approaches to seismic design and seismic analysis of NPP piping

International Nuclear Information System (INIS)

Kaliberda, Y.V.

2003-01-01

The paper presents an overview of Russian regulatory approaches to seismic design and seismic analysis of NPP piping. The paper is focused on categorization and seismic analysis of nuclear power plant items (piping, equipment, supports, valves, but not building structures). The paper outlines the current seismic recommendations, corresponding methods with the examples of calculation models. The paper considers calculation results of the mechanisms of dynamic behavior and the problems of developing a rational and economical approaches to seismic design and seismic protection. (author)

Practical application of in silico fragmentation based residue screening with ion mobility high-resolution mass spectrometry.

Science.gov (United States)

Kaufmann, Anton; Butcher, Patrick; Maden, Kathry; Walker, Stephan; Widmer, Mirjam

2017-07-15

A screening concept for residues in complex matrices based on liquid chromatography coupled to ion mobility high-resolution mass spectrometry LC/IMS-HRMS is presented. The comprehensive four-dimensional data (chromatographic retention time, drift time, mass-to-charge and ion abundance) obtained in data-independent acquisition (DIA) mode was used for data mining. An in silico fragmenter utilizing a molecular structure database was used for suspect screening, instead of targeted screening with reference substances. The utilized data-independent acquisition mode relies on the MS E concept; where two constantly alternating HRMS scans (low and high fragmentation energy) are acquired. Peak deconvolution and drift time alignment of ions from the low (precursor ion) and high (product ion) energy scan result in relatively clean product ion spectra. A bond dissociation in silico fragmenter (MassFragment) supplied with mol files of compounds of interest was used to explain the observed product ions of each extracted candidate component (chromatographic peak). Two complex matrices (fish and bovine liver extract) were fortified with 98 veterinary drugs. Out of 98 screened compounds 94 could be detected with the in silico based screening approach. The high correlation among drift time and m/z value of equally charged ions was utilized for an orthogonal filtration (ranking). Such an orthogonal ion mobility based filter removes multiply charged ions (e.g. peptides and proteins from the matrix) as well as noise and artefacts. Most significantly, this filtration dramatically reduces false positive findings but hardly increases false negative findings. The proposed screening approach may offer new possibilities for applications where reference compounds are hardly or not at all commercially available. Such areas may be the analysis of metabolites of drugs, pyrrolizidine alkaloids, marine toxins, derivatives of sildenafil or novel designer drugs (new psychoactive substances

Crystal structure study of new lanthanide silicates with silico-carnotite structure

International Nuclear Information System (INIS)

Piccinelli, F.; Lausi, A.; Speghini, A.; Bettinelli, M.

2012-01-01

The crystal structures of new rare earth-based silicate compounds (Ca 3 Eu 2 Si 3 O 12 , Ca 3 Gd 2 Si 3 O 12 , Ca 3 Dy 2 Si 3 O 12 , Ca 3 Er 2 Si 3 O 12 and Ca 3 Lu 2 Si 3 O 12 ) have been determined using powder X-ray diffraction. From Rietveld refinement calculations on the collected powder patterns we observe a different distribution of the rare earth ions on the three available crystal sites characterized by different coordination numbers, depending on the ionic radius of the rare earth ion. The reasons of the instability of the silico-carnotite structure for lanthanide ions larger than Eu 3+ have been deduced. In addition, in order to detect crystal phase transitions, the powder patterns of Ca 3 Eu 2 Si 3 O 12 and Ca 3 Sm 2 Si 3 O 12 samples have been collected as a function of the temperature (RT-1000 °C range), but no phase transitions have been observed. - Graphical abstract: Synchrotron X-ray diffraction allows us the accurate determination of the RE 3+ ions distribution on the three available crystal sites of the silico-carnotite structure. Highlights: ► The structure of the Ca 3 M 2 Si 3 O 12 (M=Eu, Gd, Dy, Er and Lu) was determined. ► Different distribution of RE 3+ ions on the three available crystal sites was observed. ► The instability of the silico-carnotite structure for RE=La→Sm was discussed.

In silico analysis, mapping of regulatory elements and corresponding dna-protein interaction in polyphenol oxidase gene promoter from different rice varieties

International Nuclear Information System (INIS)

Mahmood, T.; Rehman, M.; Aziz, E.

2015-01-01

Polyphenol oxidase (PPO) is an important enzyme that has positive impact regarding plant resistance against different biotic and abiotic stresses. In the present study PPO promoter from six different rice varieties was amplified and then analyzed for cis- and trans-acting elements. The study revealed a total of 79 different cis-acting regulatory elements including 11 elements restricted to only one or other variety. Among six varieties Pakhal-Basmati had highest number (5) of these elements, whereas C-622 and Rachna-Basmati have no such sequences. Rachna-Basmati, IR-36-Basmati and Kashmir- Basmati had 1, 2 and 3 unique elements, respectively. Different elementsrelated to pathogen, salt and water stresses were found, which may be helpful in controlling PPO activity according to changing environment. Moreover, HADDOCK was used to understand molecular mechanism of PPO regulation and it was found that DNA-protein interactions are stabilized by many potential hydrogen bonds. Adenine and arginine were the most reactive residues in DNA and proteins respectively.Structural comparison of different protein-DNA complexes show that even a highly conserved transcriptional factor can adopt different conformations when they contact a different DNA binding sequence, however their stable interactions depend on the number of hydrogen bonds formed and distance. (author)

Nomadic enhancers: tissue-specific cis-regulatory elements of yellow have divergent genomic positions among Drosophila species.

Directory of Open Access Journals (Sweden)

Gizem Kalay

2010-11-01

Full Text Available cis-regulatory DNA sequences known as enhancers control gene expression in space and time. They are central to metazoan development and are often responsible for changes in gene regulation that contribute to phenotypic evolution. Here, we examine the sequence, function, and genomic location of enhancers controlling tissue- and cell-type specific expression of the yellow gene in six Drosophila species. yellow is required for the production of dark pigment, and its expression has evolved largely in concert with divergent pigment patterns. Using Drosophila melanogaster as a transgenic host, we examined the expression of reporter genes in which either 5' intergenic or intronic sequences of yellow from each species controlled the expression of Green Fluorescent Protein. Surprisingly, we found that sequences controlling expression in the wing veins, as well as sequences controlling expression in epidermal cells of the abdomen, thorax, and wing, were located in different genomic regions in different species. By contrast, sequences controlling expression in bristle-associated cells were located in the intron of all species. Differences in the precise pattern of spatial expression within the developing epidermis of D. melanogaster transformants usually correlated with adult pigmentation in the species from which the cis-regulatory sequences were derived, which is consistent with cis-regulatory evolution affecting yellow expression playing a central role in Drosophila pigmentation divergence. Sequence comparisons among species favored a model in which sequential nucleotide substitutions were responsible for the observed changes in cis-regulatory architecture. Taken together, these data demonstrate frequent changes in yellow cis-regulatory architecture among Drosophila species. Similar analyses of other genes, combining in vivo functional tests of enhancer activity with in silico comparative genomics, are needed to determine whether the pattern of

In silico Assessment of Drug-like Properties of Alkaloids from Areca ...

African Journals Online (AJOL)

Purpose: To investigate in silico the drug-like properties of alkaloids (arecoline, arecaidine, guvacine, guvacoline, isoguvacine, arecolidine and homoarecoline) obtained from the fruits of Areca catechu L (areca nut). Methods: All chemical structures were re-drawn using Chemdraw Ultra 11.0. Furthermore, software including ...

Transcription regulatory networks analysis using CAGE

KAUST Repository

Tegné r, Jesper N.; Bjö rkegren, Johan L M; Ravasi, Timothy; Bajic, Vladimir

2009-01-01

and the fine interplay between regulatory proteins and the promoter structure governing the combinatorial regulation of gene expression. In this chapter we review how the CAGE data can be integrated with other measurements such as expression, physical

Extensive in silico analysis of Mimivirus coded Rab GTPase homolog suggests a possible role in virion membrane biogenesis

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Amrutraj eZade

2015-09-01

Full Text Available Rab GTPases are the key regulators of intracellular membrane trafficking in eukaryotes. Many viruses and intracellular bacterial pathogens have evolved to hijack the host Rab GTPase functions, mainly through activators and effector proteins, for their benefit. Acanthamoeba polyphaga mimivirus (APMV is one of the largest viruses and belongs to the monophyletic clade of nucleo-cytoplasmic large DNA viruses (NCLDV. The inner membrane lining is integral to the APMV virion structure. APMV assembly involves extensive host membrane modifications, like vesicle budding and fusion, leading to the formation of a membrane sheet that is incorporated into the virion. Intriguingly, APMV and all group I members of the Mimiviridae family code for a putative Rab GTPase protein. APMV is the first reported virus to code for a Rab GTPase (encoded by R214 gene. Our thorough in silico analysis of the subfamily specific (SF region of Mimiviridae Rab GTPase sequences suggests that they are related to Rab5, a member of the group II Rab GTPases, of lower eukaryotes. Because of their high divergence from the existing three isoforms, A, B and C of the Rab5-family, we suggest that Mimiviridae Rabs constitute a new isoform, Rab5D. Phylogenetic analysis indicated probable horizontal acquisition from a lower eukaryotic ancestor followed by selection and divergence. Furthermore, interaction network analysis suggests that vps34 (a Class III P13K homolog, coded by APMV L615, Atg-8 and dynamin (host proteins are recruited by APMV Rab GTPase during capsid assembly. Based on these observations, we hypothesize that APMV Rab plays a role in the acquisition of inner membrane during virion assembly.

In Vitro and In Silico Risk Assessment in Acquired Long QT Syndrome: The Devil Is in the Details

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William Lee

2017-11-01

Full Text Available Acquired long QT syndrome, mostly as a result of drug block of the Kv11. 1 potassium channel in the heart, is characterized by delayed cardiac myocyte repolarization, prolongation of the T interval on the ECG, syncope and sudden cardiac death due to the polymorphic ventricular arrhythmia Torsade de Pointes (TdP. In recent years, efforts are underway through the Comprehensive in vitro proarrhythmic assay (CiPA initiative, to develop better tests for this drug induced arrhythmia based in part on in silico simulations of pharmacological disruption of repolarization. However, drug binding to Kv11.1 is more complex than a simple binary molecular reaction, meaning simple steady state measures of potency are poor surrogates for risk. As a result, there is a plethora of mechanistic detail describing the drug/Kv11.1 interaction—such as drug binding kinetics, state preference, temperature dependence and trapping—that needs to be considered when developing in silico models for risk prediction. In addition to this, other factors, such as multichannel pharmacological profile and the nature of the ventricular cell models used in simulations also need to be considered in the search for the optimum in silico approach. Here we consider how much of mechanistic detail needs to be included for in silico models to accurately predict risk and further, how much of this detail can be retrieved from protocols that are practical to implement in high throughout screens as part of next generation of preclinical in silico drug screening approaches?

A population dynamics analysis of the interaction between adaptive regulatory T cells and antigen presenting cells.

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David Fouchet

Full Text Available BACKGROUND: Regulatory T cells are central actors in the maintenance of tolerance of self-antigens or allergens and in the regulation of the intensity of the immune response during infections by pathogens. An understanding of the network of the interaction between regulatory T cells, antigen presenting cells and effector T cells is starting to emerge. Dynamical systems analysis can help to understand the dynamical properties of an interaction network and can shed light on the different tasks that can be accomplished by a network. METHODOLOGY AND PRINCIPAL FINDINGS: We used a mathematical model to describe a interaction network of adaptive regulatory T cells, in which mature precursor T cells may differentiate into either adaptive regulatory T cells or effector T cells, depending on the activation state of the cell by which the antigen was presented. Using an equilibrium analysis of the mathematical model we show that, for some parameters, the network has two stable equilibrium states: one in which effector T cells are strongly regulated by regulatory T cells and another in which effector T cells are not regulated because the regulatory T cell population is vanishingly small. We then simulate different types of perturbations, such as the introduction of an antigen into a virgin system, and look at the state into which the system falls. We find that whether or not the interaction network switches from the regulated (tolerant state to the unregulated state depends on the strength of the antigenic stimulus and the state from which the network has been perturbed. CONCLUSION/SIGNIFICANCE: Our findings suggest that the interaction network studied in this paper plays an essential part in generating and maintaining tolerance against allergens and self-antigens.

Analysis of deterministic cyclic gene regulatory network models with delays

CERN Document Server

Ahsen, Mehmet Eren; Niculescu, Silviu-Iulian

2015-01-01

This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs.

In silico tools to aid risk assessment of endocrine disrupting chemicals

International Nuclear Information System (INIS)

Jacobs, M.N.

2004-01-01

In silico or computational tools could be used more effectively in endocrine disruptor risk assessment for prescreening potential endocrine disruptors, improving experimental in vitro screening assay design and facilitating more thorough data analyses. The in silico tools reviewed here are three-fold and include the use of: (1) nuclear receptor (NR) crystal structures and homology models to examine potential modes of ligand binding by different representative compounds; (2) multivariate principal component analyses (PCA) techniques to select best predicted cell lines for endocrine disrupting chemicals (EDC) risk assessment purposes; (3) NR quantitative structure-activity relationships (QSARs) that can be constructed from varied biological data sources, using multivariate partial least squares (PLS) techniques and specific descriptors. The cytosolic and NR examples discussed here include the Ah receptor (AhR), the human oestrogen receptor α (hERα) and the human pregnane X receptor (PXR). The varied biological data sets can be compared to give a more integrated dimension to receptor cross talk mechanisms, with further support from molecular modelling studies

CGUG: in silico proteome and genome parsing tool for the determination of "core" and unique genes in the analysis of genomes up to ca. 1.9 Mb

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Mahadevan Padmanabhan

2009-08-01

Full Text Available Abstract Background Viruses and small-genome bacteria (~2 megabases and smaller comprise a considerable population in the biosphere and are of interest to many researchers. These genomes are now sequenced at an unprecedented rate and require complementary computational tools to analyze. "CoreGenesUniqueGenes" (CGUG is an in silico genome data mining tool that determines a "core" set of genes from two to five organisms with genomes in this size range. Core and unique genes may reflect similar niches and needs, and may be used in classifying organisms. Findings CGUG is available at http://binf.gmu.edu/geneorder.html as a web-based on-the-fly tool that performs iterative BLASTP analyses using a reference genome and up to four query genomes to provide a table of genes common to these genomes. The result is an in silico display of genomes and their proteomes, allowing for further analysis. CGUG can be used for "genome annotation by homology", as demonstrated with Chlamydophila and Francisella genomes. Conclusion CGUG is used to reanalyze the ICTV-based classifications of bacteriophages, to reconfirm long-standing relationships and to explore new classifications. These genomes have been problematic in the past, due largely to horizontal gene transfers. CGUG is validated as a tool for reannotating small genome bacteria using more up-to-date annotations by similarity or homology. These serve as an entry point for wet-bench experiments to confirm the functions of these "hypothetical" and "unknown" proteins.

Ancestral regulatory circuits governing ectoderm patterning downstream of Nodal and BMP2/4 revealed by gene regulatory network analysis in an echinoderm.

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Alexandra Saudemont

2010-12-01

Full Text Available Echinoderms, which are phylogenetically related to vertebrates and produce large numbers of transparent embryos that can be experimentally manipulated, offer many advantages for the analysis of the gene regulatory networks (GRN regulating germ layer formation. During development of the sea urchin embryo, the ectoderm is the source of signals that pattern all three germ layers along the dorsal-ventral axis. How this signaling center controls patterning and morphogenesis of the embryo is not understood. Here, we report a large-scale analysis of the GRN deployed in response to the activity of this signaling center in the embryos of the Mediterranean sea urchin Paracentrotus lividus, in which studies with high spatial resolution are possible. By using a combination of in situ hybridization screening, overexpression of mRNA, recombinant ligand treatments, and morpholino-based loss-of-function studies, we identified a cohort of transcription factors and signaling molecules expressed in the ventral ectoderm, dorsal ectoderm, and interposed neurogenic ("ciliary band" region in response to the known key signaling molecules Nodal and BMP2/4 and defined the epistatic relationships between the most important genes. The resultant GRN showed a number of striking features. First, Nodal was found to be essential for the expression of all ventral and dorsal marker genes, and BMP2/4 for all dorsal genes. Second, goosecoid was identified as a central player in a regulatory sub-circuit controlling mouth formation, while tbx2/3 emerged as a critical factor for differentiation of the dorsal ectoderm. Finally, and unexpectedly, a neurogenic ectoderm regulatory circuit characterized by expression of "ciliary band" genes was triggered in the absence of TGF beta signaling. We propose a novel model for ectoderm regionalization, in which neural ectoderm is the default fate in the absence of TGF beta signaling, and suggest that the stomodeal and neural subcircuits that we

Identification of conserved regulatory elements by comparative genome analysis

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Jareborg Niclas

2003-05-01

Full Text Available Abstract Background For genes that have been successfully delineated within the human genome sequence, most regulatory sequences remain to be elucidated. The annotation and interpretation process requires additional data resources and significant improvements in computational methods for the detection of regulatory regions. One approach of growing popularity is based on the preferential conservation of functional sequences over the course of evolution by selective pressure, termed 'phylogenetic footprinting'. Mutations are more likely to be disruptive if they appear in functional sites, resulting in a measurable difference in evolution rates between functional and non-functional genomic segments. Results We have devised a flexible suite of methods for the identification and visualization of conserved transcription-factor-binding sites. The system reports those putative transcription-factor-binding sites that are both situated in conserved regions and located as pairs of sites in equivalent positions in alignments between two orthologous sequences. An underlying collection of metazoan transcription-factor-binding profiles was assembled to facilitate the study. This approach results in a significant improvement in the detection of transcription-factor-binding sites because of an increased signal-to-noise ratio, as demonstrated with two sets of promoter sequences. The method is implemented as a graphical web application, ConSite, which is at the disposal of the scientific community at http://www.phylofoot.org/. Conclusions Phylogenetic footprinting dramatically improves the predictive selectivity of bioinformatic approaches to the analysis of promoter sequences. ConSite delivers unparalleled performance using a novel database of high-quality binding models for metazoan transcription factors. With a dynamic interface, this bioinformatics tool provides broad access to promoter analysis with phylogenetic footprinting.

Immunoprotective efficacy of Acinetobacter baumannii outer membrane protein, FilF, predicted in silico as a potential vaccine candidate

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Ravinder eSingh

2016-02-01

Full Text Available Acinetobacter baumannii is emerging as a serious nosocomial pathogen with multidrug resistance that has made it difficult to cure and development of efficacious treatment against this pathogen is direly needed. This has led to investigate vaccine approach to prevent and treat A. baumannii infections. In this work, an outer membrane putative pilus assembly protein, FilF, was predicted as vaccine candidate by in silico analysis of A. baumannii proteome and was found to be conserved among the A. baumannii strains. It was cloned and expressed in E. coli BL21(DE3 and purified by Ni-NTA chromatography. Immunization with FilF generated high antibody titer (>64000 and provided 50% protection against a standardized lethal dose (10*8 CFU of A. baumannii in murine pneumonia model. FilF immunization reduced the bacterial load in lungs by 2 and 4 log cycles, 12 and 24 h post infection as compared to adjuvant control; reduced the levels of pro-inflammatory cytokines TNF-α, IL-6, IL-33, IFN-γ and IL-1β significantly and histology of lung tissue supported the data by showing considerably reduced damage and infiltration of neutrophils in lungs. These results demonstrate the in vivo validation of immunoprotective efficacy of a protein predicted as a vaccine candidate by in silico proteomic analysis and open the possibilities for exploration of a large array of uncharacterized proteins.

A study to evaluate the potential of an in silico approach for predicting dipeptidyl peptidase-IV inhibitory activity in vitro of protein hydrolysates.

Science.gov (United States)

Wang, Tzu-Yuan; Hsieh, Cheng-Hong; Hung, Chuan-Chuan; Jao, Chia-Ling; Lin, Pei-Yi; Hsieh, You-Liang; Hsu, Kuo-Chiang

2017-11-01

A total of 294 edible protein sequences and 5 commercial proteases listed in the BIOPEP database were analyzed in silico. The frequency (A), a parameter in silico described previously, was examined further to calculating the ratio of truncated peptides with Xaa-proline and/or Xaa-alanine to all peptide fragments in a protein hydrolyzed with a protease, using the BIOPEP database. Then the in vitro DPP-IV inhibitory activity was determined using the same 15 protein and protease combinations to evaluate their relationship. The result shows that A values considering the number of Xaa-proline+Xaa-alanine exhibited a strong correlation with in vitro DPP-IV inhibition rates by Pearson's correlation analysis (r=0.6993; Psilico approach is effective to predict DPP-IV inhibitory activities in vitro of protein hydrolysates. Copyright © 2017 Elsevier Ltd. All rights reserved.

MediPlEx - a tool to combine in silico & experimental gene expression profiles of the model legume Medicago truncatula

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Stutz Leonhard J

2010-10-01

Full Text Available Abstract Background Expressed Sequence Tags (ESTs are in general used to gain a first insight into gene activities from a species of interest. Subsequently, and typically based on a combination of EST and genome sequences, microarray-based expression analyses are performed for a variety of conditions. In some cases, a multitude of EST and microarray experiments are conducted for one species, covering different tissues, cell states, and cell types. Under these circumstances, the challenge arises to combine results derived from the different expression profiling strategies, with the goal to uncover novel information on the basis of the integrated datasets. Findings Using our new analysis tool, MediPlEx (MEDIcago truncatula multiPLe EXpression analysis, expression data from EST experiments, oligonucleotide microarrays and Affymetrix GeneChips® can be combined and analyzed, leading to a novel approach to integrated transcriptome analysis. We have validated our tool via the identification of a set of well-characterized AM-specific and AM-induced marker genes, identified by MediPlEx on the basis of in silico and experimental gene expression profiles from roots colonized with AM fungi. Conclusions MediPlEx offers an integrated analysis pipeline for different sets of expression data generated for the model legume Medicago truncatula. As expected, in silico and experimental gene expression data that cover the same biological condition correlate well. The collection of differentially expressed genes identified via MediPlEx provides a starting point for functional studies in plant mutants. MediPlEx can freely be used at http://www.cebitec.uni-bielefeld.de/mediplex.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks

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Lepoivre Cyrille

2012-01-01

Full Text Available Abstract Background Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. Results We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices, (ii potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii regulatory interactions curated from the literature, (iv predicted post-transcriptional regulation by micro-RNA, (v protein kinase-substrate interactions and (vi physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration

Evaluation of transport safety analysis processes of radioactive material performed by a regulatory body

International Nuclear Information System (INIS)

Mattar, Patricia Morais

2017-01-01

Radioactive substances have many beneficial applications, ranging from power generation to uses in medicine, industry and agriculture. As a rule, they are produced in different places from where they are used, needing to be transported. In order for transport to take place safely and efficiently, national and international standards must be complied with. This research aims to assess the safety analysis processes for the transport of radioactive material carried out by the regulatory body in Brazil, from the point of view of their compliance with the International Atomic Energy Agency (IAEA) standards. The self-assessment methodology named SARIS, developed by the AIEA, was used. The following steps were carried out: evaluation of the Diagnosis and Processes Mapping; responses to the SARIS Question Set and complementary questions; SWOT analysis; interviews with stakeholders and evaluation of a TranSAS mission conducted by the IAEA in 2002. Considering only SARIS questions, processes are 100% adherent. The deepening of the research, however, led to the development of twenty-two improvement proposals and the identification of nine good practices. The results showed that the safety analysis processes of the transport of radioactive material are being carried out in a structured, safe and reliable way but also that there is much opportunity for improvement. The formulation of an action plan, based on the presented proposals, can bring to the regulatory body many benefits. This would be an important step towards convening an external evaluation, providing greater reliability and transparency to the regulatory body´s processes. (author)

In silico profiling of miRNAs and their target polymorphisms in ...

African Journals Online (AJOL)

To assess, whether miRNA target SNPs are implicated in leukemia associated genes, we conducted an in silico approach along with the availability of publicly available web based tools for miRNA prediction and comprehensive genomic databases of SNPs. In this in-depth report, we attempted to use two computational ...

From Double-Four-Ring Germanosilicates to New Zeolites: In Silico Investigation

Czech Academy of Sciences Publication Activity Database

Trachta, Michal; Bludský, Ota; Čejka, Jiří; Morris, R. E.; Nachtigall, P.

2014-01-01

Roč. 15, č. 14 (2014), s. 2972-2976 ISSN 1439-4235 R&D Projects: GA ČR GBP106/12/G015 Institutional support: RVO:61388963 ; RVO:61388955 Keywords : density functional calculations * in silico studies * structure * synthesis * zeolites Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 3.419, year: 2014

Identification and molecular docking study of novel angiotensin-converting enzyme inhibitory peptides from Salmo salar using in silico methods.

Science.gov (United States)

Yu, Zhipeng; Chen, Yang; Zhao, Wenzhu; Li, Jianrong; Liu, Jingbo; Chen, Feng

2018-01-25

In order to circumvent some challenges of the classical approach, the in silico method has been applied to the discovery of angiotensin-converting enzyme (ACE) inhibitory peptides from food proteins. In this study, some convenient and efficient in silico tools were utilized to identify novel ACE inhibitory peptides from Salmo salar. Collagen from Salmo salar was digested in silico into hundreds of peptides. Results revealed that tetrapeptides PGAR and IGPR showed potent ACE inhibitory activity, with IC 50 values of 0.598 ± 0.12 and 0.43 ± 0.09 mmol L -1 , respectively. The molecular docking result showed that PGAR and IGPR interact with ACE mostly via hydrogen bonds and attractive charge. Peptide IGPR interacts with Zn + at the ACE active site, showing high inhibitory activity. Interaction with Zn + in ACE may lead to higher inhibitory activity of peptides, and Pi interactions may promote the effect of peptides on ACE. The in silico method can be an effective method to predict potent ACE inhibitory peptides from food proteins. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Analysis of 30 putative BRCA1 splicing mutations in hereditary breast and ovarian cancer families identifies exonic splice site mutations that escape in silico prediction.

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Barbara Wappenschmidt

Full Text Available Screening for pathogenic mutations in breast and ovarian cancer genes such as BRCA1/2, CHEK2 and RAD51C is common practice for individuals from high-risk families. However, test results may be ambiguous due to the presence of unclassified variants (UCV in the concurrent absence of clearly cancer-predisposing mutations. Especially the presence of intronic or exonic variants within these genes that possibly affect proper pre-mRNA processing poses a challenge as their functional implications are not immediately apparent. Therefore, it appears necessary to characterize potential splicing UCV and to develop appropriate classification tools. We investigated 30 distinct BRCA1 variants, both intronic and exonic, regarding their spliceogenic potential by commonly used in silico prediction algorithms (HSF, MaxEntScan along with in vitro transcript analyses. A total of 25 variants were identified spliceogenic, either causing/enhancing exon skipping or activation of cryptic splice sites, or both. Except from a single intronic variant causing minor effects on BRCA1 pre-mRNA processing in our analyses, 23 out of 24 intronic variants were correctly predicted by MaxEntScan, while HSF was less accurate in this cohort. Among the 6 exonic variants analyzed, 4 severely impair correct pre-mRNA processing, while the remaining two have partial effects. In contrast to the intronic alterations investigated, only half of the spliceogenic exonic variants were correctly predicted by HSF and/or MaxEntScan. These data support the idea that exonic splicing mutations are commonly disease-causing and concurrently prone to escape in silico prediction, hence necessitating experimental in vitro splicing analysis.

Alternative approaches for identifying acute systemic toxicity: Moving from research to regulatory testing.

Science.gov (United States)

Hamm, Jon; Sullivan, Kristie; Clippinger, Amy J; Strickland, Judy; Bell, Shannon; Bhhatarai, Barun; Blaauboer, Bas; Casey, Warren; Dorman, David; Forsby, Anna; Garcia-Reyero, Natàlia; Gehen, Sean; Graepel, Rabea; Hotchkiss, Jon; Lowit, Anna; Matheson, Joanna; Reaves, Elissa; Scarano, Louis; Sprankle, Catherine; Tunkel, Jay; Wilson, Dan; Xia, Menghang; Zhu, Hao; Allen, David

2017-06-01

Acute systemic toxicity testing provides the basis for hazard labeling and risk management of chemicals. A number of international efforts have been directed at identifying non-animal alternatives for in vivo acute systemic toxicity tests. A September 2015 workshop, Alternative Approaches for Identifying Acute Systemic Toxicity: Moving from Research to Regulatory Testing, reviewed the state-of-the-science of non-animal alternatives for this testing and explored ways to facilitate implementation of alternatives. Workshop attendees included representatives from international regulatory agencies, academia, nongovernmental organizations, and industry. Resources identified as necessary for meaningful progress in implementing alternatives included compiling and making available high-quality reference data, training on use and interpretation of in vitro and in silico approaches, and global harmonization of testing requirements. Attendees particularly noted the need to characterize variability in reference data to evaluate new approaches. They also noted the importance of understanding the mechanisms of acute toxicity, which could be facilitated by the development of adverse outcome pathways. Workshop breakout groups explored different approaches to reducing or replacing animal use for acute toxicity testing, with each group crafting a roadmap and strategy to accomplish near-term progress. The workshop steering committee has organized efforts to implement the recommendations of the workshop participants. Copyright © 2017 Elsevier Ltd. All rights reserved.

In Silico Mechanistic Profiling to Probe Small Molecule Binding to Sulfotransferases

Science.gov (United States)

Martiny, Virginie Y.; Carbonell, Pablo; Lagorce, David; Villoutreix, Bruno O.; Moroy, Gautier; Miteva, Maria A.

2013-01-01

Drug metabolizing enzymes play a key role in the metabolism, elimination and detoxification of xenobiotics, drugs and endogenous molecules. While their principal role is to detoxify organisms by modifying compounds, such as pollutants or drugs, for a rapid excretion, in some cases they render their substrates more toxic thereby inducing severe side effects and adverse drug reactions, or their inhibition can lead to drug–drug interactions. We focus on sulfotransferases (SULTs), a family of phase II metabolizing enzymes, acting on a large number of drugs and hormones and showing important structural flexibility. Here we report a novel in silico structure-based approach to probe ligand binding to SULTs. We explored the flexibility of SULTs by molecular dynamics (MD) simulations in order to identify the most suitable multiple receptor conformations for ligand binding prediction. Then, we employed structure-based docking-scoring approach to predict ligand binding and finally we combined the predicted interaction energies by using a QSAR methodology. The results showed that our protocol successfully prioritizes potent binders for the studied here SULT1 isoforms, and give new insights on specific molecular mechanisms for diverse ligands’ binding related to their binding sites plasticity. Our best QSAR models, introducing predicted protein-ligand interaction energy by using docking, showed accuracy of 67.28%, 78.00% and 75.46%, for the isoforms SULT1A1, SULT1A3 and SULT1E1, respectively. To the best of our knowledge our protocol is the first in silico structure-based approach consisting of a protein-ligand interaction analysis at atomic level that considers both ligand and enzyme flexibility, along with a QSAR approach, to identify small molecules that can interact with II phase dug metabolizing enzymes. PMID:24039991

In silico mechanistic profiling to probe small molecule binding to sulfotransferases.

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Virginie Y Martiny

Full Text Available Drug metabolizing enzymes play a key role in the metabolism, elimination and detoxification of xenobiotics, drugs and endogenous molecules. While their principal role is to detoxify organisms by modifying compounds, such as pollutants or drugs, for a rapid excretion, in some cases they render their substrates more toxic thereby inducing severe side effects and adverse drug reactions, or their inhibition can lead to drug-drug interactions. We focus on sulfotransferases (SULTs, a family of phase II metabolizing enzymes, acting on a large number of drugs and hormones and showing important structural flexibility. Here we report a novel in silico structure-based approach to probe ligand binding to SULTs. We explored the flexibility of SULTs by molecular dynamics (MD simulations in order to identify the most suitable multiple receptor conformations for ligand binding prediction. Then, we employed structure-based docking-scoring approach to predict ligand binding and finally we combined the predicted interaction energies by using a QSAR methodology. The results showed that our protocol successfully prioritizes potent binders for the studied here SULT1 isoforms, and give new insights on specific molecular mechanisms for diverse ligands' binding related to their binding sites plasticity. Our best QSAR models, introducing predicted protein-ligand interaction energy by using docking, showed accuracy of 67.28%, 78.00% and 75.46%, for the isoforms SULT1A1, SULT1A3 and SULT1E1, respectively. To the best of our knowledge our protocol is the first in silico structure-based approach consisting of a protein-ligand interaction analysis at atomic level that considers both ligand and enzyme flexibility, along with a QSAR approach, to identify small molecules that can interact with II phase dug metabolizing enzymes.

Assessment of predictivity of volatile organic compounds carcinogenicity and mutagenicity by freeware in silico models.

Science.gov (United States)

Guerra, Lília Ribeiro; de Souza, Alessandra Mendonça Teles; Côrtes, Juliana Alves; Lione, Viviane de Oliveira Freitas; Castro, Helena Carla; Alves, Gutemberg Gomes

2017-12-01

The application of in silico methods is increasing on toxicological risk prediction for human and environmental health. This work aimed to evaluate the performance of three in silico freeware models (OSIRIS v.2.0, LAZAR, and Toxtree) on the prediction of carcinogenicity and mutagenicity of thirty-eight volatile organic compounds (VOC) related to chemical risk assessment for occupational exposure. Theoretical data were compared with assessments available in international databases. Confusion matrices and ROC curves were used to evaluate the sensitivity, specificity, and accuracy of each model. All three models (OSIRIS, LAZAR and Toxtree) were able to identify VOC with a potential carcinogenicity or mutagenicity risk for humans, however presenting differences concerning the specificity, sensitivity, and accuracy. The best predictive performances were found for OSIRIS and LAZAR for carcinogenicity and OSIRIS for mutagenicity, as these softwares presented a combination of negative predictive power and lower risk of false positives (high specificity) for those endpoints. The heterogeneity of results found with different softwares reinforce the importance of using a combination of in silico models to occupational toxicological risk assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

Comprehensive in silico prediction and analysis of chlamydial outer membrane proteins reflects evolution and life style of the Chlamydiae

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Myers Garry

2009-12-01

Full Text Available Abstract Background Chlamydiae are obligate intracellular bacteria comprising some of the most important bacterial pathogens of animals and humans. Although chlamydial outer membrane proteins play a key role for attachment to and entry into host cells, only few have been described so far. We developed a comprehensive, multiphasic in silico approach, including the calculation of clusters of orthologues, to predict outer membrane proteins using conservative criteria. We tested this approach using Escherichia coli (positive control and Bacillus subtilis (negative control, and applied it to five chlamydial species; Chlamydia trachomatis, Chlamydia muridarum, Chlamydia (a.k.a. Chlamydophila pneumoniae, Chlamydia (a.k.a. Chlamydophila caviae, and Protochlamydia amoebophila. Results In total, 312 chlamydial outer membrane proteins and lipoproteins in 88 orthologous clusters were identified, including 238 proteins not previously recognized to be located in the outer membrane. Analysis of their taxonomic distribution revealed an evolutionary conservation among Chlamydiae, Verrucomicrobia, Lentisphaerae and Planctomycetes as well as lifestyle-dependent conservation of the chlamydial outer membrane protein composition. Conclusion This analysis suggested a correlation between the outer membrane protein composition and the host range of chlamydiae and revealed a common set of outer membrane proteins shared by these intracellular bacteria. The collection of predicted chlamydial outer membrane proteins is available at the online database pCOMP http://www.microbial-ecology.net/pcomp and might provide future guidance in the quest for anti-chlamydial vaccines.

In vitro and in silico Approaches to the Identification of New Compounds with Antibacterial Profile

Directory of Open Access Journals (Sweden)

Carlos R. Rodrigues

2013-06-01

Full Text Available The emergence of multidrug-resistant bacterial strains is a world problem that increases the need for new and more effective antimicrobials. On that purpose, derivatives of cyclic systems may serve as new leads for discovering new active molecules. In this work we evaluated the antibacterial profile of 243 molecules derived from the systems thienopyridine, pyrazolopiridine, quinolone, chalcone, hydrazone and lapachone against Gram-positive and Gram-negative susceptible and multiresistant strains also comparing them with antibiotics of clinical use. Our results showed that among the 243 molecules tested, only eight derivatives were active with promissing MIC values (2-64mg/mL. Our theoretical in silico analysis showed that all active compounds fulfilled Lipinski rule of five (molecular weight = 344.37–409.24, clogP = 3.15–4.11, nHBA = 6–7, and nHBD = 2, similarly to commercial drugs as well as presented better druglikeness values (from -3.68 to 0.12 than chloramphenicol (-4.61 and linezolid (-4.08. Most of the active derivatives presented a low in silico toxicity risk profile, similar to oxacillin, ampicillin, and penicillin G, and even lower than that observed for chloramphenicol and linezolid. Theoretically HOMO and the electrostatic protential distribution may be contributing for this safer profile. This study used computacional tools and may help to deal with an important world health problem.

Genes co-regulated with LBD16 in nematode feeding sites inferred from in silico analysis show similarities to regulatory circuits mediated by the auxin/cytokinin balance in Arabidopsis.

Science.gov (United States)

Cabrera, Javier; Fenoll, Carmen; Escobar, Carolina

2015-01-01

Plant endoparasitic nematodes, root-knot and cyst nematodes (RKNs and CNs) induce within the root vascular cylinder transfer cells used for nourishing, termed giant cells (GCs) and syncytia. Understanding the molecular mechanisms behind this process is essential to develop tools for nematode control. Based on the crucial role in gall development of LBD16, also a key component of the auxin pathway leading to the divisions in the xylem pole pericycle during lateral root (LR) formation, we investigated genes co-regulated with LBD16 in different transcriptomes and analyzed their similarities and differences with those of RKNs and CNs feeding sites (FS). This analysis confirmed LBD16 and its co-regulated genes, integrated in signaling cascades mediated by auxins during LR and callus formation, as a particular feature of RKN-FS distinct to CNs. However, LBD16, and its positively co-regulated genes, were repressed in syncytia, suggesting a selective down- regulation of the LBD16 auxin mediated pathways in CNs-FS. Interestingly, cytokinin-induced genes are enriched in syncytia and we encountered similarities between the transcriptome of shoot regeneration from callus, modulated by cytokinins, and that of syncytia. These findings establish differences in the regulatory networks leading to both FS formation, probably modulated by the auxin/cytokinin balance.

In silico approach to identification of a novel gene responsive to ...

African Journals Online (AJOL)

Submergence is one of the major constraints to rice production. Bioinformatics approach has been widely used to identify candidate genes on many biological aspects. In the present study, a novel gene involved in submergence stress in rice, Os07g47670 was identified by in silico approach. The amino acid sequence of ...

Methodology for the Systematic Assessment of the Regulatory Competence Needs (SARCoN) for Regulatory Bodies of Nuclear Installations

International Nuclear Information System (INIS)

2015-03-01

A regulatory body’s competence is dependent, among other things, on the competence of its staff. A necessary, but not sufficient, condition for a regulatory body to be competent is that its staff can perform the tasks related to the functions of the regulatory body. In 2001, the IAEA published TECDOC 1254, Training the Staff of the Regulatory Body for Nuclear Facilities: A Competency Framework, which examines the manner in which the recognized regulatory functions of a nuclear regulatory body results in competence needs. Using the internationally recognized systematic approach to training, TECDOC 1254 provides a framework for regulatory bodies for managing training and developing, and maintaining the competence of its staff. It has been successfully used by many regulatory bodies all over the world, including States embarking on a nuclear power programme. The IAEA has also introduced a methodology and an assessment tool — Guidelines for Systematic Assessment of Regulatory Competence Needs (SARCoN) — which provides practical guidance on analysing the training and development needs of a regulatory body and, through a gap analysis, guidance on establishing competence needs and how to meet them. In 2013, the IAEA published Safety Reports Series No. 79, Managing Regulatory Body Competence, which provides generic guidance based on IAEA safety requirements in the development of a competence management system within a regulatory body’s integrated management system. An appendix in the Safety Report deals with the special case of building up the competence of regulatory bodies as part of the overall process of establishing an embarking State’s regulatory system. This publication provides guidance for the analysis of required and existing competences to identify those required by the regulatory body to perform its functions and therefore associated needs for acquiring competences. Hence, it is equally applicable to the needs of States embarking on nuclear power

New families of human regulatory RNA structures identified by comparative analysis of vertebrate genomes.

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Parker, Brian J; Moltke, Ida; Roth, Adam; Washietl, Stefan; Wen, Jiayu; Kellis, Manolis; Breaker, Ronald; Pedersen, Jakob Skou

2011-11-01

Regulatory RNA structures are often members of families with multiple paralogous instances across the genome. Family members share functional and structural properties, which allow them to be studied as a whole, facilitating both bioinformatic and experimental characterization. We have developed a comparative method, EvoFam, for genome-wide identification of families of regulatory RNA structures, based on primary sequence and secondary structure similarity. We apply EvoFam to a 41-way genomic vertebrate alignment. Genome-wide, we identify 220 human, high-confidence families outside protein-coding regions comprising 725 individual structures, including 48 families with known structural RNA elements. Known families identified include both noncoding RNAs, e.g., miRNAs and the recently identified MALAT1/MEN β lincRNA family; and cis-regulatory structures, e.g., iron-responsive elements. We also identify tens of new families supported by strong evolutionary evidence and other statistical evidence, such as GO term enrichments. For some of these, detailed analysis has led to the formulation of specific functional hypotheses. Examples include two hypothesized auto-regulatory feedback mechanisms: one involving six long hairpins in the 3'-UTR of MAT2A, a key metabolic gene that produces the primary human methyl donor S-adenosylmethionine; the other involving a tRNA-like structure in the intron of the tRNA maturation gene POP1. We experimentally validate the predicted MAT2A structures. Finally, we identify potential new regulatory networks, including large families of short hairpins enriched in immunity-related genes, e.g., TNF, FOS, and CTLA4, which include known transcript destabilizing elements. Our findings exemplify the diversity of post-transcriptional regulation and provide a resource for further characterization of new regulatory mechanisms and families of noncoding RNAs.

Data Quality Objectives for Regulatory Requirements for Hazardous and Radioactive Air Emissions Sampling and Analysis

International Nuclear Information System (INIS)

MULKEY, C.H.

1999-01-01

This document describes the results of the data quality objective (DQO) process undertaken to define data needs for state and federal requirements associated with toxic, hazardous, and/or radiological air emissions under the jurisdiction of the River Protection Project (RPP). Hereafter, this document is referred to as the Air DQO. The primary drivers for characterization under this DQO are the regulatory requirements pursuant to Washington State regulations, that may require sampling and analysis. The federal regulations concerning air emissions are incorporated into the Washington State regulations. Data needs exist for nonradioactive and radioactive waste constituents and characteristics as identified through the DQO process described in this document. The purpose is to identify current data needs for complying with regulatory drivers for the measurement of air emissions from RPP facilities in support of air permitting. These drivers include best management practices; similar analyses may have more than one regulatory driver. This document should not be used for determining overall compliance with regulations because the regulations are in constant change, and this document may not reflect the latest regulatory requirements. Regulatory requirements are also expected to change as various permits are issued. Data needs require samples for both radionuclides and nonradionuclide analytes of air emissions from tanks and stored waste containers. The collection of data is to support environmental permitting and compliance, not for health and safety issues

Simulating clinical studies of the glucoregulatory system: in vivo meets in silico

DEFF Research Database (Denmark)

Wendt, Sabrina Lyngbye; Ranjan, Ajenthen; Møller, Jan Kloppenborg

metabolism at varying ambient insulin levels. The report compares in vivo and in silico results head-to-head, and discusses similarities and differences. We design and simulate simple studies to emphasize the implications of some glucoregulatory dynamics which are ignored in most previous clinical studies...

In Silico Functional Networks Identified in Fish Nucleated Red Blood Cells by Means of Transcriptomic and Proteomic Profiling.

Science.gov (United States)

Puente-Marin, Sara; Nombela, Iván; Ciordia, Sergio; Mena, María Carmen; Chico, Verónica; Coll, Julio; Ortega-Villaizan, María Del Mar

2018-04-09

Nucleated red blood cells (RBCs) of fish have, in the last decade, been implicated in several immune-related functions, such as antiviral response, phagocytosis or cytokine-mediated signaling. RNA-sequencing (RNA-seq) and label-free shotgun proteomic analyses were carried out for in silico functional pathway profiling of rainbow trout RBCs. For RNA-seq, a de novo assembly was conducted, in order to create a transcriptome database for RBCs. For proteome profiling, we developed a proteomic method that combined: (a) fractionation into cytosolic and membrane fractions, (b) hemoglobin removal of the cytosolic fraction, (c) protein digestion, and (d) a novel step with pH reversed-phase peptide fractionation and final Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometric (LC ESI-MS/MS) analysis of each fraction. Combined transcriptome- and proteome- sequencing data identified, in silico, novel and striking immune functional networks for rainbow trout nucleated RBCs, which are mainly linked to innate and adaptive immunity. Functional pathways related to regulation of hematopoietic cell differentiation, antigen presentation via major histocompatibility complex class II (MHCII), leukocyte differentiation and regulation of leukocyte activation were identified. These preliminary findings further implicate nucleated RBCs in immune function, such as antigen presentation and leukocyte activation.

In-silico analysis of amotosalen hydrochloride binding to CD-61 of platelets

International Nuclear Information System (INIS)

Chaudhary, H.T.

2016-01-01

To determine the docking of Amotosalen hydrochloride (AH) at CD-61 of platelets, and to suggest the cause of bleeding in AH treated platelets transfusion. Study Design: Descriptive study. Place and Duration of Study: Medical College, Taif University, Taif, Saudi Arabia, from October 2014 to May 2015. Methodology: The study was carried out in-silico. PDB (protein data bank) code of Tirofiban bound to CD-61 was 2vdm. CD-61 was docked with Tirofiban using online docking tools, i.e. Patchdock and Firedock. Then, Amotosalen hydrochloride and CD-61 were also docked. Best docking poses to active sites of 2vdm were found. Ligplot of interactions of ligands and CD-61 were obtained. Then comparison of hydrogen bonds, hydrogen bond lengths, and hydrophobic bonds of 2vdm molecule and best poses of docking results were done. Patchdock and Firedock results of best poses were also analysed using SPSS version 16. Results: More amino acids were involved in hydrogen and hydrophobic bonds in Patchdock and Firedock docking of Amotosalen hydrochloride with CD-61 than Patchdock and Firedock docking of CD-61 with Tirofiban. The binding energy was more in latter than former. Conclusion: Amotosalen hydrochloride binds to the active site of CD-61 with weaker binding force. Haemorrhage seen in Amotosalen hydrochloride-treated platelets might be due to binding of Amotosalen hydrochloride to CD-61. (author)

Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity.

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Passini, Elisa; Britton, Oliver J; Lu, Hua Rong; Rohrbacher, Jutta; Hermans, An N; Gallacher, David J; Greig, Robert J H; Bueno-Orovio, Alfonso; Rodriguez, Blanca

2017-01-01

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC 50 /Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca 2+ -transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca 2+ /late Na + currents and Na + /Ca 2+ -exchanger, reduced Na + /K + -pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density

Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity

Directory of Open Access Journals (Sweden)

Elisa Passini

2017-09-01

Full Text Available Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC50/Hill coefficient. Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca2+-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs. Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca2+/late Na+ currents and Na+/Ca2+-exchanger, reduced Na+/K+-pump are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density

Accessing biological actions of Ganoderma secondary metabolites by in silico profiling

Science.gov (United States)

Grienke, Ulrike; Kaserer, Teresa; Pfluger, Florian; Mair, Christina E.; Langer, Thierry; Schuster, Daniela; Rollinger, Judith M.

2016-01-01

The species complex around the medicinal fungus Ganoderma lucidum Karst. (Ganodermataceae) is widely known in traditional medicines as well as in modern applications such as functional food or nutraceuticals. A considerable number of publications reflects its abundance and variety in biological actions either provoked by primary metabolites such as polysaccharides or secondary metabolites such as lanostane-type triterpenes. However, due to this remarkable amount of information, a rationalization of the individual Ganoderma constituents to biological actions on a molecular level is quite challenging. To overcome this issue, a database was generated containing meta-information, i.e. chemical structures and biological actions of hitherto identified Ganoderma constituents (279). This was followed by a computational approach subjecting this 3D multi-conformational molecular dataset to in silico parallel screening against an in-house collection of validated structure- and ligand-based 3D pharmacophore models. The predictive power of the evaluated in silico tools and hints from traditional application fields served as criteria for the model selection. Thus, we focused on representative druggable targets in the field of viral infections (5) and diseases related to the metabolic syndrome (22). The results obtained from this in silico approach were compared to bioactivity data available from the literature to distinguish between true and false positives or negatives. 89 and 197 Ganoderma compounds were predicted as ligands of at least one of the selected pharmacological targets in the antiviral and the metabolic syndrome screening, respectively. Among them only a minority of individual compounds (around 10%) has ever been investigated on these targets or for the associated biological activity. Accordingly, this study discloses putative ligand target interactions for a plethora of Ganoderma constituents in the empirically manifested field of viral diseases and metabolic

Understanding the lid movements of LolA in Escherichia coli using molecular dynamics simulation and in silico point mutation.

Science.gov (United States)

Murahari, Priyadarshini; Anishetty, Sharmila; Pennathur, Gautam

2013-12-01

The Lol system in Escherichia coli is involved in localization of lipoproteins and hence is essential for growth of the organism. LolA is a periplasmic chaperone that binds to outer-membrane specific lipoproteins and transports them from inner membrane to outer membrane through LolB. The hydrophobic lipid-binding cavity of LolA consists of α-helices which act as a lid in regulating the transfer of lipoproteins from LolA to LolB. The current study aims to investigate the structural changes observed in LolA during the transition from open to closed conformation in the absence of lipoprotein. Molecular dynamics (MD) simulations were carried out for two LolA crystal structures; LolA(R43L), and in silico mutated MsL43R for a simulation time of 50 ns in water environment. We have performed an in silico point mutation of leucine to arginine in MsL43R to evaluate the importance of arginine to induce structural changes and impact the stability of protein structure. A complete dynamic analysis of open to closed conformation reveals the existence of two distinct levels; closing of lid and closing of entrance of hydrophobic cavity. Our analysis reveals that the structural flexibility of LolA is an important factor for its role as a periplasmic chaperone. Copyright © 2013 Elsevier Ltd. All rights reserved.

76 FR 28102 - Notice of Issuance of Regulatory Guide

Science.gov (United States)

2011-05-13

..., Probabilistic Risk Assessment Branch, Division of Risk Analysis, Office of Nuclear Regulatory Research, U.S... results of risk analyses are used to help justify regulatory action. As such, the principles, process, and... NUCLEAR REGULATORY COMMISSION [NRC-2009-0385] Notice of Issuance of Regulatory Guide AGENCY...

Discovery of potential cholesterol esterase inhibitors using in silico docking studies

Directory of Open Access Journals (Sweden)

Thirumalaisamy Sivashanmugam

2013-08-01

Full Text Available New drug discovery is considered broadly in terms of two kinds of investiga-tional activities such as exploration and exploitation. This study deals with the evaluation of the cholesterol esterase inhibitory activity of flavonoids apigenin, biochanin, curcumin, diosmetin, epipervilline, glycitein, okanin, rhamnazin and tangeritin using in silico docking studies. In silico docking studies were carried out using AutoDock 4.2, based on the Lamarckian genetic algorithm principle. The results showed that all the selected flavonoids showed binding energy ranging between -7.08 kcal/mol to -5.64 kcal/mol when compared with that of the standard compound gallic acid (-4.11 kcal/mol. Intermolecular energy (-9.13 kcal/mol to -7.09 kcal/mol and inhibition constant (6.48 µM to 73.18 µM of the ligands also coincide with the binding energy. All the selected flavonoids contributed cholesterol esterase inhibitory activity, these molecular docking analyses could lead to the further develop-ment of potent cholesterol esterase inhibitors for the treatment of obesity.

In silico data analyses of the hotspot mutations of CHM gene in choroideremia disease

Directory of Open Access Journals (Sweden)

Saber Imani

2018-06-01

Full Text Available This data article provides compelling computational analysis of the hotspot CHM gene mutations that contribute to the progressive causativeness and susceptibility of Choroideremia in patients. We performed structural and molecular dynamics (MD simulation analysis on abnormal states of the CHM protein caused by deleterious and disease-causing hotspot mutant forms of CHM: S89C, E177K, and V529H. Within 40 ns, MD simulation time composed of the E177K mutant shows conformational alteration especially in several parts of the variant. Mathematically, we applied eigenvector analysis to determine the modes of flexibility and atomic positional fluctuations that contribute significantly to the overall motion of the CHM protein in terms of structural alteration, free energy landscapes (FEL, entropy, enthalpy, and principal component analysis (PCA.The data described here are related to the article entitled “Molecular Genetics Characterization and Homology Modeling of the CHM Gene Mutation: A study on Its Association with Choroideremia” (Imani et al., 2018 [1]. Keywords: In silico, Choroideremia, Rab escort protein 1, Molecular dynamic simulation

In silico method for modelling metabolism and gene product expression at genome scale

Energy Technology Data Exchange (ETDEWEB)

Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.

2012-07-03

Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

In Silico Studies of Mammalian δ-ALAD Interactions with Selenides and Selenoxides.

Science.gov (United States)

Andrei Nogara, Pablo; Batista Teixeira Rocha, João

2018-04-01

Previous studies have shown that the mammalian δ-aminolevulinic acid dehydratase (δ-ALAD) is inhibited by selenides and selenoxides, which can involve thiol oxidation. However, the precise molecular interaction of selenides and selenoxides with the active center of the enzyme is unknown. Here, we try to explain the interaction of selenides and the respective selenoxides with human δ-ALAD by in silico molecular docking. The in silico data indicated that Se atoms of selenoxides have higher electrophilic character than their respective selenides. Further, the presence of oxygen increased the interaction of selenoxides with the δ-ALAD active site by O…Zn coordination. The interaction of S atom from Cys124 with the Se atom indicated the importance of the nucleophilic attack of the enzyme thiolate to the organoselenium molecules. These observations help us to understand the interaction of target proteins with organoselenium compounds. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Legal principles of regulatory administration and nuclear safety regulation

Energy Technology Data Exchange (ETDEWEB)

Lee, Kyeong Hui; Cheong, Sang Kee [Hannam Univ., Taejon (Korea, Republic of)

2000-12-15

This research presents a critical analysis and evaluation of principles of administrative laws in order to provide framework of structural reform on the nuclear safety regulation system. The focus of this analysis and evaluation is centered around the area of origin of regulatory administrative laws; authorities of regulation; procedures of regulatory actions; regulatory enforcement; and administrative relief system. In chapter 2 the concept of regulatory administration is analysed. Chapter 3 identifies the origin of regulatory administration and the principles of administration laws. It also examines legal nature of the nuclear safety standard. In relation to regulatory authorities. Chapter 4 identifies role and responsibility of administration authorities and institutions. It also examines fundamental principles of delegation of power. Then the chapter discusses the nuclear safety regulation authorities and their roles and responsibilities. Chapter 5 classifies and examines regulatory administration actions. Chapter 6 evaluates enforcement measure for effectiveness of regulation. Finally, chapter 7 discusses the administrative relief system for reviewing unreasonable regulatory acts.

In silico characterization of boron transporter (BOR1 protein sequences in Poaceae species

Directory of Open Access Journals (Sweden)

Ertuğrul Filiz

2013-01-01

Full Text Available Boron (B is essential for the plant growth and development, and its primary function is connected with formation of the cell wall. Moreover, boron toxicity is a shared problem in semiarid and arid regions. In this study, boron transporter protein (BOR1 sequences from some Poaceae species (Hordeum vulgare subsp. vulgare, Zea mays, Brachypodium distachyon, Oryza sativa subsp. japonica, Oryza sativa subsp. indica, Sorghum bicolor, Triticum aestivum were evaluated by bioinformatics tools. Physicochemical analyses revealed that most of BOR1 proteins were basic character and had generally aliphatic amino acids. Analysis of the domains showed that transmembrane domains were identified constantly and three motifs were detected with 50 amino acids length. Also, the motif SPNPWEPGSYDHWTVAKDMFNVPPAYIFGAFIPATMVAGLYYFDHSVASQ was found most frequently with 25 repeats. The phylogenetic tree showed divergence into two main clusters. B. distachyon species were clustered separately. Finally, this study contributes to the new BOR1 protein characterization in grasses and create scientific base for in silico analysis in future.

Discovery of DPP IV inhibitors by pharmacophore modeling and QSAR analysis followed by in silico screening.

Science.gov (United States)

Al-Masri, Ihab M; Mohammad, Mohammad K; Taha, Mutasem O

2008-11-01

Dipeptidyl peptidase IV (DPP IV) deactivates the natural hypoglycemic incretin hormones. Inhibition of this enzyme should restore glucose homeostasis in diabetic patients making it an attractive target for the development of new antidiabetic drugs. With this in mind, the pharmacophoric space of DPP IV was explored using a set of 358 known inhibitors. Thereafter, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and physicochemical descriptors that yield selfconsistent and predictive quantitative structure-activity relationships (QSAR) (r(2) (287)=0.74, F-statistic=44.5, r(2) (BS)=0.74, r(2) (LOO)=0.69, r(2) (PRESS) against 71 external testing inhibitors=0.51). Two orthogonal pharmacophores (of cross-correlation r(2)=0.23) emerged in the QSAR equation suggesting the existence of at least two distinct binding modes accessible to ligands within the DPP IV binding pocket. Docking experiments supported the binding modes suggested by QSAR/pharmacophore analyses. The validity of the QSAR equation and the associated pharmacophore models were established by the identification of new low-micromolar anti-DPP IV leads retrieved by in silico screening. One of our interesting potent anti-DPP IV hits is the fluoroquinolone gemifloxacin (IC(50)=1.12 muM). The fact that gemifloxacin was recently reported to potently inhibit the prodiabetic target glycogen synthase kinase 3beta (GSK-3beta) suggests that gemifloxacin is an excellent lead for the development of novel dual antidiabetic inhibitors against DPP IV and GSK-3beta.

Evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines.

Science.gov (United States)

Ghosh, Rajarshi; Oak, Ninad; Plon, Sharon E

2017-11-28

The American College of Medical Genetics and American College of Pathologists (ACMG/AMP) variant classification guidelines for clinical reporting are widely used in diagnostic laboratories for variant interpretation. The ACMG/AMP guidelines recommend complete concordance of predictions among all in silico algorithms used without specifying the number or types of algorithms. The subjective nature of this recommendation contributes to discordance of variant classification among clinical laboratories and prevents definitive classification of variants. Using 14,819 benign or pathogenic missense variants from the ClinVar database, we compared performance of 25 algorithms across datasets differing in distinct biological and technical variables. There was wide variability in concordance among different combinations of algorithms with particularly low concordance for benign variants. We also identify a previously unreported source of error in variant interpretation (false concordance) where concordant in silico predictions are opposite to the evidence provided by other sources. We identified recently developed algorithms with high predictive power and robust to variables such as disease mechanism, gene constraint, and mode of inheritance, although poorer performing algorithms are more frequently used based on review of the clinical genetics literature (2011-2017). Our analyses identify algorithms with high performance characteristics independent of underlying disease mechanisms. We describe combinations of algorithms with increased concordance that should improve in silico algorithm usage during assessment of clinically relevant variants using the ACMG/AMP guidelines.

Genomic analysis of the hierarchical structure of regulatory networks

Science.gov (United States)

Yu, Haiyuan; Gerstein, Mark

2006-01-01

A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

Predictive modelling of gene expression from transcriptional regulatory elements.

Science.gov (United States)

Budden, David M; Hurley, Daniel G; Crampin, Edmund J

2015-07-01

Predictive modelling of gene expression provides a powerful framework for exploring the regulatory logic underpinning transcriptional regulation. Recent studies have demonstrated the utility of such models in identifying dysregulation of gene and miRNA expression associated with abnormal patterns of transcription factor (TF) binding or nucleosomal histone modifications (HMs). Despite the growing popularity of such approaches, a comparative review of the various modelling algorithms and feature extraction methods is lacking. We define and compare three methods of quantifying pairwise gene-TF/HM interactions and discuss their suitability for integrating the heterogeneous chromatin immunoprecipitation (ChIP)-seq binding patterns exhibited by TFs and HMs. We then construct log-linear and ϵ-support vector regression models from various mouse embryonic stem cell (mESC) and human lymphoblastoid (GM12878) data sets, considering both ChIP-seq- and position weight matrix- (PWM)-derived in silico TF-binding. The two algorithms are evaluated both in terms of their modelling prediction accuracy and ability to identify the established regulatory roles of individual TFs and HMs. Our results demonstrate that TF-binding and HMs are highly predictive of gene expression as measured by mRNA transcript abundance, irrespective of algorithm or cell type selection and considering both ChIP-seq and PWM-derived TF-binding. As we encourage other researchers to explore and develop these results, our framework is implemented using open-source software and made available as a preconfigured bootable virtual environment. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

An approach for reduction of false predictions in reverse engineering of gene regulatory networks.

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Khan, Abhinandan; Saha, Goutam; Pal, Rajat Kumar

2018-05-14

A gene regulatory network discloses the regulatory interactions amongst genes, at a particular condition of the human body. The accurate reconstruction of such networks from time-series genetic expression data using computational tools offers a stiff challenge for contemporary computer scientists. This is crucial to facilitate the understanding of the proper functioning of a living organism. Unfortunately, the computational methods produce many false predictions along with the correct predictions, which is unwanted. Investigations in the domain focus on the identification of as many correct regulations as possible in the reverse engineering of gene regulatory networks to make it more reliable and biologically relevant. One way to achieve this is to reduce the number of incorrect predictions in the reconstructed networks. In the present investigation, we have proposed a novel scheme to decrease the number of false predictions by suitably combining several metaheuristic techniques. We have implemented the same using a dataset ensemble approach (i.e. combining multiple datasets) also. We have employed the proposed methodology on real-world experimental datasets of the SOS DNA Repair network of Escherichia coli and the IMRA network of Saccharomyces cerevisiae. Subsequently, we have experimented upon somewhat larger, in silico networks, namely, DREAM3 and DREAM4 Challenge networks, and 15-gene and 20-gene networks extracted from the GeneNetWeaver database. To study the effect of multiple datasets on the quality of the inferred networks, we have used four datasets in each experiment. The obtained results are encouraging enough as the proposed methodology can reduce the number of false predictions significantly, without using any supplementary prior biological information for larger gene regulatory networks. It is also observed that if a small amount of prior biological information is incorporated here, the results improve further w.r.t. the prediction of true positives

Inferring regulatory networks from experimental morphological phenotypes: a computational method reverse-engineers planarian regeneration.

Directory of Open Access Journals (Sweden)

Daniel Lobo

2015-06-01

Full Text Available Transformative applications in biomedicine require the discovery of complex regulatory networks that explain the development and regeneration of anatomical structures, and reveal what external signals will trigger desired changes of large-scale pattern. Despite recent advances in bioinformatics, extracting mechanistic pathway models from experimental morphological data is a key open challenge that has resisted automation. The fundamental difficulty of manually predicting emergent behavior of even simple networks has limited the models invented by human scientists to pathway diagrams that show necessary subunit interactions but do not reveal the dynamics that are sufficient for complex, self-regulating pattern to emerge. To finally bridge the gap between high-resolution genetic data and the ability to understand and control patterning, it is critical to develop computational tools to efficiently extract regulatory pathways from the resultant experimental shape phenotypes. For example, planarian regeneration has been studied for over a century, but despite increasing insight into the pathways that control its stem cells, no constructive, mechanistic model has yet been found by human scientists that explains more than one or two key features of its remarkable ability to regenerate its correct anatomical pattern after drastic perturbations. We present a method to infer the molecular products, topology, and spatial and temporal non-linear dynamics of regulatory networks recapitulating in silico the rich dataset of morphological phenotypes resulting from genetic, surgical, and pharmacological experiments. We demonstrated our approach by inferring complete regulatory networks explaining the outcomes of the main functional regeneration experiments in the planarian literature; By analyzing all the datasets together, our system inferred the first systems-biology comprehensive dynamical model explaining patterning in planarian regeneration. This method

In vitro cytotoxic and in silico activity of piperine isolated from Piper nigrum fruits Linn.

Science.gov (United States)

Paarakh, Padmaa M; Sreeram, Dileep Chandra; D, Shruthi S; Ganapathy, Sujan P S

2015-12-01

Piper nigrum [Piperaceae], commonly known as black pepper is used as medicine fairly throughout the greater part of India and as a spice globally. To isolate piperine and evaluate in vitro cytotoxic [antiproliferative] activity and in silico method. Piperine was isolated from the fruits of P.nigrum. Piperine was characterized by UV,IR, (1)H-NMR, (13)C-NMR and Mass spectrum. Standardization of piperine was done also by HPTLC fingerprinting. In vitro cytotoxic activity was done using HeLa cell lines by MTT assay at different concentrations ranging from 20 to 100 μg/ml in triplicate and in silico docking studies using enzyme EGFR tyrosine kinase. Fingerprinting of isolated piperine were done by HPTLC method. The IC50 value was found to be 61.94 ± 0.054 μg/ml in in vitro cytotoxic activity in HeLa Cell lines. Piperine was subjected to molecular docking studies for the inhibition of the enzyme EGFR tyrosine kinase, which is one of the targets for inhibition of cancer cells. It has shown -7.6 kJ mol(-1) binding and 7.06 kJ mol(-1) docking energy with two hydrogen bonds. piperine has shown to possess in vitro cytotoxic activity and in silico studies.

Combining in vitro and in silico methods for better prediction of surfactant effects on the absorption of poorly water soluble drugs-a fenofibrate case example.

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Berthelsen, Ragna; Sjögren, Erik; Jacobsen, Jette; Kristensen, Jakob; Holm, René; Abrahamsson, Bertil; Müllertz, Anette

2014-10-01

The aim of this study was to develop a sensitive and discriminative in vitro-in silico model able to simulate the in vivo performance of three fenofibrate immediate release formulations containing different surfactants. In addition, the study was designed to investigate the effect of dissolution volume when predicting the oral bioavailability of the formulations. In vitro dissolution studies were carried out using the USP apparatus 2 or a mini paddle assembly, containing 1000 mL or 100mL fasted state biorelevant medium, respectively. In silico simulations of small intestinal absorption were performed using the GI-Sim absorption model. All simulation runs were performed twice adopting either a total small intestinal volume of 533 mL or 105 mL, in order to examine the implication of free luminal water volumes for the in silico predictions. For the tested formulations, the use of a small biorelevant dissolution volume was critical for in vitro-in silico prediction of drug absorption. Good predictions, demonstrating rank order in vivo-in vitro-in silico correlations for Cmax, were obtained with in silico predictions utilizing a 105 mL estimate for the human intestinal water content combined with solubility and dissolution data performed in a mini paddle apparatus with 100mL fasted state simulated media. Copyright © 2014. Published by Elsevier B.V.

An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data

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Martens-Uzunova Elena S

2010-10-01

Full Text Available Abstract Background The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current in silico prediction methods suffer from gene-model errors introduced during genome annotation. Results A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome. As a complement to these in silico predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in A. niger were identified. Conclusions We were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed in silico predictions.

An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data.

Science.gov (United States)

Braaksma, Machtelt; Martens-Uzunova, Elena S; Punt, Peter J; Schaap, Peter J

2010-10-19

The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current in silico prediction methods suffer from gene-model errors introduced during genome annotation. A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome. As a complement to these in silico predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in A. niger were identified. We were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed in silico predictions.

Designing regulatory frameworks for merchant transmission investments by real options analysis

International Nuclear Information System (INIS)

Pringles, Rolando; Olsina, Fernando; Garcés, Francisco

2014-01-01

In deregulated electricity markets, the transmission network is a key infrastructure for enabling competition in the generation sector. A deficient expansion of the transmission grid prevents the realization of the benefits in terms of efficiency associated with market mechanisms. Consequently, it is essential to provide clear investment policies and economic signals to attract timely and efficient transmission investments in order to develop the system at minimum cost meeting the requirements of generators and consumers, while keeping adequate levels of service quality and reliability. This paper proposes a modern tool of economic evaluation based on real options analysis that provides the regulator the ability to assess various incentives that would lead transmission investors to make efficient decisions in highly uncertain environments. Real options properly values partially irreversible investment decisions, such as to defer, modify or abandon an investment project in response to the arrival of new information or as uncertainties are resolved. Decisions are evaluated from the point of view of a transmission investor trying to maximize its own profits in the time period set to recover the capital invested. The results allow the study of the behavior of transmission investors regarding their decision making when they have the possibility to manage the option to defer, under different regulatory schemes that encourage the expansion of the transmission system. - Highlights: • Regulatory frameworks for efficient and timely transmission expansions are designed. • Irreversibility and uncertainty of transmission investment is properly accounted for. • Response of network investors to regulatory incentives is quantitatively established

Managing Regulatory Body Competence

International Nuclear Information System (INIS)

2013-01-01

In 2001, the IAEA published TECDOC 1254, which examined the way in which the recognized functions of a regulatory body for nuclear facilities results in competence needs. Using the systematic approach to training (SAT), TECDOC 1254 provided a framework for regulatory bodies for managing training and developing and their maintaining their competence. It has been successfully used by many regulators. The IAEA has also introduced a methodology and an assessment tool - Guidelines for Systematic Assessment of Regulatory Competence Needs (SARCoN) - which provides practical guidance on analysing the training and development needs of a regulatory body and, through a gap analysis, guidance on establishing competence needs and how to meet them. In 2009, the IAEA established a steering committee (supported by a bureau) with the mission to advise the IAEA on how it could best assist Member States to develop suitable competence management systems for their regulatory bodies. The committee recommended the development of a safety report on managing staff competence as an integral part of a regulatory body's management system. This Safety Report was developed in response to this request. It supersedes TECDOC 1254, broadens its application to regulatory bodies for all facilities and activities, and builds upon the experience gained through the application of TECDOC 1254 and SARCoN and the feedback received from Member States. This Safety Report applies to the management of adequate competence as needs change, and as such is equally applicable to the needs of States 'embarking' on a nuclear power programme. It also deals with the special case of building up the competence of regulatory bodies as part of the overall process of establishing an 'embarking' State's regulatory system

Regulatory analysis for resolution of USI A-17

International Nuclear Information System (INIS)

Thatcher, D.F.

1989-08-01

This report presents a summary of the regulatory analysis conducted by the NRC staff to evaluate the value and impact of potential alternatives for the resolution of Unresolved Safety Issue (USI) A-17, ''Systems Interactions in Nuclear Power Plants.'' The NRC staff's proposed resolution offered in this report is based on this analysis. The staff's technical finding regarding interactions can be found in NUREG-1174. Adverse systems interactions (ASIs) involve subtle and often very complicated plant-specific dependencies between components and systems, possible compounded by inducing erroneous human intervention. The staff has identified actions to be taken by licensees and the NRC to resolve USI A-17; the staff has also made the judgment that these actions, together with other ongoing activities, would reduce the risk from adverse systems interactions. As discussed further in this report, the staff judgment that the actions are sufficient is not based on the assertion that all systems interactions have been identified, but rather that the A-17 actions, plus other activities by the licensees and staff, will identify precursors to potentially risk-significant interactions so that the action can be taken if deemed necessary

Synthesis, properties and effect of ionizing radiation on sorption behavior of iron silico-antimonate

International Nuclear Information System (INIS)

Ali, I.M.; Zakaria, E.S.; El-Naggar, I.M.; Shama, S.A.

2010-01-01

Incorporation of iron oxide into silico-antimonate of different Si/Sb molar ratios introduced a class of dual salts ion exchangers with advanced ion exchange properties. Physicochemical and equilibrium studies have been carried out to understand the ion exchange properties of these materials. Apparent investigation indicated that iron incorporation into silico-antimonate yields materials having excellent mechanical properties. On the basis of distribution studies, the materials were found to be highly selective for Sr 2+ or Ce 3+ depending on their Si/Sb molar ratios. Diffractogram, thermogram, IR spectra and sorption performance of crystalline FeSiSb (114) indicated that no detectable structural changes after an exposure up to 100 kGy of γ-rays. Effect of reaction temperature on the exchange process was investigated and the respective thermodynamic parameters were calculated. (author)

An in silico MS/MS library for automatic annotation of novel FAHFA lipids.

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Ma, Yan; Kind, Tobias; Vaniya, Arpana; Gennity, Ingrid; Fahrmann, Johannes F; Fiehn, Oliver

2015-01-01

A new lipid class named 'fatty acid esters of hydroxyl fatty acids' (FAHFA) was recently discovered in mammalian adipose tissue and in blood plasma and some FAHFAs were found to be associated with type 2 diabetes. To facilitate the automatic annotation of FAHFAs in biological specimens, a tandem mass spectra (MS/MS) library is needed. Due to the limitation of the commercial available standard compounds, we proposed building an in silico MS/MS library to extend the coverage of molecules. We developed a computer-generated library with 3267 tandem mass spectra (MS/MS) for 1089 FAHFA species. FAHFA spectra were generated based on authentic standards with negative mode electrospray ionization and 10, 20, and 40 V collision induced dissociation at 4 spectra/s as used in in ultra-high performance liquid chromatography-QTOF mass spectrometry studies. However, positional information of the hydroxyl group is only obtained either at lower QTOF spectra acquisition rates of 1 spectrum/s or at the MS(3) level in ion trap instruments. Therefore, an additional set of 4290 fragment-rich MS/MS spectra was created to enable distinguishing positional FAHFA isomers. The library was generated based on ion fragmentations and ion intensities of FAHFA external reference standards, developing a heuristic model for fragmentation rules and extending these rules to large swaths of computer-generated structures of FAHFAs with varying chain lengths, degrees of unsaturation and hydroxyl group positions. Subsequently, we validated the new in silico library by discovering several new FAHFA species in egg yolk, showing that this library enables high-throughput screening of FAHFA lipids in various biological matrices. The developed library and templates are freely available for commercial or noncommercial use at http://fiehnlab.ucdavis.edu/staff/yanma/fahfa-lipid-library. This in silico MS/MS library allows users to annotate FAHFAs from accurate mass tandem mass spectra in an easy and fast manner

Analysis of replies to an IAEA questionnaire on inspection and enforcement by the regulatory body for nuclear power plants

International Nuclear Information System (INIS)

1991-03-01

At a Special Session of the IAEA General Conference in September 1986, it was suggested that the IAEA could play a role in assisting Member States in the enhancement of their regulatory practices with the objective of increasing the confidence of the international community in the safety of nuclear power programmes. As the first stage of this assistance, the Agency initiated an IAEA Questionnaire on Regulatory Practices in Member States with Nuclear Power Programmes and summarized the results of an analysis of replies to the questionnaire, issued as IAEA-TECDOC--485 (October 1988). The IAEA Questionnaire on Inspection and Enforcement by the Regulatory Body for Nuclear Power Plants, drafted by a group of consultants and IAEA staff members in August 1989, was initiated as a follow-up to the general questionnaire on regulatory practices. This questionnaire on inspection and enforcement was sent on 3 October 1989 to 31 Member States in which nuclear power plants are under construction and/or in operation. Replies to the questionnaire received from 26 Member States were analysed by IAEA staff members with the assistance of consultants in order to identify the main differences in approach and important aspects of inspection and enforcement by the regulatory body for nuclear power plants. This report is the summary report on the results of the analysis of the replies to the questionnaire from 26 Member States. 12 tabs

In silico peptide prediction for antibody generation to recognize 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) in genetically modified organisms.

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Marani, Mariela M; Costa, Joana; Mafra, Isabel; Oliveira, Maria Beatriz P P; Camperi, Silvia A; Leite, José Roberto de Souza Almeida

2015-03-01

For the prospective immunorecognition of 5-enolpyruvylshikimate-3-phosphate synthase (CP4-EPSPS) as a biomarker protein expressed by transgenic soybean, an extensive in silico evaluation of the referred protein was performed. The main objective of this study was the selection of a set of peptides that could function as potential immunogens for the production of novel antibodies against CP4-EPSPS protein. For this purpose, the protein was in silico cleaved with trypsin/chymotrypsin and the resultant peptides were extensively analyzed for further selection of the best candidates for antibody production. The analysis enabled the successful proposal of four peptides with potential immunogenicity for their future use as screening biomarkers of genetically modified organisms. To our knowledge, this is the first attempt to select and define potential linear epitopes for the immunization of animals and, subsequently, to generate adequate antibodies for CP4-EPSPS recognition. The present work will be followed by the synthesis of the candidate peptides to be incubated in animals for antibody generation and potential applicability for the development of an immunosensor for CP4-EPSPS detection. © 2015 Wiley Periodicals, Inc.

In silico investigation of lavandulyl flavonoids for the development of potent fatty acid synthase-inhibitory prototypes.

Science.gov (United States)

Oh, Joonseok; Liu, Haining; Park, Hyun Bong; Ferreira, Daneel; Jeong, Gil-Saeng; Hamann, Mark T; Doerksen, Robert J; Na, MinKyun

2017-01-01

Inhibition of fatty acid synthase (FAS) is regarded as a sensible therapeutic strategy for the development of optimal anti-cancer agents. Flavonoids exhibit potent anti-neoplastic properties. The MeOH extract of Sophora flavescens was subjected to chromatographic analyses such as VLC and HPLC for the purification of active flavonoids. The DP4 chemical-shift analysis protocol was employed to investigate the elusive chirality of the lavandulyl moiety of the purified polyphenols. Induced Fit docking protocols and per-residue analyses were utilized to scrutinize structural prerequisites for hampering FAS activity. The FAS-inhibitory activity of the purified flavonoids was assessed via the incorporation of [ 3 H] acetyl-CoA into palmitate. Six flavonoids, including lavandulyl flavanones, were purified and evaluated for FAS inhibition. The lavandulyl flavanone sophoraflavanone G (2) exhibited the highest potency (IC 50 of 6.7±0.2μM), which was more potent than the positive controls. Extensive molecular docking studies revealed the structural requirements for blocking FAS. Per-residue interaction analysis demonstrated that the lavandulyl functional group in the active flavonoids (1-3 and 5) significantly contributed to increasing their binding affinity towards the target enzyme. This research suggests a basis for the in silico design of a lavandulyl flavonoid-based architecture showing anti-cancer effects via enhancement of the binding potential to FAS. FAS inhibition by flavonoids and their derivatives may offer significant potential as an approach to lower the risk of various cancer diseases and related fatalities. In silico technologies with available FAS crystal structures may be of significant use in optimizing preliminary leads. Copyright © 2016 Elsevier B.V. All rights reserved.

A Regulatory Network Analysis of Orphan Genes in Arabidopsis Thaliana

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Singh, Pramesh; Chen, Tianlong; Arendsee, Zebulun; Wurtele, Eve S.; Bassler, Kevin E.

Orphan genes, which are genes unique to each particular species, have recently drawn significant attention for their potential usefulness for organismal robustness. Their origin and regulatory interaction patterns remain largely undiscovered. Recently, methods that use the context likelihood of relatedness to infer a network followed by modularity maximizing community detection algorithms on the inferred network to find the functional structure of regulatory networks were shown to be effective. We apply improved versions of these methods to gene expression data from Arabidopsis thaliana, identify groups (clusters) of interacting genes with related patterns of expression and analyze the structure within those groups. Focusing on clusters that contain orphan genes, we compare the identified clusters to gene ontology (GO) terms, regulons, and pathway designations and analyze their hierarchical structure. We predict new regulatory interactions and unravel the structure of the regulatory interaction patterns of orphan genes. Work supported by the NSF through Grants DMR-1507371 and IOS-1546858.

Calibration of Multiple In Silico Tools for Predicting Pathogenicity of Mismatch Repair Gene Missense Substitutions

Science.gov (United States)

Thompson, Bryony A.; Greenblatt, Marc S.; Vallee, Maxime P.; Herkert, Johanna C.; Tessereau, Chloe; Young, Erin L.; Adzhubey, Ivan A.; Li, Biao; Bell, Russell; Feng, Bingjian; Mooney, Sean D.; Radivojac, Predrag; Sunyaev, Shamil R.; Frebourg, Thierry; Hofstra, Robert M.W.; Sijmons, Rolf H.; Boucher, Ken; Thomas, Alun; Goldgar, David E.; Spurdle, Amanda B.; Tavtigian, Sean V.

2015-01-01

Classification of rare missense substitutions observed during genetic testing for patient management is a considerable problem in clinical genetics. The Bayesian integrated evaluation of unclassified variants is a solution originally developed for BRCA1/2. Here, we take a step toward an analogous system for the mismatch repair (MMR) genes (MLH1, MSH2, MSH6, and PMS2) that confer colon cancer susceptibility in Lynch syndrome by calibrating in silico tools to estimate prior probabilities of pathogenicity for MMR gene missense substitutions. A qualitative five-class classification system was developed and applied to 143 MMR missense variants. This identified 74 missense substitutions suitable for calibration. These substitutions were scored using six different in silico tools (Align-Grantham Variation Grantham Deviation, multivariate analysis of protein polymorphisms [MAPP], Mut-Pred, PolyPhen-2.1, Sorting Intolerant From Tolerant, and Xvar), using curated MMR multiple sequence alignments where possible. The output from each tool was calibrated by regression against the classifications of the 74 missense substitutions; these calibrated outputs are interpretable as prior probabilities of pathogenicity. MAPP was the most accurate tool and MAPP + PolyPhen-2.1 provided the best-combined model (R2 = 0.62 and area under receiver operating characteristic = 0.93). The MAPP + PolyPhen-2.1 output is sufficiently predictive to feed as a continuous variable into the quantitative Bayesian integrated evaluation for clinical classification of MMR gene missense substitutions. PMID:22949387

Regulatory impact analysis of the proposed great lakes water quality guidance. Final report

International Nuclear Information System (INIS)

Raucher, R.; Dixon, A.; Trabka, E.

1993-01-01

The Regulatory Impact Analysis provides direction to the Great Lakes States and Tribes on minimum water quality standards and contains numerical water quality criteria for 32 pollutants as well as methodologies for the development of water quality criteria for additional pollutants discharged to these waters. It also provides guidance to the Great Lakes States and Tribes on antidegradation policies and standards and implementation procedures

In silico Analysis and Experimental Validation of Lignan Extracts from Kadsura longipedunculata for Potential 5-HT1AR Agonists.

Directory of Open Access Journals (Sweden)

Yaxin Zheng

Full Text Available Kadsura longipedunculata (KL has been widely used for the treatment of insomnia in traditional Chinese medicine. The aim of this study was to explore the mechanism of the sedative and hypnotic effects of KL.The content of KL was evaluated by HPLC-TOF-MS, and a potential target was found and used to construct its 3D structure to screen for potential ligands among the compounds in KL by using bioinformatics analysis, including similarity ensemble approach (SEA docking, homology modeling, molecular docking and ligand-based pharmacophore. The PCPA-induced insomnia rat model was then applied to confirm the potential targets related to the sedative effects of KL by performing the forced swimming test (FST, the tail suspension test (TST and the measurement of target-related proteins using western blotting and immunofluorescence.Bioinformatics analysis showed that most of lignan compounds in KL were optimal ligands for the 5-HT1A receptor (5-HT1AR, and they were found to be potential targets related to sedative effects; the main lignan content of KL extracts was characterized by HPLC-TOF-MS, with 7 proposed lignans detected. Administration of KL could significantly reduce FST and TST immobility time in the PCPA-induced 5HT-depleted insomnia rat model. The expressions of proteins related to the 5-HT1AR pathway were regulated by extracts of KL in a concentration-dependent manner, indicating that extracts of KL had 5-HT1AR agonist-like effects.In silico analysis and experimental validation together demonstrated that lignan extracts from KL can target 5-HT1AR in insomniac rats, which could shed light on its use as a potential 5-HT1AR agonist drug.

Regulatory reform in Turkish energy industry: An analysis

International Nuclear Information System (INIS)

Erdogdu, Erkan

2007-01-01

The Republic of Turkey has initiated an ambitious reform program in the most important segments of her energy market; which requires privatization, liberalization as well as a radical restructuring of these industries. However, there is no consensus that the measures introduced are optimal. The present article attempts, first, to evaluate the regulatory framework created by the laws of 2001 in terms of economic efficiency considerations; and second, to determine what still needs to be done to improve the current situation. The paper not only provides an analysis of these reforms but also lists some policy suggestions. The study concludes that despite relatively good legislative framework, in practice, the reforms in Turkey are far from ideal as they are mainly in the form of 'textbook reforms'; and therefore a significant amount of work still lies ahead of Turkey to set up a fully fledged energy market

Global Transcriptome Analysis of Combined Abiotic Stress Signaling Genes Unravels Key Players in Oryza sativa L.: An In silico Approach

Directory of Open Access Journals (Sweden)

Pandiyan Muthuramalingam

2017-05-01

Full Text Available Combined abiotic stress (CAbS affects the field grown plants simultaneously. The multigenic and quantitative nature of uncontrollable abiotic stresses complicates the process of understanding the stress response by plants. Considering this, we analyzed the CAbS response of C3 model plant, Oryza sativa by meta-analysis. The datasets of commonly expressed genes by drought, salinity, submergence, metal, natural expression, biotic, and abiotic stresses were data mined through publically accessible transcriptomic abiotic stress (AbS responsive datasets. Of which 1,175, 12,821, and 42,877 genes were commonly expressed in meta differential, individual differential, and unchanged expressions respectively. Highly regulated 100 differentially expressed AbS genes were derived through integrative meta-analysis of expression data (INMEX. Of this 30 genes were identified from AbS gene families through expression atlas that were computationally analyzed for their physicochemical properties. All AbS genes were physically mapped against O. sativa genome. Comparative mapping of these genes demonstrated the orthologous relationship with related C4 panicoid genome. In silico expression analysis of these genes showed differential expression patterns in different developmental tissues. Protein–protein interaction of these genes, represented the complexity of AbS. Computational expression profiling of candidate genes in response to multiple stresses suggested the putative involvement of OS05G0350900, OS02G0612700, OS05G0104200, OS03G0596200, OS12G0225900, OS07G0152000, OS08G0119500, OS06G0594700, and Os01g0393100 in CAbS. These potential candidate genes need to be studied further to decipher their functional roles in AbS dynamics.

Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

Science.gov (United States)

Clematis, Andrea; Quarati, Alfonso; Cesini, Daniele; Milanesi, Luciano; Merelli, Ivan

2013-01-01

Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements. PMID:24106693

Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

Directory of Open Access Journals (Sweden)

Daniele D'Agostino

2013-01-01

Full Text Available Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements.

In Silico Absorption, Distribution, Metabolism, Excretion, and Pharmacokinetics (ADME-PK): Utility and Best Practices. An Industry Perspective from the International Consortium for Innovation through Quality in Pharmaceutical Development.

Science.gov (United States)

Lombardo, Franco; Desai, Prashant V; Arimoto, Rieko; Desino, Kelly E; Fischer, Holger; Keefer, Christopher E; Petersson, Carl; Winiwarter, Susanne; Broccatelli, Fabio

2017-11-22

In silico tools to investigate absorption, distribution, metabolism, excretion, and pharmacokinetics (ADME-PK) properties of new chemical entities are an integral part of the current industrial drug discovery paradigm. While many companies are active in the field, scientists engaged in this area do not necessarily share the same background and have limited resources when seeking guidance on how to initiate and maintain an in silico ADME-PK infrastructure in an industrial setting. This work summarizes the views of a group of industrial in silico and experimental ADME scientists, participating in the In Silico ADME Working Group, a subgroup of the International Consortium for Innovation through Quality in Pharmaceutical Development (IQ) Drug Metabolism Leadership Group. This overview on the benefits, caveats, and impact of in silico ADME-PK should serve as a resource for medicinal chemists, computational chemists, and DMPK scientists working in drug design to increase their knowledge in the area.

Proposed standby gasoline rationing plan. Economic and regulatory analysis draft

Energy Technology Data Exchange (ETDEWEB)

1978-06-01

This economic and regulatory analysis meets the requirements of the Energy Policy and Conservation Act, which calls for an evaluation of the potential economic impacts of the gasoline rationing contingency plan. In addition, this analysis is intended to satisfy the requirements of the President's Executive Order No. 12044 of March 23, 1978, regarding government regulations, and provides an inflationary impact statement for the proposed rationing plan. To perform the analysis of rationing program impacts on the total national economy, three separate projections were required. First, a projection is made of the ''normal'' U.S. economy for a future period--the last quarter of 1980 through the third quarter of 1981 in this analysis. Second, a projection is made of the impacts which a petroleum supply interruption would have on the U.S. economy during this future period, assuming that DOE's standby allocation and price control regulations were implemented for crude oil and products. Third, and most significant, an estimate is made of the incremental impacts of the gasoline rationing program on this already-perturbed future U.S. economy.

Current therapeutic molecules and targets in neurodegenerative diseases based on in silico drug design.

Science.gov (United States)

Sehgal, Sheikh Arslan; Hammad, Mirza A; Tahir, Rana Adnan; Akram, Hafiza Nisha; Ahmad, Faheem

2018-03-15

As the number of elderly persons increases, neurodegenerative diseases are becoming ubiquitous. There is currently a great need for knowledge concerning management of old-age neurodegenerative diseases; the most important of which are: Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis, and Huntington's disease. To summarize the potential of computationally predicted molecules and targets against neurodegenerative diseases. Review of literature published since 1997 against neurodegenerative diseases, utilizing as keywords: in silico, Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis ALS, and Huntington's disease. Due to the costs associated with experimentation and current ethical law, performing experiments directly on living organisms has become much more difficult. In this scenario, in silico techniques have been successful and have become powerful tools in the search to cure disease. Researchers use the Computer Aided Drug Design pipeline which: 1) generates 3-dimensional structures of target proteins through homology modeling 2) achieves stabilization through molecular dynamics simulation, and 3) exploits molecular docking through large compound libraries. Next generation sequencing is continually producing enormous amounts of raw sequence data while neuroimaging is producing a multitude of raw image data. To solve such pressing problems, these new tools and algorithms are required. This review elaborates precise in silico tools and techniques for drug targets, active molecules, and molecular docking studies, together with future prospects and challenges concerning possible breakthroughs in Alzheimer's, Parkinson's, Amyotrophic Lateral Sclerosis, and Huntington's disease. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks.

Science.gov (United States)

Guo, Liyuan; Wang, Jing

2018-01-04

Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element-target gene pairs (E-G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Developing regulatory approaches

International Nuclear Information System (INIS)

Axelsson, Lars

2012-01-01

Lars Axelsson presented SSM progress on oversight of LMfS/SC since the Chester 1 Workshop in 2007. Current SSM approaches for safety culture oversight include targeted safety management and safety culture inspections, compliance inspections which cover aspects of safety management/safety culture and multi-disciplinary team inspections. Examples of themes for targeted inspections include management of ambiguous operational situations or other weak signals, understanding of and attitudes to Human Performance tools, the Safety Department's role and authority and Leadership for safety. All regulatory activities provide inputs for the SSM yearly safety evaluation of each licensee. A form has been developed to capture safety culture observations from inspections and other interactions with licensees. Analysis will be performed to identify patterns and provide information to support planning of specific Safety Culture activities. Training has been developed for regulatory staff to enhance the quality of regulatory interventions on safety culture. This includes a half-day seminar to provide an overview of safety culture, and a workshop which provides more in-depth discussion on cultural issues and how to capture those during regulatory activities. Future plans include guidance for inspectors, and informal seminars on safety culture with licensees

Bio-physically plausible visualization of highly scattering fluorescent neocortical models for in silico experimentation

KAUST Repository

Abdellah, Marwan; Bilgili, Ahmet; Eilemann, Stefan; Shillcock, Julian; Markram, Henry; Schü rmann, Felix

2017-01-01

to visualize the results of their virtual experiments that are performed in computer simulations, or in silico. The impact of the presented pipeline opens novel avenues for assisting the neuroscientists to build biologically accurate models of the brain

Regulatory analysis for resolution of USI [Unresolved Safety Issue] A-47

International Nuclear Information System (INIS)

Szukiewicz, A.J.

1989-07-01

This report presents a summary of the regulatory analysis conducted by the US Nuclear Regulatory Commission staff to evaluate the value/impact of alternatives for the resolution of Unresolved Safety Issue A-47, ''Safety Implications of Control Systems.'' The NRC staff's resolution presented herein is based on these analyses and on the technical findings and conclusions presented in NUREG-1217, the companion document to this report. The staff has concluded that certain actions should be taken to improve safety in light-water reactor plants. The staff recommended that certain plants improve their control systems to preclude reactor vessel/steam generator overfill events and to prevent steam generator dryout, modify their technical specifications to verify operability of such systems, and modify selected emergency procedures to ensure safe shutdown of the plant following a small-break loss-of-coolant accident. This report was issued as a draft for public comment on May 27, 1988. As a result of the public comments received, this report was revised. The NRC staff's responses to and resolution of the public comments are included as Appendix C to the final report, NUREG-1217

In Silico Functional Networks Identified in Fish Nucleated Red Blood Cells by Means of Transcriptomic and Proteomic Profiling

Directory of Open Access Journals (Sweden)

Sara Puente-Marin

2018-04-01

Full Text Available Nucleated red blood cells (RBCs of fish have, in the last decade, been implicated in several immune-related functions, such as antiviral response, phagocytosis or cytokine-mediated signaling. RNA-sequencing (RNA-seq and label-free shotgun proteomic analyses were carried out for in silico functional pathway profiling of rainbow trout RBCs. For RNA-seq, a de novo assembly was conducted, in order to create a transcriptome database for RBCs. For proteome profiling, we developed a proteomic method that combined: (a fractionation into cytosolic and membrane fractions, (b hemoglobin removal of the cytosolic fraction, (c protein digestion, and (d a novel step with pH reversed-phase peptide fractionation and final Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometric (LC ESI-MS/MS analysis of each fraction. Combined transcriptome- and proteome- sequencing data identified, in silico, novel and striking immune functional networks for rainbow trout nucleated RBCs, which are mainly linked to innate and adaptive immunity. Functional pathways related to regulation of hematopoietic cell differentiation, antigen presentation via major histocompatibility complex class II (MHCII, leukocyte differentiation and regulation of leukocyte activation were identified. These preliminary findings further implicate nucleated RBCs in immune function, such as antigen presentation and leukocyte activation.

Application of in silico modelling to estimate toxicity of migrating substances from food packaging.

Science.gov (United States)

Price, Nicholas; Chaudhry, Qasim

2014-09-01

This study derived toxicity estimates for a set of 136 chemical migrants from food packaging materials using in silico (computational) modelling and read across approaches. Where available, the predicted results for mutagenicity and carcinogenicity were compared with published experimental data. As the packaging compounds are subject to safety assessment, the migrating substances were more likely to be negative for both the endpoints. A set of structural analogues with positive experimental data for carcinogenicity and/or mutagenicity was therefore used as a positive comparator. The results showed that a weight of evidence assembled from different in silico models and read-across from already-tested structurally similar compounds can provide a rapid and reliable means for rapid screening of new yet-untested intentional or unintentional chemical compounds that may migrate to packaged foodstuffs. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Thorough in silico and in vitro cDNA analysis of 21 putative BRCA1 and BRCA2 splice variants and a complex tandem duplication in BRCA2 allowing the identification of activated cryptic splice donor sites in BRCA2 exon 11.

Science.gov (United States)

Baert, Annelot; Machackova, Eva; Coene, Ilse; Cremin, Carol; Turner, Kristin; Portigal-Todd, Cheryl; Asrat, Marie Jill; Nuk, Jennifer; Mindlin, Allison; Young, Sean; MacMillan, Andree; Van Maerken, Tom; Trbusek, Martin; McKinnon, Wendy; Wood, Marie E; Foulkes, William D; Santamariña, Marta; de la Hoya, Miguel; Foretova, Lenka; Poppe, Bruce; Vral, Anne; Rosseel, Toon; De Leeneer, Kim; Vega, Ana; Claes, Kathleen B M

2018-04-01

For 21 putative BRCA1 and BRCA2 splice site variants, the concordance between mRNA analysis and predictions by in silico programs was evaluated. Aberrant splicing was confirmed for 12 alterations. In silico prediction tools were helpful to determine for which variants cDNA analysis is warranted, however, predictions for variants in the Cartegni consensus region but outside the canonical sites, were less reliable. Learning algorithms like Adaboost and Random Forest outperformed the classical tools. Further validations are warranted prior to implementation of these novel tools in clinical settings. Additionally, we report here for the first time activated cryptic donor sites in the large exon 11 of BRCA2 by evaluating the effect at the cDNA level of a novel tandem duplication (5' breakpoint in intron 4; 3' breakpoint in exon 11) and of a variant disrupting the splice donor site of exon 11 (c.6841+1G > C). Additional sites were predicted, but not activated. These sites warrant further research to increase our knowledge on cis and trans acting factors involved in the conservation of correct transcription of this large exon. This may contribute to adequate design of ASOs (antisense oligonucleotides), an emerging therapy to render cancer cells sensitive to PARP inhibitor and platinum therapies. © 2017 Wiley Periodicals, Inc.

Transcriptional regulation of rod photoreceptor homeostasis revealed by in vivo NRL targetome analysis.

Directory of Open Access Journals (Sweden)

Hong Hao

Full Text Available A stringent control of homeostasis is critical for functional maintenance and survival of neurons. In the mammalian retina, the basic motif leucine zipper transcription factor NRL determines rod versus cone photoreceptor cell fate and activates the expression of many rod-specific genes. Here, we report an integrated analysis of NRL-centered gene regulatory network by coupling chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq data from Illumina and ABI platforms with global expression profiling and in vivo knockdown studies. We identified approximately 300 direct NRL target genes. Of these, 22 NRL targets are associated with human retinal dystrophies, whereas 95 mapped to regions of as yet uncloned retinal disease loci. In silico analysis of NRL ChIP-Seq peak sequences revealed an enrichment of distinct sets of transcription factor binding sites. Specifically, we discovered that genes involved in photoreceptor function include binding sites for both NRL and homeodomain protein CRX. Evaluation of 26 ChIP-Seq regions validated their enhancer functions in reporter assays. In vivo knockdown of 16 NRL target genes resulted in death or abnormal morphology of rod photoreceptors, suggesting their importance in maintaining retinal function. We also identified histone demethylase Kdm5b as a novel secondary node in NRL transcriptional hierarchy. Exon array analysis of flow-sorted photoreceptors in which Kdm5b was knocked down by shRNA indicated its role in regulating rod-expressed genes. Our studies identify candidate genes for retinal dystrophies, define cis-regulatory module(s for photoreceptor-expressed genes and provide a framework for decoding transcriptional regulatory networks that dictate rod homeostasis.

In Silico Analysis of the Regulation of the Photosynthetic Electron Transport Chain in C3 Plants.

Science.gov (United States)

Morales, Alejandro; Yin, Xinyou; Harbinson, Jeremy; Driever, Steven M; Molenaar, Jaap; Kramer, David M; Struik, Paul C

2018-02-01

We present a new simulation model of the reactions in the photosynthetic electron transport chain of C3 species. We show that including recent insights about the regulation of the thylakoid proton motive force, ATP/NADPH balancing mechanisms (cyclic and noncyclic alternative electron transport), and regulation of Rubisco activity leads to emergent behaviors that may affect the operation and regulation of photosynthesis under different dynamic environmental conditions. The model was parameterized with experimental results in the literature, with a focus on Arabidopsis ( Arabidopsis thaliana ). A dataset was constructed from multiple sources, including measurements of steady-state and dynamic gas exchange, chlorophyll fluorescence, and absorbance spectroscopy under different light intensities and CO 2 , to test predictions of the model under different experimental conditions. Simulations suggested that there are strong interactions between cyclic and noncyclic alternative electron transport and that an excess capacity for alternative electron transport is required to ensure adequate redox state and lumen pH. Furthermore, the model predicted that, under specific conditions, reduction of ferredoxin by plastoquinol is possible after a rapid increase in light intensity. Further analysis also revealed that the relationship between ATP synthesis and proton motive force was highly regulated by the concentrations of ATP, ADP, and inorganic phosphate, and this facilitated an increase in nonphotochemical quenching and proton motive force under conditions where metabolism was limiting, such as low CO 2 , high light intensity, or combined high CO 2 and high light intensity. The model may be used as an in silico platform for future research on the regulation of photosynthetic electron transport. © 2018 American Society of Plant Biologists. All Rights Reserved.

In silico docking studies of aldose reductase inhibitory activity of commercially available flavonoids

Directory of Open Access Journals (Sweden)

Arumugam Madeswaran

2012-12-01

Full Text Available The primary objective of this study was to investigate the aldose reductase inhibitory activity of flavonoids using in silico docking studies. In this perspective, flavonoids like biochanin, butein, esculatin, fisetin and herbacetin were selected. Epalrestat, a known aldose reductase inhibitor was used as the standard. In silico docking studies were carried out using AutoDock 4.2, based on the Lamarckian genetic algorithm principle. The results showed that all the selected flavonoids showed binding energy ranging between -9.33 kcal/mol to -7.23 kcal/mol when compared with that of the standard (-8.73 kcal/mol. Inhibition constant (144.13 µM to 4.98 µM and intermolecular energy (-11.42 kcal/mol to -7.83 kcal/mol of the flavonoids also coincide with the binding energy. All the selected flavonoids contributed aldose reductase inhibitory activity because of its structural properties. These molecular docking analyses could lead to the further development of potent aldose reductase inhibitors for the treatment of diabetes.

Safety culture in regulatory expert organization : analysis result of survey for KINS employees

International Nuclear Information System (INIS)

Choi, G. S.; Choi, Y. S.

2003-01-01

Much has been discussed on safety culture of operating organizations, however, little has been done on that of regulatory organization. Current issues and activities related to nuclear safety culture at IAEA, OECD/NEA, etc. were investigated and relevant literatures were reviewed. Elements essential for safety culture of regulatory organization were proposed and survey questionnaire for employees of regulatory expert organization, KINS, was developed based on the elements proposed. The survey result was presented and its implications were discussed. Based on the result, elements of safety culture in regulatory organization were proposed. The result of this survey can be used in developing safety culture model of regulatory organization, measurement method and also promotion of safety culture in regulatory organization

Determining Regulatory Networks Governing the Differentiation of Embryonic Stem Cells to Pancreatic Lineage

Science.gov (United States)

Banerjee, Ipsita

2009-03-01

Knowledge of pathways governing cellular differentiation to specific phenotype will enable generation of desired cell fates by careful alteration of the governing network by adequate manipulation of the cellular environment. With this aim, we have developed a novel method to reconstruct the underlying regulatory architecture of a differentiating cell population from discrete temporal gene expression data. We utilize an inherent feature of biological networks, that of sparsity, in formulating the network reconstruction problem as a bi-level mixed-integer programming problem. The formulation optimizes the network topology at the upper level and the network connectivity strength at the lower level. The method is first validated by in-silico data, before applying it to the complex system of embryonic stem (ES) cell differentiation. This formulation enables efficient identification of the underlying network topology which could accurately predict steps necessary for directing differentiation to subsequent stages. Concurrent experimental verification demonstrated excellent agreement with model prediction.

OpenVirtualToxLab--a platform for generating and exchanging in silico toxicity data.

Science.gov (United States)

Vedani, Angelo; Dobler, Max; Hu, Zhenquan; Smieško, Martin

2015-01-22

The VirtualToxLab is an in silico technology for estimating the toxic potential--endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity--of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of currently 16 proteins, known or suspected to trigger adverse effects: 10 nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, thyroid β), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG). The toxic potential of a compound--its ability to trigger adverse effects--is derived from its computed binding affinities toward these very proteins: the computationally demanding simulations are executed in client-server model on a Linux cluster of the University of Basel. The graphical-user interface supports all computer platforms, allows building and uploading molecular structures, inspecting and downloading the results and, most important, rationalizing any prediction at the atomic level by interactively analyzing the binding mode of a compound with its target protein(s) in real-time 3D. Access to the VirtualToxLab is available free of charge for universities, governmental agencies, regulatory bodies and non-profit organizations. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

In silico characterization and transcriptomic analysis of nif family genes from Anabaena sp. PCC7120.

Science.gov (United States)

Singh, Shilpi; Shrivastava, Alok Kumar

2017-10-01

In silico approaches in conjunction with morphology, nitrogenase activity, and qRT-PCR explore the impact of selected abiotic stressor such as arsenic, salt, cadmium, copper, and butachlor on nitrogen fixing (nif family) genes of diazotrophic cyanobacterium Anabaena sp. PCC7120. A total of 19 nif genes are present within the Anabaena genome that is involved in the process of nitrogen fixation. Docking studies revealed the interaction between these nif gene-encoded proteins and the selected abiotic stressors which were further validated through decreased heterocyst frequency, fragmentation of filaments, and downregulation of nitrogenase activity under these stresses indicating towards their toxic impact on nitrogen fixation potential of filamentous cyanobacterium Anabaena sp. PCC7120. Another appealing finding of this study is even though having similar binding energy and similar interacting residues between arsenic/salt and copper/cadmium to nif-encoded proteins, arsenic and cadmium are more toxic than salt and copper for nitrogenase activity of Anabaena which is crucial for growth and yield of rice paddy and soil reclamation.

Investigating the metabolic capabilities of Mycobacterium tuberculosis H37Rv using the in silico strain iNJ661 and proposing alternative drug targets

Directory of Open Access Journals (Sweden)

Palsson Bernhard Ø

2007-06-01

Full Text Available Abstract Background: Mycobacterium tuberculosis continues to be a major pathogen in the third world, killing almost 2 million people a year by the most recent estimates. Even in industrialized countries, the emergence of multi-drug resistant (MDR strains of tuberculosis hails the need to develop additional medications for treatment. Many of the drugs used for treatment of tuberculosis target metabolic enzymes. Genome-scale models can be used for analysis, discovery, and as hypothesis generating tools, which will hopefully assist the rational drug development process. These models need to be able to assimilate data from large datasets and analyze them. Results: We completed a bottom up reconstruction of the metabolic network of Mycobacterium tuberculosis H37Rv. This functional in silico bacterium, iNJ661, contains 661 genes and 939 reactions and can produce many of the complex compounds characteristic to tuberculosis, such as mycolic acids and mycocerosates. We grew this bacterium in silico on various media, analyzed the model in the context of multiple high-throughput data sets, and finally we analyzed the network in an 'unbiased' manner by calculating the Hard Coupled Reaction (HCR sets, groups of reactions that are forced to operate in unison due to mass conservation and connectivity constraints. Conclusion: Although we observed growth rates comparable to experimental observations (doubling times ranging from about 12 to 24 hours in different media, comparisons of gene essentiality with experimental data were less encouraging (generally about 55%. The reasons for the often conflicting results were multi-fold, including gene expression variability under different conditions and lack of complete biological knowledge. Some of the inconsistencies between in vitro and in silico or in vivo and in silico results highlight specific loci that are worth further experimental investigations. Finally, by considering the HCR sets in the context of known

Argentine influence on regulatory activities in Latin America

International Nuclear Information System (INIS)

Palacios, Elias

1998-01-01

An analysis of the nuclear regulatory systems and the nuclear regulations of many Latin American countries shows a substantial influence of the Argentine regulatory structure. This influence is attributed to the early Argentine development of a regulatory and control organization, the teaching of regional training courses and the advice of Argentine experts to Latin-American governments

LNG development across Europe: Infrastructural and regulatory analysis

International Nuclear Information System (INIS)

Dorigoni, Susanna; Portatadino, Sergio

2008-01-01

In this paper, a cross-section infrastructural and regulatory analysis of the European LNG sector is presented. The LNG chain is maintained as being a good tool to enlarge the number of natural gas exporters to Europe, adding in this way to competition and to the achievement of the targets of the liberalisation process, which is a decrease in price for final customers and security of supply. The main reason for this is to be identified in the minor specificity of the regasification-plant-related investment compared with pipeline transportation. As a matter of fact, as the infrastructural analysis will show, the construction of new LNG receiving terminals is likely to bring about an increase in the number of importers fostering competition among them and shrinking their margins among the value chain. In this context, regulation is meant to play a key role in promoting investments without hindering competition. Nevertheless it is questionable whether LNG will be able to introduce competition beyond the European border (that is among producers) according to the forecasted supply and demand balance that is leading to a seller's market in the upstream sector. In this case, a huger part of the rent would go to the exporters leaving minor scope for competition down the European border. (author)

As to achieve regulatory action, regulatory approaches

International Nuclear Information System (INIS)

Cid, R.; Encinas, D.

2014-01-01

The achievement of the effectiveness in the performance of a nuclear regulatory body has been a permanent challenge in the recent history of nuclear regulation. In the post-Fukushima era this challenge is even more important. This article addresses the subject from two complementary points of view: the characteristics of an effective regulatory body and the regulatory approaches. This work is based on the most recent studies carried out by the Committee on Nuclear Regulatory Activities, CNRA (OECD/NEA), as well as on the experience of the Consejo de Seguridad Nuclear, CSN, the Spanish regulatory body. Rafael Cid is the representative of CSN in these project: Diego Encinas has participated in the study on regulatory approaches. (Author)

Statistical identification of gene association by CID in application of constructing ER regulatory network

Directory of Open Access Journals (Sweden)

Lien Huang-Chun

2009-03-01

Full Text Available Abstract Background A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating in silico inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID, is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs (X and their downstream genes (Y based on clinical data. More specifically, we use estrogen receptor α (ERα as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A. Results The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC, Student's t-test (STT, coefficient of determination (CoD, and mutual information (MI. When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y against a discrete variable (X, it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays. Conclusion CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the

Regulatory Impact Analysis: Amendments to the National Emission Standards for Hazardous Air Pollutants (NESHAP) and New Source Perofrmance Standards (NSPS) for the Portland Cement Manufacturing Industry Final Report

Science.gov (United States)

For the regulatory process, EPA is required to develop a regulatory impact analysis (RIA). This August 2010 RIA includes an economic impact analysis (EIA) and a small entity impacts analysis and documents the RIA methods and results for the 2010 rules

Annotation of metabolites from gas chromatography/atmospheric pressure chemical ionization tandem mass spectrometry data using an in silico generated compound database and MetFrag.

Science.gov (United States)

Ruttkies, Christoph; Strehmel, Nadine; Scheel, Dierk; Neumann, Steffen

2015-08-30

Gas chromatography (GC) coupled to atmospheric pressure chemical ionization quadrupole time-of-flight mass spectrometry (APCI-QTOFMS) is an emerging technology in metabolomics. Reference spectra for GC/APCI-MS/MS barely exist; therefore, in silico fragmentation approaches and structure databases are prerequisites for annotation. To expand the limited coverage of derivatised structures in structure databases, in silico derivatisation procedures are required. A cheminformatics workflow has been developed for in silico derivatisation of compounds found in KEGG and PubChem, and validated on the Golm Metabolome Database (GMD). To demonstrate this workflow, these in silico generated databases were applied together with MetFrag to APCI-MS/MS spectra acquired from GC/APCI-MS/MS profiles of Arabidopsis thaliana and Solanum tuberosum. The Metabolite-Likeness of the original candidate structure was included as additional scoring term aiming at candidate structures of natural origin. The validation of our in silico derivatisation workflow on the GMD showed a true positive rate of 94%. MetFrag was applied to two datasets. In silico derivatisation of the KEGG and PubChem database served as a candidate source. For both datasets the Metabolite-Likeness score improved the identification performance. The derivatised data sources have been included into the MetFrag web application for the annotation of GC/APCI-MS/MS spectra. We demonstrated that MetFrag can support the identification of components from GC/APCI-MS/MS profiles, especially in the (common) case where reference spectra are not available. This workflow can be easily adapted to other types of derivatisation and is freely accessible together with the generated structure databases. Copyright © 2015 John Wiley & Sons, Ltd.

Competencies Setup for Nuclear Regulatory Staff in Thailand

International Nuclear Information System (INIS)

Pingish, Panupong; Siripirom, Lopchai; Nakkaew, Pongpan; Manuwong, Theerapatt; Wongsamarn, Vichian

2010-01-01

Competencies setup for regulatory bodies oversee a research reactor and nuclear power reactors in Thailand, concentrating on staff development in areas of review and assessment, inspection and enforcement, authorization, and development of regulations and guides. The regulatory body in Thailand is the Bureau of Nuclear Safety Regulation (BNSR) which belongs to the Office of Atoms for Peace (OAP). The BNSR is divided into 4 groups according to the International Atomic Energy Agency (IAEA). These groups are the nuclear safety administration group, nuclear safety technical support group, nuclear safety assessment and licensing group, and the nuclear installations inspection group. Each group is divided into senior and junior positions. The competencies model was used for implementation of staff qualification, career planning and professional progression by BNSR. Competencies are related to knowledge, skills and attitudes (KSAs) needed to perform their job. A key issue is obtaining competencies for the regulatory bodies. The systematic approach to training (SAT) has been used in several countries for improvement regulator performance. The SAT contains 5 steps, including analysis, design, development, implementation and evaluation, to achieve competencies. The SAT provides a logical progression from the identification of competencies required to perform a job to the design, development and implementation of training using the competencies model. In the first step, BNSR performs an operating analysis of training needs assessment (TNA) by using gap analysis technique, as suggested by IAEA. Individual regulatory bodies address the gap using appropriate training program, after comparing the actual and desired competency profiles to determine the gap. This paper examines competencies setup for regulatory staff of BNSR as a result of gaps analysis to establish a scheme for design characteristics of regulatory staff and training courses, thereby enhancing the regulatory

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

Science.gov (United States)

Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

2009-11-01

Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

Integrated analysis of microRNA and gene expression profiles reveals a functional regulatory module associated with liver fibrosis.

Science.gov (United States)

Chen, Wei; Zhao, Wenshan; Yang, Aiting; Xu, Anjian; Wang, Huan; Cong, Min; Liu, Tianhui; Wang, Ping; You, Hong

2017-12-15

Liver fibrosis, characterized with the excessive accumulation of extracellular matrix (ECM) proteins, represents the final common pathway of chronic liver inflammation. Ever-increasing evidence indicates microRNAs (miRNAs) dysregulation has important implications in the different stages of liver fibrosis. However, our knowledge of miRNA-gene regulation details pertaining to such disease remains unclear. The publicly available Gene Expression Omnibus (GEO) datasets of patients suffered from cirrhosis were extracted for integrated analysis. Differentially expressed miRNAs (DEMs) and genes (DEGs) were identified using GEO2R web tool. Putative target gene prediction of DEMs was carried out using the intersection of five major algorithms: DIANA-microT, TargetScan, miRanda, PICTAR5 and miRWalk. Functional miRNA-gene regulatory network (FMGRN) was constructed based on the computational target predictions at the sequence level and the inverse expression relationships between DEMs and DEGs. DAVID web server was selected to perform KEGG pathway enrichment analysis. Functional miRNA-gene regulatory module was generated based on the biological interpretation. Internal connections among genes in liver fibrosis-related module were determined using String database. MiRNA-gene regulatory modules related to liver fibrosis were experimentally verified in recombinant human TGFβ1 stimulated and specific miRNA inhibitor treated LX-2 cells. We totally identified 85 and 923 dysregulated miRNAs and genes in liver cirrhosis biopsy samples compared to their normal controls. All evident miRNA-gene pairs were identified and assembled into FMGRN which consisted of 990 regulations between 51 miRNAs and 275 genes, forming two big sub-networks that were defined as down-network and up-network, respectively. KEGG pathway enrichment analysis revealed that up-network was prominently involved in several KEGG pathways, in which "Focal adhesion", "PI3K-Akt signaling pathway" and "ECM

Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy.

Science.gov (United States)

Blaženović, Ivana; Kind, Tobias; Torbašinović, Hrvoje; Obrenović, Slobodan; Mehta, Sajjan S; Tsugawa, Hiroshi; Wermuth, Tobias; Schauer, Nicolas; Jahn, Martina; Biedendieck, Rebekka; Jahn, Dieter; Fiehn, Oliver

2017-05-25

In mass spectrometry-based untargeted metabolomics, rarely more than 30% of the compounds are identified. Without the true identity of these molecules it is impossible to draw conclusions about the biological mechanisms, pathway relationships and provenance of compounds. The only way at present to address this discrepancy is to use in silico fragmentation software to identify unknown compounds by comparing and ranking theoretical MS/MS fragmentations from target structures to experimental tandem mass spectra (MS/MS). We compared the performance of four publicly available in silico fragmentation algorithms (MetFragCL, CFM-ID, MAGMa+ and MS-FINDER) that participated in the 2016 CASMI challenge. We found that optimizing the use of metadata, weighting factors and the manner of combining different tools eventually defined the ultimate outcomes of each method. We comprehensively analysed how outcomes of different tools could be combined and reached a final success rate of 93% for the training data, and 87% for the challenge data, using a combination of MAGMa+, CFM-ID and compound importance information along with MS/MS matching. Matching MS/MS spectra against the MS/MS libraries without using any in silico tool yielded 60% correct hits, showing that the use of in silico methods is still important.

Functional and topological characteristics of mammalian regulatory domains

Science.gov (United States)

Symmons, Orsolya; Uslu, Veli Vural; Tsujimura, Taro; Ruf, Sandra; Nassari, Sonya; Schwarzer, Wibke; Ettwiller, Laurence; Spitz, François

2014-01-01

Long-range regulatory interactions play an important role in shaping gene-expression programs. However, the genomic features that organize these activities are still poorly characterized. We conducted a large operational analysis to chart the distribution of gene regulatory activities along the mouse genome, using hundreds of insertions of a regulatory sensor. We found that enhancers distribute their activities along broad regions and not in a gene-centric manner, defining large regulatory domains. Remarkably, these domains correlate strongly with the recently described TADs, which partition the genome into distinct self-interacting blocks. Different features, including specific repeats and CTCF-binding sites, correlate with the transition zones separating regulatory domains, and may help to further organize promiscuously distributed regulatory influences within large domains. These findings support a model of genomic organization where TADs confine regulatory activities to specific but large regulatory domains, contributing to the establishment of specific gene expression profiles. PMID:24398455

Selective adsorption and ion exchange of metal cations and anions with silico-titanates and layered titanates

International Nuclear Information System (INIS)

Anthony, R.G.; Philip, C.V.

1993-01-01

Metal ions may be removed from aqueous wastes from metal processing plants and from refineries. They may also be used in concentrating radioactive elements found in dilute, aqueous, nuclear wastes. A new series of silico-titanates and alkali titanates are shown to have specific selectivity for cations of lead, mercury, and cadmium and the dichromate anion in solutions with low and high pH. Furthermore, one particular silico-titanate, TAM-5, was found to be highly selective for Cs + and Sr 2+ in solutions of 5.7 M Na + and 0.6 M Oh - . A high potential exists for these materials for removing Cs + and Sr 2+ from radioactive aqueous wastes containing high concentrations of Na + at high and low pH

In-Silico identification of peptides for the diagnostics of paratuberculosis

DEFF Research Database (Denmark)

Tang, Sheila Tuyet; Lund, Ole; Jungersen, Gregers

Identification of bovine MHC class II reactive peptides that are specific/unique to paratuberculosis and conserved across pathogenic variations of the paratuberculosis proteome will be of high value for development of new vaccines and immune based diagnostics. Here, we present an in silico screen...... by statistical significance. BMC Bioinformatics, 2003. 4: p. 21. 2. Nielsen, M., et al., Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan. PLoS Comput Biol, 2008. 4(7): p. e1000107....

A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.

Science.gov (United States)

Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet

2018-01-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.

Pharmacokinetics for regulatory risk analysis: the case of trichloroethylene.

Science.gov (United States)

Bogen, K T

1988-12-01

Physiologically based pharmacokinetic (PBPK) models describing the uptake, metabolism, and excretion of volatile organic compounds (VOCs) are now proposed for use in regulatory health-risk assessment. A steady-state analysis of one such model is shown to provide simple, convenient predicted relationships between an applied dose and the corresponding toxicologically effective, metabolized dose for certain VOCs like trichloroethylene (TCE). A version of this PBPK model was fit to data on human metabolism of TCE to urinary metabolites in chronically exposed workers, yielding a direct estimate of PBPK parameters governing human capacity to metabolize TCE. It is shown that this estimate is consistent with others based on experimental studies of TCE metabolism in humans exposed to TCE by inhalation for short periods. These results are applied to human cancer-risk assessment using rodent bioassay data on TCE-induced tumorigenesis.

UJI IN SILICO SENYAWA COUMESTROL SEBAGAI LIGAN RESEPTOR ESTROGEN ALFA

Directory of Open Access Journals (Sweden)

Felicia Felicia

2015-11-01

Full Text Available Breast cancer is a cancer caused by uncontrolled cell growth at breast tissue. One of the most common triggers of breast cancer is overexpression of estrogen receptor alpha (ERα. This research’s goal is to test the ability of coumestrol as the ligand of ERα with in silico method and to discover coumestrol’s binding pose inside the ERα’s binding pocket. Coumestrol’s ability as ERα’s ligand was tested using structure-based virtual screening (SVBS method by Setiawati et al. (2014 that had been modified by Istyastono (2015. Results analysis was done using decision tree generated from recursive partition and regression tree method (RPART. If coumestrol is a ligand based on decision tree, it is concluded that coumestrol is active as ligand of ERα. At the end of analysis, coumestrol’s pose inside ERα’s binding pocket was visualized using MacPyMol. From the test acknowledged that the smallest ChemPLP value of coumestrol’s pose was -83.1487. Coumestrol interacts with GLY420, ARG394, and GLU353 using hydrogen bonds. However, coumestrol were perceived as decoy according to decision tree. Hence, coumestrol could not be recognized as ERα’s ligand by the protocol. Therefore, development of proper protocol to indentify ligand for ERα is required.

Novel microRNA-like viral small regulatory RNAs arising during human hepatitis A virus infection.

Science.gov (United States)

Shi, Jiandong; Sun, Jing; Wang, Bin; Wu, Meini; Zhang, Jing; Duan, Zhiqing; Wang, Haixuan; Hu, Ningzhu; Hu, Yunzhang

2014-10-01

MicroRNAs (miRNAs), including host miRNAs and viral miRNAs, play vital roles in regulating host-virus interactions. DNA viruses encode miRNAs that regulate the viral life cycle. However, it is generally believed that cytoplasmic RNA viruses do not encode miRNAs, owing to inaccessible cellular miRNA processing machinery. Here, we provide a comprehensive genome-wide analysis and identification of miRNAs that were derived from hepatitis A virus (HAV; Hu/China/H2/1982), which is a typical cytoplasmic RNA virus. Using deep-sequencing and in silico approaches, we identified 2 novel virally encoded miRNAs, named hav-miR-1-5p and hav-miR-2-5p. Both of the novel virally encoded miRNAs were clearly detected in infected cells. Analysis of Dicer enzyme silencing demonstrated that HAV-derived miRNA biogenesis is Dicer dependent. Furthermore, we confirmed that HAV mature miRNAs were generated from viral miRNA precursors (pre-miRNAs) in host cells. Notably, naturally derived HAV miRNAs were biologically and functionally active and induced post-transcriptional gene silencing (PTGS). Genomic location analysis revealed novel miRNAs located in the coding region of the viral genome. Overall, our results show that HAV naturally generates functional miRNA-like small regulatory RNAs during infection. This is the first report of miRNAs derived from the coding region of genomic RNA of a cytoplasmic RNA virus. These observations demonstrate that a cytoplasmic RNA virus can naturally generate functional miRNAs, as DNA viruses do. These findings also contribute to improved understanding of host-RNA virus interactions mediated by RNA virus-derived miRNAs. © FASEB.

Advances in In Vitro and In Silico Tools for Toxicokinetic Dose ...

Science.gov (United States)

Recent advances in vitro assays, in silico tools, and systems biology approaches provide opportunities for refined mechanistic understanding for chemical safety assessment that will ultimately lead to reduced reliance on animal-based methods. With the U.S. commercial chemical landscape encompassing thousands of chemicals with limited data, safety assessment strategies that reliably predict in vivo systemic exposures and subsequent in vivo effects efficiently are a priority. Quantitative in vitro-in vivo extrapolation (QIVIVE) is a methodology that facilitates the explicit and quantitative application of in vitro experimental data and in silico modeling to predict in vivo system behaviors and can be applied to predict chemical toxicokinetics, toxicodynamics and also population variability. Tiered strategies that incorporate sufficient information to reliably inform the relevant decision context will facilitate acceptance of these alternative data streams for safety assessments. This abstract does not necessarily reflect U.S. EPA policy. This talk will provide an update to an international audience on the state of science being conducted within the EPA’s Office of Research and Development to develop and refine approaches that estimate internal chemical concentrations following a given exposure, known as toxicokinetics. Toxicokinetic approaches hold great potential in their ability to link in vitro activities or toxicities identified during high-throughput screen

Analysis of replies to an IAEA questionnaire on regulatory practices in Member States with nuclear power programmes

International Nuclear Information System (INIS)

1988-10-01

The survey of regulatory practices in Member States with nuclear power programmes by means of a questionnaire is the first stage of the programme developed by the IAEA to assist the Member States in the enhancement of their regulatory practices. The questionnaire, drafted by IAEA staff members and consultants, consisted of 120 detailed questions and its structure corresponds approximately to the Structure of Code on the Safety of Nuclear Power Plants: Governmental Organizations (IAEA Safety Series No. 50-C-G-Rev.1). The questionnaire was sent to 64 Member States on 7 July 1987 and the replies received from 44 Member States have been analysed by IAEA staff members with the assistance of two consultants in order to identify the main differences in approach and the important features of regulatory practices in Member States. This technical document is the summary report of this analysis

Nuclear reactor decommissioning: an analysis of the regulatory environments

International Nuclear Information System (INIS)

Cantor, R.

1984-04-01

The purpose of this study is to highlight some of the current and likely regulations that will significantly affect the costs, technical alternatives and financing schemes for reactor decommissioning encountered by electric utilities and their customers. The paper includes a general review of the decommissioning literature, as well as information on specific regulations at the federal, state, and utility levels. Available estimated costs for the decommissioning of individual reactors are also presented. Finally, classification of the specific policies into common trends and practices among the various regulatory bodies is used to examine more general regulatory environments and their potential financial implications

Molecular hybridization conceded exceptionally potent quinolinyl-oxadiazole hybrids through phenyl linked thiosemicarbazide antileishmanial scaffolds: In silico validation and SAR studies.

Science.gov (United States)

Taha, Muhammad; Ismail, Nor Hadiani; Ali, Muhammad; Rashid, Umer; Imran, Syahrul; Uddin, Nizam; Khan, Khalid Mohammed

2017-04-01

The high potential of quinoline containing natural products and their derivatives in medicinal chemistry led us to discover a novel series of compounds 6-23 based on the concept of molecular hybridization. Most of the synthesized analogues exhibited potent leishmanicidal potential. The most potent compound (23, IC 50 =0.10±0.001μM) among the series was found ∼70 times more lethal than the standard drug. The current series 6-23 conceded in the development of fourteen (14) extraordinarily active compounds against leishmaniasis. In silico analysis were also performed to probe the mode of action while all the compounds structure were established by NMR and Mass spectral analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

Resolution of contradiction between in silico predictions and Ames test results for four pharmaceutically relevant impurities.

Science.gov (United States)

Gunther, William C; Kenyon, Michelle O; Cheung, Jennifer R; Dugger, Robert W; Dobo, Krista L

2017-12-01

The ICH M7 Guideline requires low level control of mutagenic impurities in pharmaceutical products to minimize cancer risk in patients (ICHM7, 2014). Bacterial mutagenicity (Ames) data is generally used to determine mutagenic and possible carcinogenic potential of compounds. Recently, a publication on experiences of using two in silico systems to identify potentially mutagenic impurities highlighted the importance of performing a critical review of published Ames data utilized as part of a mutagenicity assessment of impurities (Greene et al., 2015). Four compounds (2-amino-5-hydroxybenzoic acid, 2-amino-3-chlorobenzoic acid, methyl 2-amino-4-chlorobenzoate and 4-morpholinopyridine) reported mutagenic were identified in a two system in silico assessment and expert review of the structuresas non-mutagenic. Likely reasons for mutagenicity could not be identified and the purity of the compounds tested was proposed. In the current investigation, the purest available sample of the four compounds was tested in an OECD-compliant Ames test. The compounds were all found to be non-mutagenic. Possible reasons for the discrepancy between previously reported and current results are discussed. Additionally, important points to consider when conducting an expert review of available Ames data are provided particularly in cases where reported Ames results are discrepant with a two system in silico assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

Stability analysis of delayed genetic regulatory networks with stochastic disturbances

Energy Technology Data Exchange (ETDEWEB)

Zhou Qi, E-mail: zhouqilhy@yahoo.com.c [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China); Xu Shengyuan [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China); Chen Bing [Institute of Complexity Science, Qingdao University, Qingdao 266071, Shandong (China); Li Hongyi [Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001 (China); Chu Yuming [Department of Mathematics, Huzhou Teacher' s College, Huzhou 313000, Zhejiang (China)

2009-10-05

This Letter considers the problem of stability analysis of a class of delayed genetic regulatory networks with stochastic disturbances. The delays are assumed to be time-varying and bounded. By utilizing Ito's differential formula and Lyapunov-Krasovskii functionals, delay-range-dependent and rate-dependent (rate-independent) stability criteria are proposed in terms of linear matrices inequalities. An important feature of the proposed results is that all the stability conditions are dependent on the upper and lower bounds of the delays. Another important feature is that the obtained stability conditions are less conservative than certain existing ones in the literature due to introducing some appropriate free-weighting matrices. A simulation example is employed to illustrate the applicability and effectiveness of the proposed methods.

In vitro antioxidant, antiinflammatory and in silico molecular docking studies of thiosemicarbazones

Science.gov (United States)

Subhashree, G. R.; Haribabu, J.; Saranya, S.; Yuvaraj, P.; Anantha Krishnan, D.; Karvembu, R.; Gayathri, D.

2017-10-01

A series of 5-methoxysalicylaldehyde appended thiosemicarbazones (1-4) and 2-hydroxy-1-naphthaldehyde appended thiosemicarbazones (5-8) was obtained from the reactions between 5-methoxysalicylaldehyde/2-hydroxy-1-naphthaldehyde and (un)substituted thiosemicarbazides with the view to ascertain their biological properties brought about by the change in substitution at N-terminal position of the thiosemicarbazide derivatives. The compounds were fully characterized by elemental analyses, and various spectroscopic techniques (UV-Visible, FT-IR, NMR and mass). The solid-state structure of three compounds (1, 2 and 7) was determined by single crystal X-ray diffraction method. The compounds (1, 2 and 7) have adopted a monoclinic crystal system with P21/c (1 and 2) or C2/c (7) space group. Antioxidant and non-haemolysis activities of the compounds (1-8) were analyzed by in vitro DPPH and haemolysis assays, respectively. Antiinflammatory potential was verified by in vitro PLA2 inhibition assay and in silico molecular docking study. In vitro and in silico studies revealed promising antiinflammatory potential of the thiosemicarbazone derivatives. Compounds 2, 4, 6, 7 and 8 showed significant antiinflammatory activity.

Freely Accessible Chemical Database Resources of Compounds for in Silico Drug Discovery.

Science.gov (United States)

Yang, JingFang; Wang, Di; Jia, Chenyang; Wang, Mengyao; Hao, GeFei; Yang, GuangFu

2018-05-07

In silico drug discovery has been proved to be a solidly established key component in early drug discovery. However, this task is hampered by the limitation of quantity and quality of compound databases for screening. In order to overcome these obstacles, freely accessible database resources of compounds have bloomed in recent years. Nevertheless, how to choose appropriate tools to treat these freely accessible databases are crucial. To the best of our knowledge, this is the first systematic review on this issue. The existed advantages and drawbacks of chemical databases were analyzed and summarized based on the collected six categories of freely accessible chemical databases from literature in this review. Suggestions on how and in which conditions the usage of these databases could be reasonable were provided. Tools and procedures for building 3D structure chemical libraries were also introduced. In this review, we described the freely accessible chemical database resources for in silico drug discovery. In particular, the chemical information for building chemical database appears as attractive resources for drug design to alleviate experimental pressure. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

CAPSAICIN: ITS BIOLOGICAL ACTIVITIES AND IN SILICO TARGET FISHING.

Science.gov (United States)

Akhtar, Fahad; Muhammad Sharif, Hajra; Arshad Mallick, Muhammad; Zahoor, Fareeha; Abdulmalik, Attiya; Baig, Warda; Shujaat, Nodia; Gul, Sundas; Bibi, Gulfam; Ramzan, Rahdia; Murtaza, Ghulam

2017-03-01

Capsicum annuum L. is a rich source of capsaicin, an alkaloid, which is a very pungent compound. Due to ever growing need of capsaicin, an extensive research on its efficient cultivation as well as chemical synthesis is underway. Owing to the pungent nature of capsaicin, its analogous molecules without pungent effect are being explored. The objective of this descriptive review is to comprehensively present the updates on the bioactivities of capsaicin. Additionally, the in silico target fishing approach has been used to identify the possible protein targets of capsaicin. This article will definitely provide future perspectives of research on capsaicin.

In Silico Modeling of Novel Drug Ligands for Treatment of Concussion Associated Tauopathy.

Science.gov (United States)

Zhao, Wei; Ho, Lap; Wang, Jun; Bi, Weina; Yemul, Shrishailam; Ward, Libby; Freire, Daniel; Mazzola, Paolo; Brathwaite, Justin; Mezei, Mihaly; Sanchez, Roberto; Elder, Gregory A; Pasinetti, Giulio Maria

2016-10-01

The objective of this study was to develop an in silico screening model for characterization of potential novel ligands from commercial drug libraries able to functionally activate certain olfactory receptors (ORs), which are members of the class A rhodopsin-like family of G protein couple receptors (GPCRs), in the brain of murine models of concussion. We previously found that concussions may significantly influence expression of certain ORs, for example, OR4M1 in subjects with a history of concussion/traumatic brain injury (TBI). In this study, we built a 3-D OR4M1 model and used it in in silico screening of potential novel ligands from commercial drug libraries. We report that in vitro activation of OR4M1 with the commercially available ZINC library compound 10915775 led to a significant attenuation of abnormal tau phosphorylation in embryonic cortico-hippocampal neuronal cultures derived from NSE-OR4M1 transgenic mice, possibly through modulation of the JNK signaling pathway. The attenuation of abnormal tau phosphorylation was rather selective since ZINC10915775 significantly decreased tau phosphorylation on tau Ser202/T205 (AT8 epitope) and tau Thr212/Ser214 (AT100 epitope), but not on tau Ser396/404 (PHF-1 epitope). Moreover, no response of ZINC10915775 was found in control hippocampal neuronal cultures derived from wild type littermates. Our in silico model provides novel means to pharmacologically modulate select ubiquitously expressed ORs in the brain through high affinity ligand activation to prevent and eventually to treat concussion induced down regulation of ORs and subsequent cascade of tau pathology. J. Cell. Biochem. 117: 2241-2248, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Gastrointestinal Endogenous Proteins as a Source of Bioactive Peptides - An In Silico Study

Science.gov (United States)

Dave, Lakshmi A.; Montoya, Carlos A.; Rutherfurd, Shane M.; Moughan, Paul J.

2014-01-01

Dietary proteins are known to contain bioactive peptides that are released during digestion. Endogenous proteins secreted into the gastrointestinal tract represent a quantitatively greater supply of protein to the gut lumen than those of dietary origin. Many of these endogenous proteins are digested in the gastrointestinal tract but the possibility that these are also a source of bioactive peptides has not been considered. An in silico prediction method was used to test if bioactive peptides could be derived from the gastrointestinal digestion of gut endogenous proteins. Twenty six gut endogenous proteins and seven dietary proteins were evaluated. The peptides present after gastric and intestinal digestion were predicted based on the amino acid sequence of the proteins and the known specificities of the major gastrointestinal proteases. The predicted resultant peptides possessing amino acid sequences identical to those of known bioactive peptides were identified. After gastrointestinal digestion (based on the in silico simulation), the total number of bioactive peptides predicted to be released ranged from 1 (gliadin) to 55 (myosin) for the selected dietary proteins and from 1 (secretin) to 39 (mucin-5AC) for the selected gut endogenous proteins. Within the intact proteins and after simulated gastrointestinal digestion, angiotensin converting enzyme (ACE)-inhibitory peptide sequences were the most frequently observed in both the dietary and endogenous proteins. Among the dietary proteins, after in silico simulated gastrointestinal digestion, myosin was found to have the highest number of ACE-inhibitory peptide sequences (49 peptides), while for the gut endogenous proteins, mucin-5AC had the greatest number of ACE-inhibitory peptide sequences (38 peptides). Gut endogenous proteins may be an important source of bioactive peptides in the gut particularly since gut endogenous proteins represent a quantitatively large and consistent source of protein. PMID:24901416

Gastrointestinal endogenous proteins as a source of bioactive peptides--an in silico study.

Science.gov (United States)

Dave, Lakshmi A; Montoya, Carlos A; Rutherfurd, Shane M; Moughan, Paul J

2014-01-01

Dietary proteins are known to contain bioactive peptides that are released during digestion. Endogenous proteins secreted into the gastrointestinal tract represent a quantitatively greater supply of protein to the gut lumen than those of dietary origin. Many of these endogenous proteins are digested in the gastrointestinal tract but the possibility that these are also a source of bioactive peptides has not been considered. An in silico prediction method was used to test if bioactive peptides could be derived from the gastrointestinal digestion of gut endogenous proteins. Twenty six gut endogenous proteins and seven dietary proteins were evaluated. The peptides present after gastric and intestinal digestion were predicted based on the amino acid sequence of the proteins and the known specificities of the major gastrointestinal proteases. The predicted resultant peptides possessing amino acid sequences identical to those of known bioactive peptides were identified. After gastrointestinal digestion (based on the in silico simulation), the total number of bioactive peptides predicted to be released ranged from 1 (gliadin) to 55 (myosin) for the selected dietary proteins and from 1 (secretin) to 39 (mucin-5AC) for the selected gut endogenous proteins. Within the intact proteins and after simulated gastrointestinal digestion, angiotensin converting enzyme (ACE)-inhibitory peptide sequences were the most frequently observed in both the dietary and endogenous proteins. Among the dietary proteins, after in silico simulated gastrointestinal digestion, myosin was found to have the highest number of ACE-inhibitory peptide sequences (49 peptides), while for the gut endogenous proteins, mucin-5AC had the greatest number of ACE-inhibitory peptide sequences (38 peptides). Gut endogenous proteins may be an important source of bioactive peptides in the gut particularly since gut endogenous proteins represent a quantitatively large and consistent source of protein.

Meal Disturbance Effect on Control of Blood Glucose Level for Critically-ill Patients using In-silico Works

Science.gov (United States)

Yusof, N. F. M.; Som, A. M.; Ali, S. A.; Azman, N. H.

2018-05-01

This study was conducted to determine the effect of meal disturbance on blood glucose level of the critically ill patients and to simulate the control algorithm previously developed using in-silico works. The study is significant so as to reduce the mortality rate of critically ill patients who usually encounter hyperglycaemia or/and hypoglycaemia while in treatment. The meal intake is believed to affect the blood glucose regulation and causes the hyperglycaemia to occur. Critically ill patients receive their meal through parenteral and enteral nutrition. Furthermore, by using in-silico works, time consumed and resources needed for clinical evaluation of the patients can be reduced. Hovorka model was employed in which the simulation study was carried out using MATLAB on the virtual patient and it was being compared with actual patient in which the data were provided by Institut Jantung Negara (IJN). Based on the simulation, the disturbance on enteral glucose supplied had affected the blood glucose level of the patient; however, it remained unchanged for the parental glucose. To reduce the occurrence of hypoglycaemia and hyperglycaemia, the patient was injected with 30 g/hr and 10 g/hr of enteral glucose, respectively. In conclusion, the disturbance of meal received can be controlled through in-silico works.

Genome-wide analysis of the regulatory function mediated by the small regulatory psm-mec RNA of methicillin-resistant Staphylococcus aureus.

Science.gov (United States)

Cheung, Gordon Y C; Villaruz, Amer E; Joo, Hwang-Soo; Duong, Anthony C; Yeh, Anthony J; Nguyen, Thuan H; Sturdevant, Daniel E; Queck, S Y; Otto, M

2014-07-01

Several methicillin resistance (SCCmec) clusters characteristic of hospital-associated methicillin-resistant Staphylococcus aureus (MRSA) strains harbor the psm-mec locus. In addition to encoding the cytolysin, phenol-soluble modulin (PSM)-mec, this locus has been attributed gene regulatory functions. Here we employed genome-wide transcriptional profiling to define the regulatory function of the psm-mec locus. The immune evasion factor protein A emerged as the primary conserved and strongly regulated target of psm-mec, an effect we show is mediated by the psm-mec RNA. Furthermore, the psm-mec locus exerted regulatory effects that were more moderate in extent. For example, expression of PSM-mec limited expression of mecA, thereby decreasing methicillin resistance. Our study shows that the psm-mec locus has a rare dual regulatory RNA and encoded cytolysin function. Furthermore, our findings reveal a specific mechanism underscoring the recently emerging concept that S. aureus strains balance pronounced virulence and high expression of antibiotic resistance. Published by Elsevier GmbH.

Data Quality Objectives for Regulatory Requirements for Hazardous and Radioactive Air Emissions Sampling and Analysis

Energy Technology Data Exchange (ETDEWEB)

MULKEY, C.H.

1999-07-06

This document describes the results of the data quality objective (DQO) process undertaken to define data needs for state and federal requirements associated with toxic, hazardous, and/or radiological air emissions under the jurisdiction of the River Protection Project (RPP). Hereafter, this document is referred to as the Air DQO. The primary drivers for characterization under this DQO are the regulatory requirements pursuant to Washington State regulations, that may require sampling and analysis. The federal regulations concerning air emissions are incorporated into the Washington State regulations. Data needs exist for nonradioactive and radioactive waste constituents and characteristics as identified through the DQO process described in this document. The purpose is to identify current data needs for complying with regulatory drivers for the measurement of air emissions from RPP facilities in support of air permitting. These drivers include best management practices; similar analyses may have more than one regulatory driver. This document should not be used for determining overall compliance with regulations because the regulations are in constant change, and this document may not reflect the latest regulatory requirements. Regulatory requirements are also expected to change as various permits are issued. Data needs require samples for both radionuclides and nonradionuclide analytes of air emissions from tanks and stored waste containers. The collection of data is to support environmental permitting and compliance, not for health and safety issues. This document does not address health or safety regulations or requirements (those of the Occupational Safety and Health Administration or the National Institute of Occupational Safety and Health) or continuous emission monitoring systems. This DQO is applicable to all equipment, facilities, and operations under the jurisdiction of RPP that emit or have the potential to emit regulated air pollutants.

Data Quality Objectives for Regulatory Requirements for Hazardous and Radioactive Air Emissions Sampling and Analysis

International Nuclear Information System (INIS)

MULKEY, C.H.

1999-01-01

This document describes the results of the data quality objective (DQO) process undertaken to define data needs for state and federal requirements associated with toxic, hazardous, and/or radiological air emissions under the jurisdiction of the River Protection Project (RPP). Hereafter, this document is referred to as the Air DQO. The primary drivers for characterization under this DQO are the regulatory requirements pursuant to Washington State regulations, that may require sampling and analysis. The federal regulations concerning air emissions are incorporated into the Washington State regulations. Data needs exist for nonradioactive and radioactive waste constituents and characteristics as identified through the DQO process described in this document. The purpose is to identify current data needs for complying with regulatory drivers for the measurement of air emissions from RPP facilities in support of air permitting. These drivers include best management practices; similar analyses may have more than one regulatory driver. This document should not be used for determining overall compliance with regulations because the regulations are in constant change, and this document may not reflect the latest regulatory requirements. Regulatory requirements are also expected to change as various permits are issued. Data needs require samples for both radionuclides and nonradionuclide analytes of air emissions from tanks and stored waste containers. The collection of data is to support environmental permitting and compliance, not for health and safety issues. This document does not address health or safety regulations or requirements (those of the Occupational Safety and Health Administration or the National Institute of Occupational Safety and Health) or continuous emission monitoring systems. This DQO is applicable to all equipment, facilities, and operations under the jurisdiction of RPP that emit or have the potential to emit regulated air pollutants

Advanced Reactor Technologies - Regulatory Technology Development Plan (RTDP)

Energy Technology Data Exchange (ETDEWEB)

Moe, Wayne L. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2017-08-23

This DOE-NE Advanced Small Modular Reactor (AdvSMR) regulatory technology development plan (RTDP) will link critical DOE nuclear reactor technology development programs to important regulatory and policy-related issues likely to impact a “critical path” for establishing a viable commercial AdvSMR presence in the domestic energy market. Accordingly, the regulatory considerations that are set forth in the AdvSMR RTDP will not be limited to any one particular type or subset of advanced reactor technology(s) but rather broadly consider potential regulatory approaches and the licensing implications that accompany all DOE-sponsored research and technology development activity that deal with commercial non-light water reactors. However, it is also important to remember that certain “minimum” levels of design and safety approach knowledge concerning these technology(s) must be defined and available to an extent that supports appropriate pre-licensing regulatory analysis within the RTDP. Final resolution to advanced reactor licensing issues is most often predicated on the detailed design information and specific safety approach as documented in a facility license application and submitted for licensing review. Because the AdvSMR RTDP is focused on identifying and assessing the potential regulatory implications of DOE-sponsored reactor technology research very early in the pre-license application development phase, the information necessary to support a comprehensive regulatory analysis of a new reactor technology, and the resolution of resulting issues, will generally not be available. As such, the regulatory considerations documented in the RTDP should be considered an initial “first step” in the licensing process which will continue until a license is issued to build and operate the said nuclear facility. Because a facility license application relies heavily on the data and information generated by technology development studies, the anticipated regulatory

Advanced Reactor Technology -- Regulatory Technology Development Plan (RTDP)

Energy Technology Data Exchange (ETDEWEB)

Moe, Wayne Leland [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-05-01

This DOE-NE Advanced Small Modular Reactor (AdvSMR) regulatory technology development plan (RTDP) will link critical DOE nuclear reactor technology development programs to important regulatory and policy-related issues likely to impact a “critical path” for establishing a viable commercial AdvSMR presence in the domestic energy market. Accordingly, the regulatory considerations that are set forth in the AdvSMR RTDP will not be limited to any one particular type or subset of advanced reactor technology(s) but rather broadly consider potential regulatory approaches and the licensing implications that accompany all DOE-sponsored research and technology development activity that deal with commercial non-light water reactors. However, it is also important to remember that certain “minimum” levels of design and safety approach knowledge concerning these technology(s) must be defined and available to an extent that supports appropriate pre-licensing regulatory analysis within the RTDP. Final resolution to advanced reactor licensing issues is most often predicated on the detailed design information and specific safety approach as documented in a facility license application and submitted for licensing review. Because the AdvSMR RTDP is focused on identifying and assessing the potential regulatory implications of DOE-sponsored reactor technology research very early in the pre-license application development phase, the information necessary to support a comprehensive regulatory analysis of a new reactor technology, and the resolution of resulting issues, will generally not be available. As such, the regulatory considerations documented in the RTDP should be considered an initial “first step” in the licensing process which will continue until a license is issued to build and operate the said nuclear facility. Because a facility license application relies heavily on the data and information generated by technology development studies, the anticipated regulatory

In Silico Approach for Prediction of Antifungal Peptides

Directory of Open Access Journals (Sweden)

Piyush Agrawal

2018-02-01

Full Text Available This paper describes in silico models developed using a wide range of peptide features for predicting antifungal peptides (AFPs. Our analyses indicate that certain types of residue (e.g., C, G, H, K, R, Y are more abundant in AFPs. The positional residue preference analysis reveals the prominence of the particular type of residues (e.g., R, V, K at N-terminus and a certain type of residues (e.g., C, H at C-terminus. In this study, models have been developed for predicting AFPs using a wide range of peptide features (like residue composition, binary profile, terminal residues. The support vector machine based model developed using compositional features of peptides achieved maximum accuracy of 88.78% on the training dataset and 83.33% on independent or validation dataset. Our model developed using binary patterns of terminal residues of peptides achieved maximum accuracy of 84.88% on training and 84.64% on validation dataset. We benchmark models developed in this study and existing methods on a dataset containing compositionally similar antifungal and non-AFPs. It was observed that binary based model developed in this study preforms better than any model/method. In order to facilitate scientific community, we developed a mobile app, standalone and a user-friendly web server ‘Antifp’ (http://webs.iiitd.edu.in/raghava/antifp.

Giving Drugs a Second Chance: Overcoming Regulatory and Financial Hurdles in Repurposing Approved Drugs As Cancer Therapeutics.

Science.gov (United States)

Hernandez, J Javier; Pryszlak, Michael; Smith, Lindsay; Yanchus, Connor; Kurji, Naheed; Shahani, Vijay M; Molinski, Steven V

2017-01-01

The repositioning or "repurposing" of existing therapies for alternative disease indications is an attractive approach that can save significant investments of time and money during drug development. For cancer indications, the primary goal of repurposed therapies is on efficacy, with less restriction on safety due to the immediate need to treat this patient population. This report provides a high-level overview of how drug developers pursuing repurposed assets have previously navigated funding efforts, regulatory affairs, and intellectual property laws to commercialize these "new" medicines in oncology. This article provides insight into funding programs (e.g., government grants and philanthropic organizations) that academic and corporate initiatives can leverage to repurpose drugs for cancer. In addition, we highlight previous examples where secondary uses of existing, Food and Drug Administration- or European Medicines Agency-approved therapies have been predicted in silico and successfully validated in vitro and/or in vivo (i.e., animal models and human clinical trials) for certain oncology indications. Finally, we describe the strategies that the pharmaceutical industry has previously employed to navigate regulatory considerations and successfully commercialize their drug products. These factors must be carefully considered when repurposing existing drugs for cancer to best benefit patients and drug developers alike.

Giving Drugs a Second Chance: Overcoming Regulatory and Financial Hurdles in Repurposing Approved Drugs As Cancer Therapeutics

Directory of Open Access Journals (Sweden)

J. Javier Hernandez

2017-11-01

Full Text Available The repositioning or “repurposing” of existing therapies for alternative disease indications is an attractive approach that can save significant investments of time and money during drug development. For cancer indications, the primary goal of repurposed therapies is on efficacy, with less restriction on safety due to the immediate need to treat this patient population. This report provides a high-level overview of how drug developers pursuing repurposed assets have previously navigated funding efforts, regulatory affairs, and intellectual property laws to commercialize these “new” medicines in oncology. This article provides insight into funding programs (e.g., government grants and philanthropic organizations that academic and corporate initiatives can leverage to repurpose drugs for cancer. In addition, we highlight previous examples where secondary uses of existing, Food and Drug Administration- or European Medicines Agency-approved therapies have been predicted in silico and successfully validated in vitro and/or in vivo (i.e., animal models and human clinical trials for certain oncology indications. Finally, we describe the strategies that the pharmaceutical industry has previously employed to navigate regulatory considerations and successfully commercialize their drug products. These factors must be carefully considered when repurposing existing drugs for cancer to best benefit patients and drug developers alike.

An integrated dataset for in silico drug discovery

Directory of Open Access Journals (Sweden)

Cockell Simon J

2010-12-01

Full Text Available Drug development is expensive and prone to failure. It is potentially much less risky and expensive to reuse a drug developed for one condition for treating a second disease, than it is to develop an entirely new compound. Systematic approaches to drug repositioning are needed to increase throughput and find candidates more reliably. Here we address this need with an integrated systems biology dataset, developed using the Ondex data integration platform, for the in silico discovery of new drug repositioning candidates. We demonstrate that the information in this dataset allows known repositioning examples to be discovered. We also propose a means of automating the search for new treatment indications of existing compounds.

Development of highly reliable in silico SNP resource and genotyping assay from exome capture and sequencing: an example from black spruce (Picea mariana).

Science.gov (United States)

Pavy, Nathalie; Gagnon, France; Deschênes, Astrid; Boyle, Brian; Beaulieu, Jean; Bousquet, Jean

2016-03-01

Picea mariana is a widely distributed boreal conifer across Canada and the subject of advanced breeding programmes for which population genomics and genomic selection approaches are being developed. Targeted sequencing was achieved after capturing P. mariana exome with probes designed from the sequenced transcriptome of Picea glauca, a distant relative. A high capture efficiency of 75.9% was reached although spruce has a complex and large genome including gene sequences interspersed by some long introns. The results confirmed the relevance of using probes from congeneric species to perform successfully interspecific exome capture in the genus Picea. A bioinformatics pipeline was developed including stringent criteria that helped detect a set of 97,075 highly reliable in silico SNPs. These SNPs were distributed across 14,909 genes. Part of an Infinium iSelect array was used to estimate the rate of true positives by validating 4267 of the predicted in silico SNPs by genotyping trees from P. mariana populations. The true positive rate was 96.2% for in silico SNPs, compared to a genotyping success rate of 96.7% for a set 1115 P. mariana control SNPs recycled from previous genotyping arrays. These results indicate the high success rate of the genotyping array and the relevance of the selection criteria used to delineate the new P. mariana in silico SNP resource. Furthermore, in silico SNPs were generally of medium to high frequency in natural populations, thus providing high informative value for future population genomics applications. © 2015 John Wiley & Sons Ltd.

A canonical correlation analysis-based dynamic bayesian network prior to infer gene regulatory networks from multiple types of biological data.

Science.gov (United States)

Baur, Brittany; Bozdag, Serdar

2015-04-01

One of the challenging and important computational problems in systems biology is to infer gene regulatory networks (GRNs) of biological systems. Several methods that exploit gene expression data have been developed to tackle this problem. In this study, we propose the use of copy number and DNA methylation data to infer GRNs. We developed an algorithm that scores regulatory interactions between genes based on canonical correlation analysis. In this algorithm, copy number or DNA methylation variables are treated as potential regulator variables, and expression variables are treated as potential target variables. We first validated that the canonical correlation analysis method is able to infer true interactions in high accuracy. We showed that the use of DNA methylation or copy number datasets leads to improved inference over steady-state expression. Our results also showed that epigenetic and structural information could be used to infer directionality of regulatory interactions. Additional improvements in GRN inference can be gleaned from incorporating the result in an informative prior in a dynamic Bayesian algorithm. This is the first study that incorporates copy number and DNA methylation into an informative prior in dynamic Bayesian framework. By closely examining top-scoring interactions with different sources of epigenetic or structural information, we also identified potential novel regulatory interactions.

In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria

KAUST Repository

Motwalli, Olaa Amin; Essack, Magbubah; Jankovic, Boris R.; Ji, Boyang; Liu, Xinyao; Ansari, Hifzur Rahman; Hoehndorf, Robert; Gao, Xin; Arold, Stefan T.; Mineta, Katsuhiko; Archer, John A.C.; Gojobori, Takashi; Mijakovic, Ivan; Bajic, Vladimir B.

2017-01-01

To our knowledge FFASC is the first in silico method to screen cyanobacteria proteomes for their potential to produce and excrete FFA, as well as the first attempt to parameterize the criteria derived from genetic characteristics that are favorable/non-favorable for this purpose. Thus, FFASC helps focus experimental evaluation only on the most promising cyanobacteria.

La vía de transducción de señales TOR de mamíferos está presente en Trypanosoma cruzi: Reconstrucción in silico y posibles funciones The mammalian TOR pathway is present in Trypanosoma cruzi: In silico reconstruction and possible functions

Directory of Open Access Journals (Sweden)

Fabio A. Digirolamo

2012-06-01

Full Text Available La vía TOR ("Target Of Rapamycin" de mamíferos es una red proteica de regulación para una amplia gama de procesos involucrados en el crecimiento y la diferenciación celular, constituyendo un interruptor funcional entre el metabolismo anabólico y catabólico de la célula. El Trypanosoma cruzi, agente etiológico de la enfermedad de Chagas, tiene un ciclo de vida muy complejo con diferentes estadios morfológicos en varios hospedadores. Este ciclo de vida implica que los parásitos enfrentan grandes fluctuaciones en el medio extracelular que deben ser detectadas y a las cuales deben responder adaptando su metabolismo. Un candidato a ser el mediador entre los receptores/sensores del medio y la respuesta adaptativa celular es la vía TOR. En este trabajo integramos los datos bibliográficos de la vía TOR de organismos tripanosomátidos con un análisis in silico (simulación computacional de procesos o estructuras biológicas del genoma del parásito. Se proponen además posibles efectores y procesos regulados por esta ruta metabólica. Teniendo en cuenta que existe muy poca información sobre los mecanismos de transducción de señales en tripanosomátidos, consideramos que el mapa presentado en este trabajo puede ser una referencia para futuros trabajos experimentales.The mammalian TOR pathway ("Target Of Rapamycin" is a regulatory protein network involved in a wide range of processes including cell growth and differentiation, providing a functional switch between anabolic and catabolic cell metabolism. Trypanosoma cruzi, the etiologic agent of Chagas disease, has a complex life cycle with different morphological stages in various hosts. This life cycle implies that parasites have to deal with fluctuations in the extracellular medium that should be detected and counteracted adapting their metabolism. A candidate to be the mediator between the receptors / sensors of the environment and cellular adaptive response is the TOR pathway. In this

76 FR 32878 - Draft Regulatory Guide: Issuance, Availability

Science.gov (United States)

2011-06-07

...: Mekonen [email protected] . SUPPLEMENTARY INFORMATION: I. Introduction The U.S. Nuclear Regulatory..., the public can gain entry into ADAMS, which provides text and image files of the NRC's [email protected] . The Regulatory Analysis is available electronically under ADAMS Accession Number...

Reactor aging research. United States Nuclear Regulatory Commission

International Nuclear Information System (INIS)

Vassilaros, M.G.

1998-01-01

The reactor ageing research activities in USA described, are focused on the research of reactor vessel integrity, including regulatory issues and technical aspects. Current emphasis are described for fracture analysis, embrittlement research, inspection capabilities, validation od annealing rule, revision of regulatory guide

In silico fragmentation for computer assisted identification of metabolite mass spectra

Directory of Open Access Journals (Sweden)

Müller-Hannemann Matthias

2010-03-01

Full Text Available Abstract Background Mass spectrometry has become the analytical method of choice in metabolomics research. The identification of unknown compounds is the main bottleneck. In addition to the precursor mass, tandem MS spectra carry informative fragment peaks, but the coverage of spectral libraries of measured reference compounds are far from covering the complete chemical space. Compound libraries such as PubChem or KEGG describe a larger number of compounds, which can be used to compare their in silico fragmentation with spectra of unknown metabolites. Results We created the MetFrag suite to obtain a candidate list from compound libraries based on the precursor mass, subsequently ranked by the agreement between measured and in silico fragments. In the evaluation MetFrag was able to rank most of the correct compounds within the top 3 candidates returned by an exact mass query in KEGG. Compared to a previously published study, MetFrag obtained better results than the commercial MassFrontier software. Especially for large compound libraries, the candidates with a good score show a high structural similarity or just different stereochemistry, a subsequent clustering based on chemical distances reduces this redundancy. The in silico fragmentation requires less than a second to process a molecule, and MetFrag performs a search in KEGG or PubChem on average within 30 to 300 seconds, respectively, on an average desktop PC. Conclusions We presented a method that is able to identify small molecules from tandem MS measurements, even without spectral reference data or a large set of fragmentation rules. With today's massive general purpose compound libraries we obtain dozens of very similar candidates, which still allows a confident estimate of the correct compound class. Our tool MetFrag improves the identification of unknown substances from tandem MS spectra and delivers better results than comparable commercial software. MetFrag is available through a web

In silico serine β-lactamases analysis reveals a huge potential resistome in environmental and pathogenic species.

Science.gov (United States)

Brandt, Christian; Braun, Sascha D; Stein, Claudia; Slickers, Peter; Ehricht, Ralf; Pletz, Mathias W; Makarewicz, Oliwia

2017-02-24

The secretion of antimicrobial compounds is an ancient mechanism with clear survival benefits for microbes competing with other microorganisms. Consequently, mechanisms that confer resistance are also ancient and may represent an underestimated reservoir in environmental bacteria. In this context, β-lactamases (BLs) are of great interest due to their long-term presence and diversification in the hospital environment, leading to the emergence of Gram-negative pathogens that are resistant to cephalosporins (extended spectrum BLs = ESBLs) and carbapenems (carbapenemases). In the current study, protein sequence databases were used to analyze BLs, and the results revealed a substantial number of unknown and functionally uncharacterized BLs in a multitude of environmental and pathogenic species. Together, these BLs represent an uncharacterized reservoir of potentially transferable resistance genes. Considering all available data, in silico approaches appear to more adequately reflect a given resistome than analyses of limited datasets. This approach leads to a more precise definition of BL clades and conserved motifs. Moreover, it may support the prediction of new resistance determinants and improve the tailored development of robust molecular diagnostics.

In Silico Analysis of the Regulation of the Photosynthetic Electron Transport Chain in C3 Plants1[OPEN

Science.gov (United States)

Kramer, David M.

2018-01-01

We present a new simulation model of the reactions in the photosynthetic electron transport chain of C3 species. We show that including recent insights about the regulation of the thylakoid proton motive force, ATP/NADPH balancing mechanisms (cyclic and noncyclic alternative electron transport), and regulation of Rubisco activity leads to emergent behaviors that may affect the operation and regulation of photosynthesis under different dynamic environmental conditions. The model was parameterized with experimental results in the literature, with a focus on Arabidopsis (Arabidopsis thaliana). A dataset was constructed from multiple sources, including measurements of steady-state and dynamic gas exchange, chlorophyll fluorescence, and absorbance spectroscopy under different light intensities and CO2, to test predictions of the model under different experimental conditions. Simulations suggested that there are strong interactions between cyclic and noncyclic alternative electron transport and that an excess capacity for alternative electron transport is required to ensure adequate redox state and lumen pH. Furthermore, the model predicted that, under specific conditions, reduction of ferredoxin by plastoquinol is possible after a rapid increase in light intensity. Further analysis also revealed that the relationship between ATP synthesis and proton motive force was highly regulated by the concentrations of ATP, ADP, and inorganic phosphate, and this facilitated an increase in nonphotochemical quenching and proton motive force under conditions where metabolism was limiting, such as low CO2, high light intensity, or combined high CO2 and high light intensity. The model may be used as an in silico platform for future research on the regulation of photosynthetic electron transport. PMID:28924017

A comparative survey of chemistry-driven in silico methods to identify hazardous substances under REACH

NARCIS (Netherlands)

Nendza, M.; Gabbert, S.G.M.; Kühne, R.; Lombardo, A.; Roncaglioni, A.; Benfenati, E.; Benigi, R.; Bossa, C.; Strempel, S.; Scheringer, M.; Fernandez, A.; Rallo, R.; Giralt, F.; Dimitrov, S.; Mekenyan, O.; Bringezu, F.; Schüürmann, G.

2013-01-01

This paper presents an inventory of in silico screening tools to identify substance properties of concern under the European chemicals’ legislation REACH. The objective is to support the selection and implementation of appropriate tools as building blocks within integrated testing strategies (ITS).

78 FR 1634 - Regulatory Agenda

Science.gov (United States)

2013-01-08

... amendments include updates to organizational information, use of the term ``disability'' in lieu of the term.../00/13 Regulatory Flexibility Analysis Required: No. Agency Contact: Robert W. Cosgrove, External...

78 FR 44329 - Regulatory Agenda

Science.gov (United States)

2013-07-23

... amendments include updates to organizational information, use of the term ``disability'' in lieu of the term.../00/13 Regulatory Flexibility Analysis Required: No. Agency Contact: Robert W. Cosgrove, External...

The Virtual Anemia Trial: An Assessment of Model‐Based In Silico Clinical Trials of Anemia Treatment Algorithms in Patients With Hemodialysis

Science.gov (United States)

Topping, Alice; Kappel, Franz; Thijssen, Stephan; Kotanko, Peter

2018-01-01

In silico approaches have been proposed as a novel strategy to increase the repertoire of clinical trial designs. Realistic simulations of clinical trials can provide valuable information regarding safety and limitations of treatment protocols and have been shown to assist in the cost‐effective planning of clinical studies. In this report, we present a blueprint for the stepwise integration of internal, external, and ecological validity considerations in virtual clinical trials (VCTs). We exemplify this approach in the context of a model‐based in silico clinical trial aimed at anemia treatment in patients undergoing hemodialysis (HD). Hemoglobin levels and subsequent anemia treatment were simulated on a per patient level over the course of a year and compared to real‐life clinical data of 79,426 patients undergoing HD. The novel strategies presented here, aimed to improve external and ecological validity of a VCT, significantly increased the predictive power of the discussed in silico trial. PMID:29368434

In-silico analysis of cis-acting regulatory elements of pathogenesis-related proteins of Arabidopsis thaliana and Oryza sativa.

Science.gov (United States)

Kaur, Amritpreet; Pati, Pratap Kumar; Pati, Aparna Maitra; Nagpal, Avinash Kaur

2017-01-01

Pathogenesis related (PR) proteins are low molecular weight family of proteins induced in plants under various biotic and abiotic stresses. They play an important role in plant-defense mechanism. PRs have wide range of functions, acting as hydrolases, peroxidases, chitinases, anti-fungal, protease inhibitors etc. In the present study, an attempt has been made to analyze promoter regions of PR1, PR2, PR5, PR9, PR10 and PR12 of Arabidopsis thaliana and Oryza sativa. Analysis of cis-element distribution revealed the functional multiplicity of PRs and provides insight into the gene regulation. CpG islands are observed only in rice PRs, which indicates that monocot genome contains more GC rich motifs than dicots. Tandem repeats were also observed in 5' UTR of PR genes. Thus, the present study provides an understanding of regulation of PR genes and their versatile roles in plants.

76 FR 5215 - Draft Regulatory Guide: Issuance, Availability

Science.gov (United States)

2011-01-28

... . SUPPLEMENTARY INFORMATION: I. Introduction The U.S. Nuclear Regulatory Commission (NRC) is issuing for public... . From this page, the public can gain entry into ADAMS, which provides text and image files of NRC's... [email protected] . The Regulatory Analysis is available electronically under ADAMS Accession...

Is Increased Susceptibility to Balkan Endemic Nephropathy in Carriers of Common GSTA1 (*A/*B Polymorphism Linked with the Catalytic Role of GSTA1 in Ochratoxin A Biotransformation? Serbian Case Control Study and In Silico Analysis

Directory of Open Access Journals (Sweden)

Zorica Reljic

2014-08-01

Full Text Available Although recent data suggest aristolochic acid as a putative cause of Balkan endemic nephropathy (BEN, evidence also exists in favor of ochratoxin A (OTA exposure as risk factor for the disease. The potential role of xenobiotic metabolizing enzymes, such as the glutathione transferases (GSTs, in OTA biotransformation is based on OTA glutathione adducts (OTHQ-SG and OTB-SG in blood and urine of BEN patients. We aimed to analyze the association between common GSTA1, GSTM1, GSTT1, and GSTP1 polymorphisms and BEN susceptibility, and thereafter performed an in silico simulation of particular GST enzymes potentially involved in OTA transformations. GSTA1, GSTM1, GSTT1 and GSTP1 genotypes were determined in 207 BEN patients and 138 non-BEN healthy individuals from endemic regions by polymerase chain reaction (PCR. Molecular modeling in silico was performed for GSTA1 protein. Among the GST polymorphisms tested, only GSTA1 was significantly associated with a higher risk of BEN. Namely, carriers of the GSTA1*B gene variant, associated with lower transcriptional activation, were at a 1.6-fold higher BEN risk than those carrying the homozygous GSTA1*A/*A genotype (OR = 1.6; p = 0.037. In in silico modeling, we found four structures, two OTB-SG and two OTHQ-SG, bound in a GSTA1 monomer. We found that GSTA1 polymorphism was associated with increased risk of BEN, and suggested, according to the in silico simulation, that GSTA1-1 might be involved in catalyzing the formation of OTHQ-SG and OTB-SG conjugates.

In Silico Detection and Typing of Plasmids using PlasmidFinder and Plasmid Multilocus Sequence Typing

DEFF Research Database (Denmark)

Carattoli, Alessandra; Zankari, Ea; García-Fernández, Aurora

2014-01-01

In the work presented here, we designed and developed two easy-to-use Web tools for in silico detection and characterization of whole-genome sequence (WGS) and whole-plasmid sequence data from members of the family Enterobacteriaceae. These tools will facilitate bacterial typing based on draft...... genomes of multidrug-resistant Enterobacteriaceae species by the rapid detection of known plasmid types. Replicon sequences from 559 fully sequenced plasmids associated with the family Enterobacteriaceae in the NCBI nucleotide database were collected to build a consensus database for integration...... sequences identified in the 559 fully sequenced plasmids. For plasmid multilocus sequence typing (pMLST) analysis, a database that is updated weekly was generated from www.pubmlst.org and integrated into a Web tool called pMLST. Both databases were evaluated using draft genomes from a collection...

Assessment of regulatory effectiveness. Peer discussions on regulatory practices

International Nuclear Information System (INIS)

1999-09-01

This report arises from the seventh series of peer discussions on regulatory practices entitled 'Assessment of Regulatory Effectiveness'. The term 'regulatory effectiveness' covers the quality of the work and level of performance of a regulatory body. In this sense, regulatory effectiveness applies to regulatory body activities aimed at preventing safety degradation and ensuring that an acceptable level of safety is being maintained by the regulated operating organizations. In addition, regulatory effectiveness encompasses the promotion of safety improvements, the timely and cost effective performance of regulatory functions in a manner which ensures the confidence of the operating organizations, the general public and the government, and striving for continuous improvements to performance. Senior regulators from 22 Member States participated in two peer group discussions during March and May 1999. The discussions were focused on the elements of an effective regulatory body, possible indicators of regulatory effectiveness and its assessment. This report presents the outcome of these meetings and recommendations of good practices identified by senior regulators, which do not necessarily reflect those of the governments of the nominating Member States, the organizations they belong to, or the International Atomic Energy Agency. In order to protect people and the environment from hazards associated with nuclear facilities, the main objective of a nuclear regulatory body is to ensure that a high level of safety in the nuclear activities under its jurisdiction is achieved, maintained and within the control of operating organizations. Even if it is possible to directly judge objective safety levels at nuclear facilities, such safety levels would not provide an exclusive indicator of regulatory effectiveness. The way the regulatory body ensures the safety of workers and the public and the way it discharges its responsibilities also determine its effectiveness. Hence the

Proteome-wide analysis of lysine acetylation suggests its broad regulatory scope in Saccharomyces cerevisiae

DEFF Research Database (Denmark)

Henriksen, Peter; Wagner, Sebastian Alexander; Weinert, Brian Tate

2012-01-01

Post-translational modification of proteins by lysine acetylation plays important regulatory roles in living cells. The budding yeast Saccharomyces cerevisiae is a widely used unicellular eukaryotic model organism in biomedical research. S. cerevisiae contains several evolutionary conserved lysine...... acetyltransferases and deacetylases. However, only a few dozen acetylation sites in S. cerevisiae are known, presenting a major obstacle for further understanding the regulatory roles of acetylation in this organism. Here we use high resolution mass spectrometry to identify about 4000 lysine acetylation sites in S....... cerevisiae. Acetylated proteins are implicated in the regulation of diverse cytoplasmic and nuclear processes including chromatin organization, mitochondrial metabolism, and protein synthesis. Bioinformatic analysis of yeast acetylation sites shows that acetylated lysines are significantly more conserved...

In silico and cell-based analyses reveal strong divergence between prediction and observation of T-cell-recognized tumor antigen T-cell epitopes.

Science.gov (United States)

Schmidt, Julien; Guillaume, Philippe; Dojcinovic, Danijel; Karbach, Julia; Coukos, George; Luescher, Immanuel

2017-07-14

Tumor exomes provide comprehensive information on mutated, overexpressed genes and aberrant splicing, which can be exploited for personalized cancer immunotherapy. Of particular interest are mutated tumor antigen T-cell epitopes, because neoepitope-specific T cells often are tumoricidal. However, identifying tumor-specific T-cell epitopes is a major challenge. A widely used strategy relies on initial prediction of human leukocyte antigen-binding peptides by in silico algorithms, but the predictive power of this approach is unclear. Here, we used the human tumor antigen NY-ESO-1 (ESO) and the human leukocyte antigen variant HLA-A*0201 (A2) as a model and predicted in silico the 41 highest-affinity, A2-binding 8-11-mer peptides and assessed their binding, kinetic complex stability, and immunogenicity in A2-transgenic mice and on peripheral blood mononuclear cells from ESO-vaccinated melanoma patients. We found that 19 of the peptides strongly bound to A2, 10 of which formed stable A2-peptide complexes and induced CD8 + T cells in A2-transgenic mice. However, only 5 of the peptides induced cognate T cells in humans; these peptides exhibited strong binding and complex stability and contained multiple large hydrophobic and aromatic amino acids. These results were not predicted by in silico algorithms and provide new clues to improving T-cell epitope identification. In conclusion, our findings indicate that only a small fraction of in silico -predicted A2-binding ESO peptides are immunogenic in humans, namely those that have high peptide-binding strength and complex stability. This observation highlights the need for improving in silico predictions of peptide immunogenicity. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Nuclear reactor decommissioning: an analysis of the regulatory environments

International Nuclear Information System (INIS)

Cantor, R.

1986-08-01

In the next several decades, the electric utility industry will be faced withthe retirement of 50,000 megawatts (mW) of nuclear capacity. Responsibility for the financial and technical burdens this activity entails has been delegated to the utilities operating the reactors. However, the operators will have to perform the tasks of reactor decommissioning within the regulatory environment dictated by federal, state and local regulations. The purpose of this study was to highlight some of the current and likely trends in regulations and regulatory practices that will significantly affect the costs, technical alternatives and financing schemes encountered by the electric utilities and their customers. To identify significant trends and practices among regulatory bodies and utilities, a reviw of these factors was undertaken at various levels in the regulatory hierarchy. The technical policies were examined in reference to their treatment of allowed technical modes, restoration of the plant site including any specific recognition of the residual radioactivity levels, and planning requirements. The financial policies were examined for specification of acceptable financing arrangements, mechanisms which adjust for changes in the important parameters used to establish the fund, tax and rate-base treatments of the payments to and earnings on the fund, and whether or not escalation and/or discounting were considered in the estimates of decommissioning costs. The attitudes of regulators toward financial risk, the tax treatment of the decommissioning fund, and the time distribution of the technical mode were found to have the greatest effect on the discounted revenue requirements. Under plausible assumptions, the cost of a highly restricted environment is about seven times that of the minimum revenue requirement environment for the plants that must be decommissioned in the next three decades

Nanoparticulate materials and regulatory policy in Europe: An analysis of stakeholder perspectives

International Nuclear Information System (INIS)

Helland, Aasgeir; Kastenholz, Hans; Thidell, Aake; Arnfalk, Peter; Deppert, Knut

2006-01-01

The novel properties of nanoparticulate materials (NPM) and the rapid development of NPM based products have raised many unanswered questions and concerns by different stakeholders over its consequences for the environment and human health. These concerns have led to an increasing discussion in both the US and Europe about possible regulatory policies for NPM. In this article a comparative study of stakeholders' perceptions on regulatory policy issues with NPM in Europe is presented. It was found that industry wants to regulate this area if the scientific evidence demonstrates that NPM are harmful, but also that the regulatory bodies do not find it necessary at this point of time to regulate until scientific evidence demonstrates that NPM are harmful. This research therefore shows that there will most likely not be any regulatory interventions until there is an established and convincing scientific knowledge base demonstrating that NPM can be hazardous. It is furthermore discussed in this article the different roles and responsibilities of the stakeholders in financing the research required to establish the necessary level of fundamental scientific evidence. It was also found that the activity of the regulatory bodies on this issue differ between the European countries

Transport of Th(IV) and U(VI) through barium silico-phosphate composite membrane using electric field

International Nuclear Information System (INIS)

Zaki, E.E.

2002-01-01

The present paper describes the preparation of a novel barium silico-phosphate filter paper supported membrane. It is based on precipitation reaction of barium silico-phosphate on the outer surface and in the interstices of a filter paper by means of electrodialysis. The main physical and electrical properties of the membrane are given and its electrodialysis behaviour is assessed for Th(IV) and U(VI). The transport of Th(IV) in presence of U(VI) was studied. The cationic fluxes of Th(IV) and U(VI) were found to be 1.2 x 10 -8 and 6.5 x 10 -9 g eq cm -2 s -1 , respectively. Transport of Th(IV) and U(VI) in presence of EDTA was investigated. The cationic flux of U(VI) is found to be 9.8 x 10 -9 g eq cm -2 s -1 at a current density of 25 mA/cm 2 . A comparative study on the electro osmotic effect was carried out using the developed membrane and commercially available Nafion membranes. In this context, different parameters like current density, electrolyte concentration, etc. were investigated. The electro-osmotic permeability coefficient, D e , of Th(IV) through barium silico-phosphate and Nafion membranes were 6.9 x 10 -2 and 1.0 x 10 -2 cm 3 /As, respectively. It can be concluded that inorganic membranes have very marked electro-osmotic properties unlike their organic counterparts. (orig.)

Advanced Reactor Technology -- Regulatory Technology Development Plan (RTDP)

International Nuclear Information System (INIS)

Moe, Wayne Leland

2015-01-01

This DOE-NE Advanced Small Modular Reactor (AdvSMR) regulatory technology development plan (RTDP) will link critical DOE nuclear reactor technology development programs to important regulatory and policy-related issues likely to impact a ''critical path'' for establishing a viable commercial AdvSMR presence in the domestic energy market. Accordingly, the regulatory considerations that are set forth in the AdvSMR RTDP will not be limited to any one particular type or subset of advanced reactor technology(s) but rather broadly consider potential regulatory approaches and the licensing implications that accompany all DOE-sponsored research and technology development activity that deal with commercial non-light water reactors. However, it is also important to remember that certain ''minimum'' levels of design and safety approach knowledge concerning these technology(s) must be defined and available to an extent that supports appropriate pre-licensing regulatory analysis within the RTDP. Final resolution to advanced reactor licensing issues is most often predicated on the detailed design information and specific safety approach as documented in a facility license application and submitted for licensing review. Because the AdvSMR RTDP is focused on identifying and assessing the potential regulatory implications of DOE-sponsored reactor technology research very early in the pre-license application development phase, the information necessary to support a comprehensive regulatory analysis of a new reactor technology, and the resolution of resulting issues, will generally not be available. As such, the regulatory considerations documented in the RTDP should be considered an initial ''first step'' in the licensing process which will continue until a license is issued to build and operate the said nuclear facility. Because a facility license application relies heavily on the data and information generated by

Joint IAEA/NEA workshop proceedings on regulatory review of plant safety analysis - Abstracts, Summary and Conclusions

International Nuclear Information System (INIS)

Lacey, Derek; Drozd, Andrzej; Husarcek, Jan; Modro, Mike

1999-01-01

Based on the final discussion, the seminar was a valuable exchange of information and helpful in understanding the safety analysis and regulatory review issues. It gave a chance for some countries to see 'where they are' regulatory-wise with respect to other countries. There was a strong support for a follow-up workshop within the next two years. A general opinion expressed by most of the participants was that the suggested next seminar should be based more on an 'overall safety analysis' review rather than on very detailed presentations on specific issues. Also, there should be more discussions on Emergency Operating Procedures (EOPs) and emergency planning. In addition, to establish a 'common language', the development of a glossary of terms would be most helpful. In general, all of the participating countries are adapting regulatory and licensing practices previously developed by other countries. Such an approach allows to utilise and rely on a broad experience of countries with a well established nuclear power industry, strong regulatory organisation and licensing practices. Since there are obvious differences in engineering traditions and in countries' legal/regulatory frameworks, questions arise about how to reconcile these differences in adapting and developing practices suitable for a given country. It was advised as a good practice to identify from the very beginning what needs to be done and the goals to be accomplished not only in the perspective of safety and technical requirements but also in the context of the economical, political, legal and regulatory situation in a given country. There has to be a consistency in any approach, but one can never follow 'blindly' the others. It became quite obvious that the needs of countries with a big nuclear program are very different from those of 'small' countries. Adaptation of other countries' rules is a big effort in itself (e.g., Romania applying Canadian regulations). In addition, the French-German co

Genome-wide analysis of regulatory proteases sequences identified through bioinformatics data mining in Taenia solium.

Science.gov (United States)

Yan, Hong-Bin; Lou, Zhong-Zi; Li, Li; Brindley, Paul J; Zheng, Yadong; Luo, Xuenong; Hou, Junling; Guo, Aijiang; Jia, Wan-Zhong; Cai, Xuepeng

2014-06-04

Cysticercosis remains a major neglected tropical disease of humanity in many regions, especially in sub-Saharan Africa, Central America and elsewhere. Owing to the emerging drug resistance and the inability of current drugs to prevent re-infection, identification of novel vaccines and chemotherapeutic agents against Taenia solium and related helminth pathogens is a public health priority. The T. solium genome and the predicted proteome were reported recently, providing a wealth of information from which new interventional targets might be identified. In order to characterize and classify the entire repertoire of protease-encoding genes of T. solium, which act fundamental biological roles in all life processes, we analyzed the predicted proteins of this cestode through a combination of bioinformatics tools. Functional annotation was performed to yield insights into the signaling processes relevant to the complex developmental cycle of this tapeworm and to highlight a suite of the proteases as potential intervention targets. Within the genome of this helminth parasite, we identified 200 open reading frames encoding proteases from five clans, which correspond to 1.68% of the 11,902 protein-encoding genes predicted to be present in its genome. These proteases include calpains, cytosolic, mitochondrial signal peptidases, ubiquitylation related proteins, and others. Many not only show significant similarity to proteases in the Conserved Domain Database but have conserved active sites and catalytic domains. KEGG Automatic Annotation Server (KAAS) analysis indicated that ~60% of these proteases share strong sequence identities with proteins of the KEGG database, which are involved in human disease, metabolic pathways, genetic information processes, cellular processes, environmental information processes and organismal systems. Also, we identified signal peptides and transmembrane helices through comparative analysis with classes of important regulatory proteases

ReMap 2018: an updated atlas of regulatory regions from an integrative analysis of DNA-binding ChIP-seq experiments.

Science.gov (United States)

Chèneby, Jeanne; Gheorghe, Marius; Artufel, Marie; Mathelier, Anthony; Ballester, Benoit

2018-01-04

With this latest release of ReMap (http://remap.cisreg.eu), we present a unique collection of regulatory regions in human, as a result of a large-scale integrative analysis of ChIP-seq experiments for hundreds of transcriptional regulators (TRs) such as transcription factors, transcriptional co-activators and chromatin regulators. In 2015, we introduced the ReMap database to capture the genome regulatory space by integrating public ChIP-seq datasets, covering 237 TRs across 13 million (M) peaks. In this release, we have extended this catalog to constitute a unique collection of regulatory regions. Specifically, we have collected, analyzed and retained after quality control a total of 2829 ChIP-seq datasets available from public sources, covering a total of 485 TRs with a catalog of 80M peaks. Additionally, the updated database includes new search features for TR names as well as aliases, including cell line names and the ability to navigate the data directly within genome browsers via public track hubs. Finally, full access to this catalog is available online together with a TR binding enrichment analysis tool. ReMap 2018 provides a significant update of the ReMap database, providing an in depth view of the complexity of the regulatory landscape in human. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Large-scale in silico mapping of complex quantitative traits in inbred mice.

Directory of Open Access Journals (Sweden)

Pengyuan Liu

2007-07-01

Full Text Available Understanding the genetic basis of common disease and disease-related quantitative traits will aid in the development of diagnostics and therapeutics. The processs of gene discovery can be sped up by rapid and effective integration of well-defined mouse genome and phenome data resources. We describe here an in silico gene-discovery strategy through genome-wide association (GWA scans in inbred mice with a wide range of genetic variation. We identified 937 quantitative trait loci (QTLs from a survey of 173 mouse phenotypes, which include models of human disease (atherosclerosis, cardiovascular disease, cancer and obesity as well as behavioral, hematological, immunological, metabolic, and neurological traits. 67% of QTLs were refined into genomic regions <0.5 Mb with approximately 40-fold increase in mapping precision as compared with classical linkage analysis. This makes for more efficient identification of the genes that underlie disease. We have identified two QTL genes, Adam12 and Cdh2, as causal genetic variants for atherogenic diet-induced obesity. Our findings demonstrate that GWA analysis in mice has the potential to resolve multiple tightly linked QTLs and achieve single-gene resolution. These high-resolution QTL data can serve as a primary resource for positional cloning and gene identification in the research community.

Management systems for regulatory authorities

International Nuclear Information System (INIS)

Mpandanyama, Rujeko Lynette

2015-02-01

For a regulatory body to fulfil its statutory obligations, there is need to develop and implement a regulatory management system that has the necessary arrangements for achieving and maintaining high quality performance in regulating the safety of nuclear and radiation facilities under its authority. Hence, the regulatory management system needs to fully integrate the human resources, processes and physical resources of the organization. This study sought to provide an understanding of the concept, principles, policies and fundamentals of management systems as they relate to regulatory systems in the field of radiation protection and to make appropriate recommendations to ensure that an effective management system exists for the control of ionizing radiation and radiation sources and addresses all relevant stakeholders in Zimbabwe. A comparative analysis was done on the current management status and the ideal management system, which led to the identification of the gaps existing. The main key that was found to be of significance was lack of linkages between processes and management tools within the institution. (au)

In silico structure-based drug screening of novel antimycobacterial pharmacophores by DOCK-GOLD tandem screening

Directory of Open Access Journals (Sweden)

Junichi Taira

2017-01-01

Full Text Available Background: Enzymes responsible for cell wall development in Mycobacterium tuberculosis are considered as potential targets of anti-tuberculosis (TB agents. Mycobacterial cyclopropane mycolic acid synthase 1 (CmaA1 is essential for mycobacterial survival because of its critical role in synthesizing mycolic acids. Materials and Methods: We screened compounds that were capable of interacting with the mycobacterial CmaA1 active site using a virtual compound library with an in silico structure-based drug screening (SBDS. Following the selection of such compounds, their antimycobacterial activity was examined. Results: With the in silico SBDS, for which we also used DOCK-GOLD programs and screening methods that utilized the structural similarity between the selected active compounds, we identified two compounds with potent inhibitory effects on mycobacterial growth. The antimycobacterial effect of the compounds was comparable to that of isoniazid, which is used as a first-line anti-TB drug. Conclusion: The compounds identified through SBDS were expected to be a novel class of anti-TB pharmacophores.

Patient-specific in silico models can quantify primary implant stability in elderly human bone.

Science.gov (United States)

Steiner, Juri A; Hofmann, Urs A T; Christen, Patrik; Favre, Jean M; Ferguson, Stephen J; van Lenthe, G Harry

2018-03-01

Secure implant fixation is challenging in osteoporotic bone. Due to the high variability in inter- and intra-patient bone quality, ex vivo mechanical testing of implants in bone is very material- and time-consuming. Alternatively, in silico models could substantially reduce costs and speed up the design of novel implants if they had the capability to capture the intricate bone microstructure. Therefore, the aim of this study was to validate a micro-finite element model of a multi-screw fracture fixation system. Eight human cadaveric humerii were scanned using micro-CT and mechanically tested to quantify bone stiffness. Osteotomy and fracture fixation were performed, followed by mechanical testing to quantify displacements at 12 different locations on the instrumented bone. For each experimental case, a micro-finite element model was created. From the micro-finite element analyses of the intact model, the patient-specific bone tissue modulus was determined such that the simulated apparent stiffness matched the measured stiffness of the intact bone. Similarly, the tissue modulus of a small damage region around each screw was determined for the instrumented bone. For validation, all in silico models were rerun using averaged material properties, resulting in an average coefficient of determination of 0.89 ± 0.04 with a slope of 0.93 ± 0.19 and a mean absolute error of 43 ± 10 μm when correlating in silico marker displacements with the ex vivo test. In conclusion, we validated a patient-specific computer model of an entire organ bone-implant system at the tissue-level at high resolution with excellent overall accuracy. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:954-962, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Data Quality Objectives for Regulatory Requirements for Hazardous and Radioactive Air Emissions Sampling and Analysis; FINAL

International Nuclear Information System (INIS)

MULKEY, C.H.

1999-01-01

This document describes the results of the data quality objective (DQO) process undertaken to define data needs for state and federal requirements associated with toxic, hazardous, and/or radiological air emissions under the jurisdiction of the River Protection Project (RPP). Hereafter, this document is referred to as the Air DQO. The primary drivers for characterization under this DQO are the regulatory requirements pursuant to Washington State regulations, that may require sampling and analysis. The federal regulations concerning air emissions are incorporated into the Washington State regulations. Data needs exist for nonradioactive and radioactive waste constituents and characteristics as identified through the DQO process described in this document. The purpose is to identify current data needs for complying with regulatory drivers for the measurement of air emissions from RPP facilities in support of air permitting. These drivers include best management practices; similar analyses may have more than one regulatory driver. This document should not be used for determining overall compliance with regulations because the regulations are in constant change, and this document may not reflect the latest regulatory requirements. Regulatory requirements are also expected to change as various permits are issued. Data needs require samples for both radionuclides and nonradionuclide analytes of air emissions from tanks and stored waste containers. The collection of data is to support environmental permitting and compliance, not for health and safety issues. This document does not address health or safety regulations or requirements (those of the Occupational Safety and Health Administration or the National Institute of Occupational Safety and Health) or continuous emission monitoring systems. This DQO is applicable to all equipment, facilities, and operations under the jurisdiction of RPP that emit or have the potential to emit regulated air pollutants

Identification of trans-acting factors regulating SamDC expression in Oryza sativa

Energy Technology Data Exchange (ETDEWEB)

Basu, Supratim, E-mail: supratim_genetics@yahoo.co.in [Department of Crop Soil and Environmental Sciences, University of Arkansas, Fayetteville, AR 72701 (United States); Division of Plant Biology, Bose Institute, Kolkata (India); Roychoudhury, Aryadeep [Post Graduate Department of Biotechnology, St. Xavier' s College (Autonomous), 30, Mother Teresa Sarani, Kolkata - 700016, West Bengal (India); Sengupta, Dibyendu N. [Division of Plant Biology, Bose Institute, Kolkata (India)

2014-03-07

Highlights: • Identification of cis elements responsible for SamDC expression by in silico analysis. • qPCR analysis of SamDC expression to abiotic and biotic stress treatments. • Detection of SamDC regulators using identified cis-elements as probe by EMSA. • Southwestern Blot analysis to predict the size of the trans-acting factors. - Abstract: Abiotic stress affects the growth and productivity of crop plants; to cope with the adverse environmental conditions, plants have developed efficient defense machinery comprising of antioxidants like phenolics and flavonoids, and osmolytes like polyamines. SamDC is a key enzyme in the polyamine biosynthesis pathway in plants. In our present communication we have done in silico analysis of the promoter region of SamDC to look for the presence of different cis-regulatory elements contributing to its expression. Based on the presence of different cis-regulatory elements we completed comparative analysis of SamDC gene expression in rice lamina of IR-29 and Nonabokra by qPCR in response to the abiotic stress treatments of salinity, drought, cold and the biotic stress treatments of ABA and light. Additionally, to explore the role of the cis-regulatory elements in regulating the expression of SamDC gene in plants we comparatively analyzed the binding of rice nuclear proteins prepared from IR-29 and Nonabokra undergoing various stress treatments. The intensity of the complex formed was low and inducible in IR-29 in contrast to Nonabokra. Southwestern blot analysis helped in predicting the size of the trans-acting factors binding to these cis-elements. To our knowledge this is the first report on the comprehensive analysis of SamDC gene expression in rice and identification of the trans-acting factors regulating its expression.

Genome-wide in silico identification of GPI proteins in Mycosphaerella fijiensis and transcriptional analysis of two GPI-anchored β-1,3-glucanosyltransferases.

Science.gov (United States)

Kantún-Moreno, Nuvia; Vázquez-Euán, Roberto; Tzec-Simá, Miguel; Peraza-Echeverría, Leticia; Grijalva-Arango, Rosa; Rodríguez-García, Cecilia; James, Andrew C; Ramírez-Prado, Jorge; Islas-Flores, Ignacio; Canto-Canché, Blondy

2013-01-01

The hemibiotrophic fungus Mycosphaerella fijiensis is the causal agent of black Sigatoka (BS), the most devastating foliar disease in banana (Musa spp.) worldwide. Little is known about genes that are important during M. fijiensis-Musa sp. interaction. The fungal cell wall is an attractive area of study because it is essential for maintenance of cellular homeostasis and it is the most external structure in the fungal cell and therefore mediates the interaction of the pathogen with the host. In this manuscript we describe the in silico identification of glycosyl phosphatidylinositol-protein (GPI) family in M. fijiensis, and the analysis of two β-1,3-glucanosyltrans-ferases (Gas), selected by homology with fungal pathogenicity factors. Potential roles in pathogenesis were evaluated through analyzing expression during different stages of black Sigatoka disease, comparing expression data with BS symptoms and fungal biomass inside leaves. Real-time quantitative RT-PCR showed nearly constant expression of MfGAS1 with slightly increases (about threefold) in conidia and at speck-necrotrophic stage during banana-pathogen interaction. Conversely, MfGAS2 expression was increased during biotrophy (about seven times) and reached a maximum at speck (about 23 times) followed by a progressive decrease in next stages, suggesting an active role in M. fijiensis pathogenesis.

Improved vanillin production in baker's yeast through in silico design.

Science.gov (United States)

Brochado, Ana Rita; Matos, Claudia; Møller, Birger L; Hansen, Jørgen; Mortensen, Uffe H; Patil, Kiran Raosaheb

2010-11-08

Vanillin is one of the most widely used flavouring agents, originally obtained from cured seed pods of the vanilla orchid Vanilla planifolia. Currently vanillin is mostly produced via chemical synthesis. A de novo synthetic pathway for heterologous vanillin production from glucose has recently been implemented in baker's yeast, Saccharamyces cerevisiae. In this study we aimed at engineering this vanillin cell factory towards improved productivity and thereby at developing an attractive alternative to chemical synthesis. Expression of a glycosyltransferase from Arabidopsis thaliana in the vanillin producing S. cerevisiae strain served to decrease product toxicity. An in silico metabolic engineering strategy of this vanillin glucoside producing strain was designed using a set of stoichiometric modelling tools applied to the yeast genome-scale metabolic network. Two targets (PDC1 and GDH1) were selected for experimental verification resulting in four engineered strains. Three of the mutants showed up to 1.5 fold higher vanillin β-D-glucoside yield in batch mode, while continuous culture of the Δpdc1 mutant showed a 2-fold productivity improvement. This mutant presented a 5-fold improvement in free vanillin production compared to the previous work on de novo vanillin biosynthesis in baker's yeast. Use of constraints corresponding to different physiological states was found to greatly influence the target predictions given minimization of metabolic adjustment (MOMA) as biological objective function. In vivo verification of the targets, selected based on their predicted metabolic adjustment, successfully led to overproducing strains. Overall, we propose and demonstrate a framework for in silico design and target selection for improving microbial cell factories.

Measuring and Reconstructing the Brain at the Synaptic Scale: Towards a Biofidelic Human Brain in silico

OpenAIRE

NeuroData; CE, Priebe; Burns, R.; RJ, Vogelstein

2015-01-01

Vogelstein JT, Priebe CE, Burns R, Vogelstein RJ, Lichtman J. Measuring and Reconstructing the Brain at the Synaptic Scale: Towards a Biofidelic Human Brain in silico. DARPA Neural Engineering, Science and Technology Forum, 2010

Regulatory analyses for severe accident issues: an example

International Nuclear Information System (INIS)

Burke, R.P.; Strip, D.R.; Aldrich, D.C.

1984-09-01

This report presents the results of an effort to develop a regulatory analysis methodology and presentation format to provide information for regulatory decision-making related to severe accident issues. Insights and conclusions gained from an example analysis are presented. The example analysis draws upon information generated in several previous and current NRC research programs (the Severe Accident Risk Reduction Program (SARRP), Accident Sequence Evaluation Program (ASEP), Value-Impact Handbook, Economic Risk Analyses, and studies of Vented Containment Systems and Alternative Decay Heat Removal Systems) to perform preliminary value-impact analyses on the installation of either a vented containment system or an alternative decay heat removal system at the Peach Bottom No. 2 plant. The results presented in this report are first-cut estimates, and are presented only for illustrative purposes in the context of this document. This study should serve to focus discussion on issues relating to the type of information, the appropriate level of detail, and the presentation format which would make a regulatory analysis most useful in the decisionmaking process

In silico design and functional assessment of semisynthetic genes that confer tolerance to phosphinothricin

Directory of Open Access Journals (Sweden)

Jenny Paola Jiménez

2016-07-01

Full Text Available Herbicide tolerance is one of the features most used in GM crops, which has shown positive results for farmers and the environment. The starting point is the development of expression cassettes that express the characteristic of interest, they are initially constructed by standard molecular biology techniques. Currently, by bioinformatics and synthetic biology tools, it is possible to design and test the construct in silico, and then hire their synthesis. This approach allows optimizing expression by modifying the codon usage. In this work there were designed and evaluated semi-synthetic versions of genes in Nicotiana benthamiana, these genes confer tolerance to the herbicide phosphinothricin. It was made an analysis of freedom to operate in order to ensure that the designed constructs not violate intellectual property in Colombia. There were obtained two expression cassettes with freedom to operate, which express versions of the bar gene.

Sodium leak detection on large pipes. Heat insulating shells made of silico-aluminate

International Nuclear Information System (INIS)

Antonakas, D.; Blanc, R.; Casselman, C.; Malet, J.C.

1986-05-01

This report presents an equipment installed on the large secondary pipes of fast reactors, ensuring several functions: support and equilibrium of static and dynamic loads, heat insulator, preheating, and the detection of possible sodium leaks. The research programs associated to the development of the shells are briefly evoked; then, the report deals no longer with the studies on silico-aluminate aging and the detection performance [fr

75 FR 33853 - Draft Regulatory Guide: Issuance, Availability

Science.gov (United States)

2010-06-15

.... Introduction The U.S. Nuclear Regulatory Commission (NRC) is issuing for public comment a draft guide in the... provides text and image files of NRC's public documents. If you do not have access to ADAMS or if there are... ADAMS Accession Number ML100760364. The regulatory analysis is available electronically under ADAMS...

75 FR 52996 - Draft Regulatory Guide: Issuance, Availability

Science.gov (United States)

2010-08-30

.... Introduction The U.S. Nuclear Regulatory Commission (NRC) is issuing for public comment a draft guide in the... entry into ADAMS, which provides text and image files of NRC's public documents. If you do not have.../ . The regulatory analysis may be found in ADAMS under Accession No. ML102310331. Federal Rulemaking Web...

Parameter optimization for constructing competing endogenous RNA regulatory network in glioblastoma multiforme and other cancers.

Science.gov (United States)

Chiu, Yu-Chiao; Hsiao, Tzu-Hung; Chen, Yidong; Chuang, Eric Y

2015-01-01

In addition to direct targeting and repressing mRNAs, recent studies reported that microRNAs (miRNAs) can bridge up an alternative layer of post-transcriptional gene regulatory networks. The competing endogenous RNA (ceRNA) regulation depicts the scenario where pairs of genes (ceRNAs) sharing, fully or partially, common binding miRNAs (miRNA program) can establish coexpression through competition for a limited pool of the miRNA program. While the dynamics of ceRNA regulation among cellular conditions have been verified based on in silico and in vitro experiments, comprehensive investigation into the strength of ceRNA regulation in human datasets remains largely unexplored. Furthermore, pan-cancer analysis of ceRNA regulation, to our knowledge, has not been systematically investigated. In the present study we explored optimal conditions for ceRNA regulation, investigated functions governed by ceRNA regulation, and evaluated pan-cancer effects. We started by investigating how essential factors, such as the size of miRNA programs, the number of miRNA program binding sites, and expression levels of miRNA programs and ceRNAs affect the ceRNA regulation capacity in tumors derived from glioblastoma multiforme patients captured by The Cancer Genome Atlas (TCGA). We demonstrated that increased numbers of common targeting miRNAs as well as the abundance of binding sites enhance ceRNA regulation and strengthen coexpression of ceRNA pairs. Also, our investigation revealed that the strength of ceRNA regulation is dependent on expression levels of both miRNA programs and ceRNAs. Through functional annotation analysis, our results indicated that ceRNA regulation is highly associated with essential cellular functions and diseases including cancer. Furthermore, the highly intertwined ceRNA regulatory relationship enables constitutive and effective intra-function regulation of genes in diverse types of cancer. Using gene and microRNA expression datasets from TCGA, we successfully

76 FR 28102 - Notice of Issuance of Regulatory Guide

Science.gov (United States)

2011-05-13

... Analysis, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, Washington, DC 20555... qualitative, traditional or probabilistic), data, and criteria for considering risk are appropriate for making... 10 CFR part 52, ``Licenses, Certifications, and Approvals for Nuclear Power Plants.'' Other types of...

Regulatory analysis for Generic Issue 23: Reactor coolant pump seal failure. Draft report for comment

Energy Technology Data Exchange (ETDEWEB)

Shaukat, S K; Jackson, J E; Thatcher, D F

1991-04-01

This report presents the regulatory/backfit analysis for Generic Issue 23 (GI-23), 'Reactor Coolant Pump Seal Failure'. A backfit analysis in accordance with 10 CFR 50.109 is presented in Appendix E. The proposed resolution includes quality assurance provisions for reactor coolant pump seals, instrumentation and procedures for monitoring seal performance, and provisions for seal cooling during off-normal plant conditions involving loss of all seal cooling such as station blackout. Research, technical data, and other analyses supporting the resolution of this issue are summarized in the technical findings report (NUREG/CR-4948) and cost/benefit report (NUREG/CR-5167). (author)

Exploring the Potential of Generative Adversarial Networks for Synthesizing Radiological Images of the Spine to be Used in In Silico Trials

Directory of Open Access Journals (Sweden)

Fabio Galbusera

2018-05-01

Full Text Available In silico trials recently emerged as a disruptive technology, which may reduce the costs related to the development and marketing approval of novel medical technologies, as well as shortening their time-to-market. In these trials, virtual patients are recruited from a large database and their response to the therapy, such as the implantation of a medical device, is simulated by means of numerical models. In this work, we propose the use of generative adversarial networks to produce synthetic radiological images to be used in in silico trials. The generative models produced credible synthetic sagittal X-rays of the lumbar spine based on a simple sketch, and were able to generate sagittal radiological images of the trunk using coronal projections as inputs, and vice versa. Although numerous inaccuracies in the anatomical details may still allow distinguishing synthetic and real images in the majority of cases, the present work showed that generative models are a feasible solution for creating synthetic imaging data to be used in in silico trials of novel medical devices.

The Virtual Anemia Trial: An Assessment of Model-Based In Silico Clinical Trials of Anemia Treatment Algorithms in Patients With Hemodialysis.

Science.gov (United States)

Fuertinger, Doris H; Topping, Alice; Kappel, Franz; Thijssen, Stephan; Kotanko, Peter

2018-04-01

In silico approaches have been proposed as a novel strategy to increase the repertoire of clinical trial designs. Realistic simulations of clinical trials can provide valuable information regarding safety and limitations of treatment protocols and have been shown to assist in the cost-effective planning of clinical studies. In this report, we present a blueprint for the stepwise integration of internal, external, and ecological validity considerations in virtual clinical trials (VCTs). We exemplify this approach in the context of a model-based in silico clinical trial aimed at anemia treatment in patients undergoing hemodialysis (HD). Hemoglobin levels and subsequent anemia treatment were simulated on a per patient level over the course of a year and compared to real-life clinical data of 79,426 patients undergoing HD. The novel strategies presented here, aimed to improve external and ecological validity of a VCT, significantly increased the predictive power of the discussed in silico trial. © 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Regulatory and Non-regulatory Responses to Hydraulic Fracturing in Local Communities

Science.gov (United States)

Phartiyal, P.

2015-12-01

The practice of extracting oil and gas from tight rock formations using advances in technology, such as hydraulic fracturing and directional drilling, has expanded exponentially in states and localities across the country. As the scientific data collection and analysis catches up on the many potential impacts of this unconventional oil and gas development, communities are turning to their local officials to make decisions on whether and how fracking should proceed. While most regulatory authority on the issue rests with the state agencies, local officials have experimented with a wide range of regulatory, non-regulatory, and fiscal tools to manage the impacts of fracking. These impacts can occur on the local air, water, seismicity, soil, roads, schools, and affect residents, on-site workers, emergency and social services. Local officials' approaches are often influenced by their prior experience with minerals extraction in their localities. The speaker will present examples of the kinds of information sources, tools and approaches communities across the country are using, from noise barriers to setback requirements to information sharing in order to be able to balance the promise and perils of oil and gas development in their jurisdictions.