The Protein Model Portal—a comprehensive resource for protein structure and model information

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Haas, Juergen; Roth, Steven; Arnold, Konstantin; Kiefer, Florian; Schmidt, Tobias; Bordoli, Lorenza; Schwede, Torsten

2013-01-01

The Protein Model Portal (PMP) has been developed to foster effective use of 3D molecular models in biomedical research by providing convenient and comprehensive access to structural information for proteins. Both experimental structures and theoretical models for a given protein can be searched simultaneously and analyzed for structural variability. By providing a comprehensive view on structural information, PMP offers the opportunity to apply consistent assessment and validation criteria to the complete set of structural models available for proteins. PMP is an open project so that new methods developed by the community can contribute to PMP, for example, new modeling servers for creating homology models and model quality estimation servers for model validation. The accuracy of participating modeling servers is continuously evaluated by the Continuous Automated Model EvaluatiOn (CAMEO) project. The PMP offers a unique interface to visualize structural coverage of a protein combining both theoretical models and experimental structures, allowing straightforward assessment of the model quality and hence their utility. The portal is updated regularly and actively developed to include latest methods in the field of computational structural biology. Database URL: http://www.proteinmodelportal.org PMID:23624946

Laminin-111 protein therapy reduces muscle pathology and improves viability of a mouse model of merosin-deficient congenital muscular dystrophy.

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Rooney, Jachinta E; Knapp, Jolie R; Hodges, Bradley L; Wuebbles, Ryan D; Burkin, Dean J

2012-04-01

Merosin-deficient congenital muscular dystrophy type 1A (MDC1A) is a lethal muscle-wasting disease that is caused by mutations in the LAMA2 gene, resulting in the loss of laminin-α2 protein. MDC1A patients exhibit severe muscle weakness from birth, are confined to a wheelchair, require ventilator assistance, and have reduced life expectancy. There are currently no effective treatments or cures for MDC1A. Laminin-α2 is required for the formation of heterotrimeric laminin-211 (ie, α2, β1, and γ1) and laminin-221 (ie, α2, β2, and γ1), which are major constituents of skeletal muscle basal lamina. Laminin-111 (ie, α1, β1, and γ1) is the predominant laminin isoform in embryonic skeletal muscle and supports normal skeletal muscle development in laminin-α2-deficient muscle but is absent from adult skeletal muscle. In this study, we determined whether treatment with Engelbreth-Holm-Swarm-derived mouse laminin-111 protein could rescue MDC1A in the dy(W-/-) mouse model. We demonstrate that laminin-111 protein systemically delivered to the muscles of laminin-α2-deficient mice prevents muscle pathology, improves muscle strength, and dramatically increases life expectancy. Laminin-111 also prevented apoptosis in laminin-α2-deficient mouse muscle and primary human MDC1A myogenic cells, which indicates a conserved mechanism of action and cross-reactivity between species. Our results demonstrate that laminin-111 can serve as an effective protein substitution therapy for the treatment of muscular dystrophy in the dy(W-/-) mouse model and establish the potential for its use in the treatment of MDC1A. Copyright © 2012 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Maillard-reaction-induced modification and aggregation of proteins and hardening of texture in protein bar model systems.

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Zhou, Peng; Guo, Mufan; Liu, Dasong; Liu, Xiaoming; Labuza, Teodore P

2013-03-01

The hardening of high-protein bars causes problems in their acceptability to consumers. The objective of this study was to determine the progress of the Maillard reaction in model systems of high-protein nutritional bars containing reducing sugars, and to illustrate the influences of the Maillard reaction on the modification and aggregation of proteins and the hardening of bar matrices during storage. The progress of the Maillard reaction, glycation, and aggregation of proteins, and textural changes in bar matrices were investigated during storage at 25, 35, and 45 °C. The initial development of the Maillard reaction caused little changes in hardness; however, further storage resulted in dramatic modification of protein with formation of high-molecular-weight polymers, resulting in the hardening in texture. The replacement of reducing sugars with nonreducing ingredients such as sugar alcohols in the formula minimized the changes in texture. The hardening of high-protein bars causes problems in their acceptability to consumers. Maillard reaction is one of the mechanisms contributing to the hardening of bar matrix, particularly for the late stage of storage. The replacement of reducing sugars with nonreducing ingredients such as sugar alcohols in the formula will minimize the changes in texture. © 2013 Institute of Food Technologists®

Scalable rule-based modelling of allosteric proteins and biochemical networks.

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Julien F Ollivier

2010-11-01

Full Text Available Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

The PMDB Protein Model Database

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Castrignanò, Tiziana; De Meo, Paolo D'Onorio; Cozzetto, Domenico; Talamo, Ivano Giuseppe; Tramontano, Anna

2006-01-01

The Protein Model Database (PMDB) is a public resource aimed at storing manually built 3D models of proteins. The database is designed to provide access to models published in the scientific literature, together with validating experimental data. It is a relational database and it currently contains >74 000 models for ∼240 proteins. The system is accessible at and allows predictors to submit models along with related supporting evidence and users to download them through a simple and intuitive interface. Users can navigate in the database and retrieve models referring to the same target protein or to different regions of the same protein. Each model is assigned a unique identifier that allows interested users to directly access the data. PMID:16381873

Protein energy malnutrition alters mucosal IgA responses and reduces mucosal vaccine efficacy in mice.

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Rho, Semi; Kim, Heejoo; Shim, Seung Hyun; Lee, Seung Young; Kim, Min Jung; Yang, Bo-Gie; Jang, Myoung Ho; Han, Byung Woo; Song, Man Ki; Czerkinsky, Cecil; Kim, Jae-Ouk

2017-10-01

Oral vaccine responsiveness is often lower in children from less developed countries. Childhood malnutrition may be associated with poor immune response to oral vaccines. The present study was designed to investigate whether protein energy malnutrition (PEM) impairs B cell immunity and ultimately reduces oral vaccine efficacy in a mouse model. Purified isocaloric diets containing low protein (1/10 the protein of the control diet) were used to determine the effect of PEM. PEM increased both nonspecific total IgA and oral antigen-specific IgA in serum without alteration of gut permeability. However, PEM decreased oral antigen-specific IgA in feces, which is consistent with decreased expression of polymeric Immunoglobulin receptor (pIgR) in the small intestine. Of note, polymeric IgA was predominant in serum under PEM. In addition, PEM altered B cell development status in the bone marrow and increased the frequency of IgA-secreting B cells, as well as IgA secretion by long-lived plasma cells in the small intestinal lamina propria. Moreover, PEM reduced the protective efficacy of the mucosally administered cholera vaccine and recombinant attenuated Salmonella enterica serovar Typhimurium vaccine in a mouse model. Our results suggest that PEM can impair mucosal immunity where IgA plays an important role in host protection and may partly explain the reduced efficacy of oral vaccines in malnourished subjects. Copyright © 2017 European Federation of Immunological Societies. Published by Elsevier B.V. All rights reserved.

Graphene as a protein crystal mounting material to reduce background scatter.

Science.gov (United States)

Wierman, Jennifer L; Alden, Jonathan S; Kim, Chae Un; McEuen, Paul L; Gruner, Sol M

2013-10-01

The overall signal-to-noise ratio per unit dose for X-ray diffraction data from protein crystals can be improved by reducing the mass and density of all material surrounding the crystals. This article demonstrates a path towards the practical ultimate in background reduction by use of atomically thin graphene sheets as a crystal mounting platform for protein crystals. The results show the potential for graphene in protein crystallography and other cases where X-ray scatter from the mounting material must be reduced and specimen dehydration prevented, such as in coherent X-ray diffraction imaging of microscopic objects.

Chenodeoxycholic Acid Reduces Hypoxia Inducible Factor-1α Protein and Its Target Genes.

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Yunwon Moon

Full Text Available This study evaluated HIF-1α inhibitors under different hypoxic conditions, physiological hypoxia (5% O2 and severe hypoxia (0.1% O2. We found that chenodeoxy cholic acid (CDCA reduced the amount of HIF-1α protein only under physiological hypoxia but not under severe hypoxia without decreasing its mRNA level. By using a proteasome inhibitor MG132 and a translation inhibitor cyclohexamide, we showed that CDCA reduced HIF-1α protein by decreasing its translation but not by enhancing its degradation. The following findings indicated that farnesoid X receptor (FXR, a CDCA receptor and its target gene, Small heterodimer partner (SHP are not involved in this effect of CDCA. Distinctly from CDCA, MG132 prevented SHP and an exogenous FXR agonist, GW4064 from reducing HIF-1α protein. Furthermore a FXR antagonist, guggulsterone failed to prevent CDCA from decreasing HIF-1α protein. Furthermore, guggulsterone by itself reduced HIF-1α protein even in the presence of MG132. These findings suggested that CDCA and guggulsterone reduced the translation of HIF-1α in a mechanism which FXR and SHP are not involved. This study reveals novel therapeutic functions of traditional nontoxic drugs, CDCA and guggulsterone, as inhibitors of HIF-1α protein.

Optimization of elution salt concentration in stepwise elution of protein chromatography using linear gradient elution data. Reducing residual protein A by cation-exchange chromatography in monoclonal antibody purification.

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Ishihara, Takashi; Kadoya, Toshihiko; Endo, Naomi; Yamamoto, Shuichi

2006-05-05

Our simple method for optimization of the elution salt concentration in stepwise elution was applied to the actual protein separation system, which involves several difficulties such as detection of the target. As a model separation system, reducing residual protein A by cation-exchange chromatography in human monoclonal antibody (hMab) purification was chosen. We carried out linear gradient elution experiments and obtained the data for the peak salt concentration of hMab and residual protein A, respectively. An enzyme-linked immunosorbent assay was applied to the measurement of the residual protein A. From these data, we calculated the distribution coefficient of the hMab and the residual protein A as a function of salt concentration. The optimal salt concentration of stepwise elution to reduce the residual protein A from the hMab was determined based on the relationship between the distribution coefficient and the salt concentration. Using the optimized condition, we successfully performed the separation, resulting in high recovery of hMab and the elimination of residual protein A.

Lipoxygenase independent hexanal formation in isolated soy proteins induced by reducing agents.

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Lei, Q; Boatright, W L

2008-08-01

Compared to corresponding controls, 6.5 mM dithiothreitol (DTT) elevated headspace hexanal level over aqueous slurries of both commercial isolated soy proteins (ISP) and laboratory ISP prepared with 80 degrees C treatment. Further analysis revealed that lipoxygenase (LOX) activity was not detected from these ISP, indicating that LOX is not involved in the observed hexanal increase. Levels of the induced headspace hexanal over the ISP aqueous slurries were proportional to the amount of DTT added in the range of 0 to 65 mM. Subsequent systematic investigations with model systems revealed that iron was required for the reducing agent-induced hexanal formation from linoleic acid. Erythorbate, another reducing agent, can also induce hexanal formation in both ISP and model systems. As a comparison, the LOX activity and hexanal synthesis in defatted soy flour were examined. The corresponding results showed that defatted soy flour maintained high LOX activities and that hexanal synthesis in such sample was significantly inhibited by high concentration DTT (above 130 mM). Data from the current investigation demonstrate the existence of LOX independent hexanal formation induced by reducing agents in ISP and the potential requirement of iron as a catalyst.

Proteomic detection of oxidized and reduced thiol proteins in cultured cells.

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Cuddihy, Sarah L; Baty, James W; Brown, Kristin K; Winterbourn, Christine C; Hampton, Mark B

2009-01-01

The oxidation and reduction of cysteine residues is emerging as an important post-translational control of protein function. We describe a method for fluorescent labelling of either reduced or oxidized thiols in combination with two-dimensional sodium dodecyl sulphate polyacrylamide gel electrophoresis (2DE) to detect changes in the redox proteome of cultured cells. Reduced thiols are labelled with the fluorescent compound 5-iodoacetamidofluorescein. To monitor oxidized thiols, the reduced thiols are first blocked with N-ethyl-maleimide, then the oxidized thiols reduced with dithiothreitol and labelled with 5-iodoacetamidofluorescein. The method is illustrated by treating Jurkat T-lymphoma cells with hydrogen peroxide and monitoring increased labelling of oxidized thiol proteins. A decrease in labelling can also be detected, and this is attributed to the formation of higher oxidation states of cysteine that are not reduced by dithiothreitol.

Effects of Supplementation of Branched-Chain Amino Acids to Reduced-Protein Diet on Skeletal Muscle Protein Synthesis and Degradation in the Fed and Fasted States in a Piglet Model

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Liufeng Zheng

2016-12-01

Full Text Available Supplementation of branched-chain amino acids (BCAA has been demonstrated to promote skeletal muscle mass gain, but the mechanisms underlying this observation are still unknown. Since the regulation of muscle mass depends on a dynamic equilibrium (fasted losses–fed gains in protein turnover, the aim of this study was to investigate the effects of BCAA supplementation on muscle protein synthesis and degradation in fed/fasted states and the related mechanisms. Fourteen 26- (Experiment 1 and 28-day-old (Experiment 2 piglets were fed reduced-protein diets without or with supplemental BCAA. After a four-week acclimation period, skeletal muscle mass and components of anabolic and catabolic signaling in muscle samples after overnight fasting were determined in Experiment 1. Pigs in Experiment 2 were implanted with carotid arterial, jugular venous, femoral arterial and venous catheters, and fed once hourly along with the intravenous infusion of NaH13CO3 for 2 h, followed by a 6-h infusion of [1-13C]leucine. Muscle leucine kinetics were measured using arteriovenous difference technique. The mass of most muscles was increased by BCAA supplementation. During feeding, BCAA supplementation increased leucine uptake, protein synthesis, protein degradation and net transamination. The greater increase in protein synthesis than in protein degradation resulted in elevated protein deposition. Protein synthesis was strongly and positively correlated with the intramuscular net production of α-ketoisocaproate (KIC and protein degradation. Moreover, BCAA supplementation enhanced the fasted-state phosphorylation of protein translation initiation factors and inhibited the protein-degradation signaling of ubiquitin-proteasome and autophagy-lysosome systems. In conclusion, supplementation of BCAA to reduced-protein diet increases fed-state protein synthesis and inhibits fasted-state protein degradation, both of which could contribute to the elevation of skeletal muscle

Reduced protein oxidation in Wistar rats supplemented with marine ω3 PUFAs.

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Méndez, Lucía; Pazos, Manuel; Gallardo, José M; Torres, Josep L; Pérez-Jiménez, Jara; Nogués, Rosa; Romeu, Marta; Medina, Isabel

2013-02-01

The potential effects of various dietary eicosapentaenoic acid (EPA; 20:5) and docosahexaenoic acid (DHA; 22:6) ratios (1:1, 2:1, and 1:2, respectively) on protein redox states from plasma, kidney, skeletal muscle, and liver were investigated in Wistar rats. Dietary fish oil groups were compared with animals fed soybean and linseed oils, vegetable oils enriched in ω6 linoleic acid (LA; 18:2) and ω3 α-linolenic acid (ALA; 18:3), respectively. Fish oil treatments were effective at reducing the level of total fatty acids in plasma and enriching the plasmatic free fatty acid fraction and erythrocyte membranes in EPA and DHA. A proteomic approach consisting of fluorescein 5-thiosemicarbazide (FTSC) labeling of protein carbonyls, FTSC intensity visualization on 1-DE or 2-DE gels, and protein identification by MS/MS was used for the protein oxidation assessment. Albumin was found to be the most carbonylated protein in plasma for all dietary groups, and its oxidation level was significantly modulated by dietary interventions. Supplementation with an equal EPA:DHA ratio (1:1) showed the lowest oxidation score for plasma albumin, followed in increasing order of carbonylation by 1:2 proteins and cytosolic proteins from kidney and liver also indicated a protective effect on proteins for the fish oil treatments, the 1:1 ratio exhibiting the lowest protein oxidation scores. The effect of fish oil treatments at reducing carbonylation on specific proteins from plasma (albumin), skeletal muscle (actin), and liver (albumin, argininosuccinate synthetase, 3-α-hydroxysteroid dehydrogenase) was remarkable. This investigation highlights the efficiency of dietary fish oil at reducing in vivo oxidative damage of proteins compared to oils enriched in the 18-carbon polyunsaturated fatty acids ω3 ALA and ω6 LA, and such antioxidant activity may differ among different fish oil sources because of variations in EPA/DHA content. Copyright © 2012 Elsevier Inc. All rights reserved.

Sodium 4-Phenylbutyrate Attenuates Myocardial Reperfusion Injury by Reducing the Unfolded Protein Response.

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Takatori, Osamu; Usui, Soichiro; Okajima, Masaki; Kaneko, Shuichi; Ootsuji, Hiroshi; Takashima, Shin-Ichiro; Kobayashi, Daisuke; Murai, Hisayoshi; Furusho, Hiroshi; Takamura, Masayuki

2017-05-01

The unfolded protein response (UPR) plays a pivotal role in ischemia-reperfusion (I/R) injury in various organs such as heart, brain, and liver. Sodium 4-phenylbutyrate (PBA) reportedly acts as a chemical chaperone that reduces UPR. In the present study, we evaluated the effect of PBA on reducing the UPR and protecting against myocardial I/R injury in mice. Male C57BL/6 mice were subjected to 30-minute myocardial I/R, and were treated with phosphate-buffered saline (as a vehicle) or PBA. At 4 hours after reperfusion, mice treated with PBA had reduced serum cardiac troponin I levels and numbers of apoptotic cells in left ventricles (LVs) in myocardial I/R. Infarct size had also reduced in mice treated with PBA at 48 hours after reperfusion. At 2 hours after reperfusion, UPR markers, including eukaryotic initiation of the factor 2α-subunit, activating transcription factor-6, inositol-requiring enzyme-1, glucose-regulated protein 78, CCAAT/enhancer-binding protein (C/EBP) homologous protein, and caspase-12, were significantly increased in mice treated with vehicle compared to sham-operated mice. Administration of PBA significantly reduced the I/R-induced increases of these markers. Cardiac function and dimensions were assessed at 21 days after I/R. Sodium 4-phenylbutyrate dedicated to the improvement of cardiac parameters deterioration including LV end-diastolic diameter and LV fractional shortening. Consistently, PBA reduced messenger RNA expression levels of cardiac remodeling markers such as collagen type 1α1, brain natriuretic peptide, and α skeletal muscle actin in LV at 21 days after I/R. Unfolded protein response mediates myocardial I/R injury. Administration of PBA reduces the UPR, apoptosis, infarct size, and preserved cardiac function. Hence, PBA may be a therapeutic option to attenuate myocardial I/R injury in clinical practice.

Completion of autobuilt protein models using a database of protein fragments

International Nuclear Information System (INIS)

Cowtan, Kevin

2012-01-01

Two developments in the process of automated protein model building in the Buccaneer software are described: the use of a database of protein fragments in improving the model completeness and the assembly of disconnected chain fragments into complete molecules. Two developments in the process of automated protein model building in the Buccaneer software are presented. A general-purpose library for protein fragments of arbitrary size is described, with a highly optimized search method allowing the use of a larger database than in previous work. The problem of assembling an autobuilt model into complete chains is discussed. This involves the assembly of disconnected chain fragments into complete molecules and the use of the database of protein fragments in improving the model completeness. Assembly of fragments into molecules is a standard step in existing model-building software, but the methods have not received detailed discussion in the literature

Protein carbonylation, protein aggregation and neuronal cell death in a murine model of multiple sclerosis

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Dasgupta, Anushka

Many studies have suggested that oxidative stress plays an important role in the pathophysiology of both multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE). Yet, the mechanism by which oxidative stress leads to tissue damage in these disorders is unclear. Recent work from our laboratory has revealed that protein carbonylation, a major oxidative modification caused by severe and/or chronic oxidative stress conditions, is elevated in MS and EAE. Furthermore, protein carbonylation has been shown to alter protein structure leading to misfolding/aggregation. These findings prompted me to hypothesize that carbonylated proteins, formed as a consequence of oxidative stress and/or decreased proteasomal activity, promote protein aggregation to mediate neuronal apoptosis in vitro and in EAE. To test this novel hypothesis, I first characterized protein carbonylation, protein aggregation and apoptosis along the spinal cord during the course of myelin-oligodendrocyte glycoprotein (MOG)35-55 peptide-induced EAE in C57BL/6 mice [Chapter 2]. The results show that carbonylated proteins accumulate throughout the course of the disease, albeit by different mechanisms: increased oxidative stress in acute EAE and decreased proteasomal activity in chronic EAE. I discovered not only that there is a temporal correlation between protein carbonylation and apoptosis but also that carbonyl levels are significantly higher in apoptotic cells. A high number of juxta-nuclear and cytoplasmic protein aggregates containing the majority of the oxidized proteins are also present during the course of EAE, which seems to be due to reduced autophagy. In chapter 3, I show that when gluthathione levels are reduced to those in EAE spinal cord, both neuron-like PC12 (nPC12) cells and primary neuronal cultures accumulate carbonylated proteins and undergo cell death (both by necrosis and apoptosis). Immunocytochemical and biochemical studies also revealed a temporal

In silico modeling of the yeast protein and protein family interaction network

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Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

Direct, simple derivatization of disulfide bonds in proteins with organic mercury in alkaline medium without any chemical pre-reducing agents

Energy Technology Data Exchange (ETDEWEB)

Campanella, Beatrice; Onor, Massimo [National Research Council of Italy, C.N.R., Istituto di Chimica dei Composti Organo Metallici-ICCOM- UOS Pisa, Area di Ricerca, Via G. Moruzzi 1, 56124 Pisa (Italy); Ferrari, Carlo [National Research Council of Italy, C.N.R., Istituto Nazionale di Ottica, INO-UOS Pisa, Area di Ricerca, Via G. Moruzzi 1, 56124 Pisa (Italy); D’Ulivo, Alessandro [National Research Council of Italy, C.N.R., Istituto di Chimica dei Composti Organo Metallici-ICCOM- UOS Pisa, Area di Ricerca, Via G. Moruzzi 1, 56124 Pisa (Italy); Bramanti, Emilia, E-mail: bramanti@pi.iccom.cnr.it [National Research Council of Italy, C.N.R., Istituto di Chimica dei Composti Organo Metallici-ICCOM- UOS Pisa, Area di Ricerca, Via G. Moruzzi 1, 56124 Pisa (Italy)

2014-09-16

Highlights: • A simple procedure for the derivatization of proteins disulfide bonds. • Cysteine groups in several proteins derivatised with pHMB in alkaline media. • 75–100% labelling of cysteines in proteins with pHMB. - Abstract: In this work we have studied the derivatization of protein disulfide bonds with p-Hydroxymercurybenzoate (pHMB) in strong alkaline medium without any preliminary reduction. The reaction has been followed by the determination of the protein–pHMB complex using size exclusion chromatography coupled to a microwave/UV mercury oxidation system for the on-line oxidation of free and protein-complexed pHMB and atomic fluorescence spectrometry (SEC–CVG–AFS) detection. The reaction has been optimized by an experimental design using lysozyme as a model protein and applied to several thiolic proteins. The proposed method reports, for the first time, that it is possible to label 75–100% cysteines of proteins and, thus, to determine thiolic proteins without the need of any reducing step to obtain reduced -SH groups before mercury labelling. We obtained a detection limit of 100 nmol L{sup −1} based on a signal-to-noise ratio of 3 for unbound and complexed pHMB, corresponding to a detection limit of proteins ranged between 3 and 360 nmol L{sup −1}, depending on the number of cysteines in the protein sequence.

Direct, simple derivatization of disulfide bonds in proteins with organic mercury in alkaline medium without any chemical pre-reducing agents

International Nuclear Information System (INIS)

Campanella, Beatrice; Onor, Massimo; Ferrari, Carlo; D’Ulivo, Alessandro; Bramanti, Emilia

2014-01-01

Highlights: • A simple procedure for the derivatization of proteins disulfide bonds. • Cysteine groups in several proteins derivatised with pHMB in alkaline media. • 75–100% labelling of cysteines in proteins with pHMB. - Abstract: In this work we have studied the derivatization of protein disulfide bonds with p-Hydroxymercurybenzoate (pHMB) in strong alkaline medium without any preliminary reduction. The reaction has been followed by the determination of the protein–pHMB complex using size exclusion chromatography coupled to a microwave/UV mercury oxidation system for the on-line oxidation of free and protein-complexed pHMB and atomic fluorescence spectrometry (SEC–CVG–AFS) detection. The reaction has been optimized by an experimental design using lysozyme as a model protein and applied to several thiolic proteins. The proposed method reports, for the first time, that it is possible to label 75–100% cysteines of proteins and, thus, to determine thiolic proteins without the need of any reducing step to obtain reduced -SH groups before mercury labelling. We obtained a detection limit of 100 nmol L −1 based on a signal-to-noise ratio of 3 for unbound and complexed pHMB, corresponding to a detection limit of proteins ranged between 3 and 360 nmol L −1 , depending on the number of cysteines in the protein sequence

A Mesoscopic Model for Protein-Protein Interactions in Solution

OpenAIRE

Lund, Mikael; Jönsson, Bo

2003-01-01

Protein self-association may be detrimental in biological systems, but can be utilized in a controlled fashion for protein crystallization. It is hence of considerable interest to understand how factors like solution conditions prevent or promote aggregation. Here we present a computational model describing interactions between protein molecules in solution. The calculations are based on a molecular description capturing the detailed structure of the protein molecule using x-ray or nuclear ma...

Nuclear protein import is reduced in cells expressing nuclear envelopathy-causing lamin A mutants

International Nuclear Information System (INIS)

Busch, Albert; Kiel, Tilman; Heupel, Wolfgang-M.; Wehnert, Manfred; Huebner, Stefan

2009-01-01

Lamins, which form the nuclear lamina, not only constitute an important determinant of nuclear architecture, but additionally play essential roles in many nuclear functions. Mutations in A-type lamins cause a wide range of human genetic disorders (laminopathies). The importance of lamin A (LaA) in the spatial arrangement of nuclear pore complexes (NPCs) prompted us to study the role of LaA mutants in nuclear protein transport. Two mutants, causing prenatal skin disease restrictive dermopathy (RD) and the premature aging disease Hutchinson Gilford progeria syndrome, were used for expression in HeLa cells to investigate their impact on the subcellular localization of NPC-associated proteins and nuclear protein import. Furthermore, dynamics of the LaA mutants within the nuclear lamina were studied. We observed affected localization of NPC-associated proteins, diminished lamina dynamics for both LaA mutants and reduced nuclear import of representative cargo molecules. Intriguingly, both LaA mutants displayed similar effects on nuclear morphology and functions, despite their differences in disease severity. Reduced nuclear protein import was also seen in RD fibroblasts and impaired lamina dynamics for the nucleoporin Nup153. Our data thus represent the first study of a direct link between LaA mutant expression and reduced nuclear protein import.

Prediction of protein-protein interactions between viruses and human by an SVM model

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Cui Guangyu

2012-05-01

Full Text Available Abstract Background Several computational methods have been developed to predict protein-protein interactions from amino acid sequences, but most of those methods are intended for the interactions within a species rather than for interactions across different species. Methods for predicting interactions between homogeneous proteins are not appropriate for finding those between heterogeneous proteins since they do not distinguish the interactions between proteins of the same species from those of different species. Results We developed a new method for representing a protein sequence of variable length in a frequency vector of fixed length, which encodes the relative frequency of three consecutive amino acids of a sequence. We built a support vector machine (SVM model to predict human proteins that interact with virus proteins. In two types of viruses, human papillomaviruses (HPV and hepatitis C virus (HCV, our SVM model achieved an average accuracy above 80%, which is higher than that of another SVM model with a different representation scheme. Using the SVM model and Gene Ontology (GO annotations of proteins, we predicted new interactions between virus proteins and human proteins. Conclusions Encoding the relative frequency of amino acid triplets of a protein sequence is a simple yet powerful representation method for predicting protein-protein interactions across different species. The representation method has several advantages: (1 it enables a prediction model to achieve a better performance than other representations, (2 it generates feature vectors of fixed length regardless of the sequence length, and (3 the same representation is applicable to different types of proteins.

EFFECTS OF PROTEIN-XANTHOPHYLL (PX CONCENTRATE OF ALFALFA ADDITIVE TO CRUDE PROTEIN-REDUCED DIETS ON NITROGEN EXCRETION, GROWTH PERFORMANCE AND MEAT QUALITY OF PIGS

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Eugeniusz GRELA

2009-06-01

Full Text Available The infl uence of protein-xanthophyll (PX concentrate of alfalfa supplement to crude protein-reduced diets was examined in relation to nitrogen excretion, performance parameters and pig meat quality. The investigations included 60 growers (PL x PLW x Duroc crossbreeds assigned to 3 groups. The conclusion is that there is a large potential to decrease nitrogen emission to the environment by 10% lowering of dietary crude protein intake along with reduced animal growth rate and elevated mixture utilization. Inclusion of a protein-xanthophyll concentrate (PX of alfalfa to the diet is likely to diminish disadvantageous productive parameters arising from limiting of total crude protein level in relation to the requirements of pigs feeding norms [1993]. At the same time, it improves feed nitrogen utilization and reduces noxious odour emissions from a piggery. The components of a protein-xanthophyll concentrate (PX contribute to increased liver and kidney weight.

Reduced expression of G protein-coupled receptor kinases in schizophrenia but not in schizoaffective disorder

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Bychkov, ER; Ahmed, MR; Gurevich, VV; Benovic, JL; Gurevich, EV

2011-01-01

Alterations of multiple G protein-mediated signaling pathways are detected in schizophrenia. G protein-coupled receptor kinases (GRKs) and arrestins terminate signaling by G protein-coupled receptors exerting powerful influence on receptor functions. Modifications of arrestin and/or GRKs expression may contribute to schizophrenia pathology. Cortical expression of arrestins and GRKs was measured postmortem in control and subjects with schizophrenia or schizoaffective disorder. Additionally, arrestin/GRK expression was determined in elderly patients with schizophrenia and age-matched control. Patients with schizophrenia, but not schizoaffective disorder, displayed reduced concentration of arrestin and GRK mRNAs and GRK3 protein. Arrestins and GRK significantly decreased with age. In elderly patients, GRK6 was reduced, with other GRKs and arrestins unchanged. Reduced cortical concentration of GRKs in schizophrenia (resembling that in aging) may result in altered G protein-dependent signaling, thus contributing to prefrontal deficits in schizophrenia. The data suggest distinct molecular mechanisms underlying schizophrenia and schizoaffective disorder. PMID:21784156

A reduced amino acid alphabet for understanding and designing protein adaptation to mutation.

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Etchebest, C; Benros, C; Bornot, A; Camproux, A-C; de Brevern, A G

2007-11-01

Protein sequence world is considerably larger than structure world. In consequence, numerous non-related sequences may adopt similar 3D folds and different kinds of amino acids may thus be found in similar 3D structures. By grouping together the 20 amino acids into a smaller number of representative residues with similar features, sequence world simplification may be achieved. This clustering hence defines a reduced amino acid alphabet (reduced AAA). Numerous works have shown that protein 3D structures are composed of a limited number of building blocks, defining a structural alphabet. We previously identified such an alphabet composed of 16 representative structural motifs (5-residues length) called Protein Blocks (PBs). This alphabet permits to translate the structure (3D) in sequence of PBs (1D). Based on these two concepts, reduced AAA and PBs, we analyzed the distributions of the different kinds of amino acids and their equivalences in the structural context. Different reduced sets were considered. Recurrent amino acid associations were found in all the local structures while other were specific of some local structures (PBs) (e.g Cysteine, Histidine, Threonine and Serine for the alpha-helix Ncap). Some similar associations are found in other reduced AAAs, e.g Ile with Val, or hydrophobic aromatic residues Trp with Phe and Tyr. We put into evidence interesting alternative associations. This highlights the dependence on the information considered (sequence or structure). This approach, equivalent to a substitution matrix, could be useful for designing protein sequence with different features (for instance adaptation to environment) while preserving mainly the 3D fold.

High-fiber diets with reduced crude protein for commercial layers

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MFFM Praes

2014-06-01

Full Text Available This study aimed at evaluating diets containing different fiber sources and two crude protein levels on the performance, egg quality, and nitrogen metabolism of commercial layers. In total, 392 48-wk-old Isa Brown layers were distributed according to a completely randomized experimental design in a 3x2+1 (control factorial arrangement, resulting in seven treatments with seven replicates of eight birds each. Treatments consisted of three fiber feedstuffs (cottonseed hulls, soybean hulls, and rice hulls and two dietary crude protein levels (12% and 16%. Cottonseed hulls associated with the high crude protein level (16% resulted in the worst feed conversion ratio per dozen eggs. Diets with 16% crude protein resulted in the highest feed intake, egg production, egg weight, egg mass values, and improved feed conversion ratio (kg eggs/kg feed. The dietary inclusion of soybean hulls determined low yolk pigmentation, and of rice hulls, low egg specific gravity. The 16% crude protein diet with rice hulls promoted the best feed conversion ratio. Hens fed the reference diet presented higher egg mass and better feed conversion ratio per kg eggs and per dozen eggs. Hens fed the diets with low crude protein level (12% had reduced nitrogen excretion, but presented worse egg production.

Protein folding simulations: from coarse-grained model to all-atom model.

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Zhang, Jian; Li, Wenfei; Wang, Jun; Qin, Meng; Wu, Lei; Yan, Zhiqiang; Xu, Weixin; Zuo, Guanghong; Wang, Wei

2009-06-01

Protein folding is an important and challenging problem in molecular biology. During the last two decades, molecular dynamics (MD) simulation has proved to be a paramount tool and was widely used to study protein structures, folding kinetics and thermodynamics, and structure-stability-function relationship. It was also used to help engineering and designing new proteins, and to answer even more general questions such as the minimal number of amino acid or the evolution principle of protein families. Nowadays, the MD simulation is still undergoing rapid developments. The first trend is to toward developing new coarse-grained models and studying larger and more complex molecular systems such as protein-protein complex and their assembling process, amyloid related aggregations, and structure and motion of chaperons, motors, channels and virus capsides; the second trend is toward building high resolution models and explore more detailed and accurate pictures of protein folding and the associated processes, such as the coordination bond or disulfide bond involved folding, the polarization, charge transfer and protonate/deprotonate process involved in metal coupled folding, and the ion permeation and its coupling with the kinetics of channels. On these new territories, MD simulations have given many promising results and will continue to offer exciting views. Here, we review several new subjects investigated by using MD simulations as well as the corresponding developments of appropriate protein models. These include but are not limited to the attempt to go beyond the topology based Gō-like model and characterize the energetic factors in protein structures and dynamics, the study of the thermodynamics and kinetics of disulfide bond involved protein folding, the modeling of the interactions between chaperonin and the encapsulated protein and the protein folding under this circumstance, the effort to clarify the important yet still elusive folding mechanism of protein BBL

Gestational diabetes is characterized by reduced mitochondrial protein expression and altered calcium signaling proteins in skeletal muscle.

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Kristen E Boyle

Full Text Available The rising prevalence of gestational diabetes mellitus (GDM affects up to 18% of pregnant women with immediate and long-term metabolic consequences for both mother and infant. Abnormal glucose uptake and lipid oxidation are hallmark features of GDM prompting us to use an exploratory proteomics approach to investigate the cellular mechanisms underlying differences in skeletal muscle metabolism between obese pregnant women with GDM (OGDM and obese pregnant women with normal glucose tolerance (ONGT. Functional validation was performed in a second cohort of obese OGDM and ONGT pregnant women. Quantitative proteomic analysis in rectus abdominus skeletal muscle tissue collected at delivery revealed reduced protein content of mitochondrial complex I (C-I subunits (NDUFS3, NDUFV2 and altered content of proteins involved in calcium homeostasis/signaling (calcineurin A, α1-syntrophin, annexin A4 in OGDM (n = 6 vs. ONGT (n = 6. Follow-up analyses showed reduced enzymatic activity of mitochondrial complexes C-I, C-III, and C-IV (-60-75% in the OGDM (n = 8 compared with ONGT (n = 10 subjects, though no differences were observed for mitochondrial complex protein content. Upstream regulators of mitochondrial biogenesis and oxidative phosphorylation were not different between groups. However, AMPK phosphorylation was dramatically reduced by 75% in the OGDM women. These data suggest that GDM is associated with reduced skeletal muscle oxidative phosphorylation and disordered calcium homeostasis. These relationships deserve further attention as they may represent novel risk factors for development of GDM and may have implications on the effectiveness of physical activity interventions on both treatment strategies for GDM and for prevention of type 2 diabetes postpartum.

DockQ: A Quality Measure for Protein-Protein Docking Models.

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Sankar Basu

Full Text Available The state-of-the-art to assess the structural quality of docking models is currently based on three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and standardized by CAPRI. These quality measures quantify different aspects of the quality of a particular docking model and need to be viewed together to reveal the true quality, e.g. a model with relatively poor LRMS (>10Å might still qualify as 'acceptable' with a descent Fnat (>0.50 and iRMS (<3.0Å. This is also the reason why the so called CAPRI criteria for assessing the quality of docking models is defined by applying various ad-hoc cutoffs on these measures to classify a docking model into the four classes: Incorrect, Acceptable, Medium, or High quality. This classification has been useful in CAPRI, but since models are grouped in only four bins it is also rather limiting, making it difficult to rank models, correlate with scoring functions or use it as target function in machine learning algorithms. Here, we present DockQ, a continuous protein-protein docking model quality measure derived by combining Fnat, LRMS, and iRMS to a single score in the range [0, 1] that can be used to assess the quality of protein docking models. By using DockQ on CAPRI models it is possible to almost completely reproduce the original CAPRI classification into Incorrect, Acceptable, Medium and High quality. An average PPV of 94% at 90% Recall demonstrating that there is no need to apply predefined ad-hoc cutoffs to classify docking models. Since DockQ recapitulates the CAPRI classification almost perfectly, it can be viewed as a higher resolution version of the CAPRI classification, making it possible to estimate model quality in a more quantitative way using Z-scores or sum of top ranked models, which has been so valuable for the CASP community. The possibility to directly correlate a quality measure to a scoring function has been crucial for the development of scoring functions for

Modeling on-column reduction of trisulfide bonds in monoclonal antibodies during protein A chromatography.

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Ghose, Sanchayita; Rajshekaran, Rupshika; Labanca, Marisa; Conley, Lynn

2017-01-06

Trisulfides can be a common post-translational modification in many recombinant monoclonal antibodies. These are a source of product heterogeneity that add to the complexity of product characterization and hence, need to be reduced for consistent product quality. Trisulfide bonds can be converted to the regular disulfide bonds by incorporating a novel cysteine wash step during Protein A affinity chromatography. An empirical model is developed for this on-column reduction reaction to compare the reaction rates as a function of typical operating parameters such as temperature, cysteine concentration, reaction time and starting level of trisulfides. The model presented here is anticipated to assist in the development of optimal wash conditions for the Protein A step to effectively reduce trisulfides to desired levels. Copyright © 2016 Elsevier B.V. All rights reserved.

Proteochemometric model for predicting the inhibition of penicillin-binding proteins

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Nabu, Sunanta; Nantasenamat, Chanin; Owasirikul, Wiwat; Lawung, Ratana; Isarankura-Na-Ayudhya, Chartchalerm; Lapins, Maris; Wikberg, Jarl E. S.; Prachayasittikul, Virapong

2015-02-01

Neisseria gonorrhoeae infection threatens to become an untreatable sexually transmitted disease in the near future owing to the increasing emergence of N. gonorrhoeae strains with reduced susceptibility and resistance to the extended-spectrum cephalosporins (ESCs), i.e. ceftriaxone and cefixime, which are the last remaining option for first-line treatment of gonorrhea. Alteration of the penA gene, encoding penicillin-binding protein 2 (PBP2), is the main mechanism conferring penicillin resistance including reduced susceptibility and resistance to ESCs. To predict and investigate putative amino acid mutations causing β-lactam resistance particularly for ESCs, we applied proteochemometric modeling to generalize N. gonorrhoeae susceptibility data for predicting the interaction of PBP2 with therapeutic β-lactam antibiotics. This was afforded by correlating publicly available data on antimicrobial susceptibility of wild-type and mutant N. gonorrhoeae strains for penicillin-G, cefixime and ceftriaxone with 50 PBP2 protein sequence data using partial least-squares projections to latent structures. The generated model revealed excellent predictability ( R 2 = 0.91, Q 2 = 0.77, Q Ext 2 = 0.78). Moreover, our model identified amino acid mutations in PBP2 with the highest impact on antimicrobial susceptibility and provided information on physicochemical properties of amino acid mutations affecting antimicrobial susceptibility. Our model thus provided insight into the physicochemical basis for resistance development in PBP2 suggesting its use for predicting and monitoring novel PBP2 mutations that may emerge in the future.

Fish protein hydrolysate elevates plasma bile acids and reduces visceral adipose tissue mass in rats

DEFF Research Database (Denmark)

Liaset, Bjørn; Madsen, Lise; Hao, Qin

2009-01-01

levels relative to rats fed soy protein or casein. Concomitantly, the saithe FPH fed rats had reduced liver lipids and fasting plasma TAG levels. Furthermore, visceral adipose tissue mass was reduced and expression of genes involved in fatty acid oxidation and energy expenditure was induced in perirenal....../retroperitoneal adipose tissues of rats fed saithe FPH. Our results provide the first evidence that dietary protein sources with different amino acid compositions can modulate the level of plasma bile acids and our data suggest potential novel mechanisms by which dietary protein sources can affect energy metabolism....

Reduced synaptic vesicle protein degradation at lysosomes curbs TBC1D24/sky-induced neurodegeneration.

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Fernandes, Ana Clara; Uytterhoeven, Valerie; Kuenen, Sabine; Wang, Yu-Chun; Slabbaert, Jan R; Swerts, Jef; Kasprowicz, Jaroslaw; Aerts, Stein; Verstreken, Patrik

2014-11-24

Synaptic demise and accumulation of dysfunctional proteins are thought of as common features in neurodegeneration. However, the mechanisms by which synaptic proteins turn over remain elusive. In this paper, we study Drosophila melanogaster lacking active TBC1D24/Skywalker (Sky), a protein that in humans causes severe neurodegeneration, epilepsy, and DOOR (deafness, onychdystrophy, osteodystrophy, and mental retardation) syndrome, and identify endosome-to-lysosome trafficking as a mechanism for degradation of synaptic vesicle-associated proteins. In fly sky mutants, synaptic vesicles traveled excessively to endosomes. Using chimeric fluorescent timers, we show that synaptic vesicle-associated proteins were younger on average, suggesting that older proteins are more efficiently degraded. Using a genetic screen, we find that reducing endosomal-to-lysosomal trafficking, controlled by the homotypic fusion and vacuole protein sorting (HOPS) complex, rescued the neurotransmission and neurodegeneration defects in sky mutants. Consistently, synaptic vesicle proteins were older in HOPS complex mutants, and these mutants also showed reduced neurotransmission. Our findings define a mechanism in which synaptic transmission is facilitated by efficient protein turnover at lysosomes and identify a potential strategy to suppress defects arising from TBC1D24 mutations in humans. © 2014 Fernandes et al.

Modelling of proteins in membranes

DEFF Research Database (Denmark)

Sperotto, Maria Maddalena; May, S.; Baumgaertner, A.

2006-01-01

This review describes some recent theories and simulations of mesoscopic and microscopic models of lipid membranes with embedded or attached proteins. We summarize results supporting our understanding of phenomena for which the activities of proteins in membranes are expected to be significantly ...

The reduced kinome of Ostreococcus tauri: core eukaryotic signalling components in a tractable model species.

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Hindle, Matthew M; Martin, Sarah F; Noordally, Zeenat B; van Ooijen, Gerben; Barrios-Llerena, Martin E; Simpson, T Ian; Le Bihan, Thierry; Millar, Andrew J

2014-08-02

The current knowledge of eukaryote signalling originates from phenotypically diverse organisms. There is a pressing need to identify conserved signalling components among eukaryotes, which will lead to the transfer of knowledge across kingdoms. Two useful properties of a eukaryote model for signalling are (1) reduced signalling complexity, and (2) conservation of signalling components. The alga Ostreococcus tauri is described as the smallest free-living eukaryote. With less than 8,000 genes, it represents a highly constrained genomic palette. Our survey revealed 133 protein kinases and 34 protein phosphatases (1.7% and 0.4% of the proteome). We conducted phosphoproteomic experiments and constructed domain structures and phylogenies for the catalytic protein-kinases. For each of the major kinases families we review the completeness and divergence of O. tauri representatives in comparison to the well-studied kinomes of the laboratory models Arabidopsis thaliana and Saccharomyces cerevisiae, and of Homo sapiens. Many kinase clades in O. tauri were reduced to a single member, in preference to the loss of family diversity, whereas TKL and ABC1 clades were expanded. We also identified kinases that have been lost in A. thaliana but retained in O. tauri. For three, contrasting eukaryotic pathways - TOR, MAPK, and the circadian clock - we established the subset of conserved components and demonstrate conserved sites of substrate phosphorylation and kinase motifs. We conclude that O. tauri satisfies our two central requirements. Several of its kinases are more closely related to H. sapiens orthologs than S. cerevisiae is to H. sapiens. The greatly reduced kinome of O. tauri is therefore a suitable model for signalling in free-living eukaryotes.

Resistance training reduces whole-body protein turnover and improves net protein retention in untrained young males.

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Hartman, Joseph W; Moore, Daniel R; Phillips, Stuart M

2006-10-01

It is thought that resistance exercise results in an increased need for dietary protein; however, data also exists to support the opposite conclusion. The purpose of this study was to determine the impact of resistance exercise training on protein metabolism in novices with the hypothesis that resistance training would reduce protein turnover and improve whole-body protein retention. Healthy males (n = 8, 22 +/- 1 y, BMI = 25.3 +/- 1.8 kg.m(-2)) participated in a progressive whole-body split routine resistance-training program 5d/week for 12 weeks. Before (PRE) and after (POST) the training, oral [15N]-glycine ingestion was used to assess nitrogen flux (Q), protein synthesis (PS), protein breakdown (PB), and net protein balance (NPB = PS-PB). Macronutrient intake was controlled over a 5d period PRE and POST, while estimates of protein turnover and urinary nitrogen balance (N(bal) = N(in) - urine N(out)) were conducted. Bench press and leg press increased 40% and 50%, respectively (p training-induced increases in both NPB (PRE = 0.22 +/- 0.13 g.kg(-1).d(-1); POST = 0.54 +/- 0.08 g.kg(-1).d(-1)) and urinary nitrogen balance (PRE = 2.8 +/- 1.7 g N.d(-1); POST = 6.5 +/- 0.9 g N.d(-1)) were observed. A program of resistance training that induced significant muscle hypertrophy resulted in reductions of both whole-body PS and PB, but an improved NPB, which favoured the accretion of skeletal muscle protein. Urinary nitrogen balance increased after training. The reduction in PS and PB and a higher NPB in combination with an increased nitrogen balance after training suggest that dietary requirements for protein in novice resistance-trained athletes are not higher, but lower, after resistance training.

RNAi reduces expression and intracellular retention of mutant cartilage oligomeric matrix protein.

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Karen L Posey

2010-04-01

Full Text Available Mutations in cartilage oligomeric matrix protein (COMP, a large extracellular glycoprotein expressed in musculoskeletal tissues, cause two skeletal dysplasias, pseudoachondroplasia and multiple epiphyseal dysplasia. These mutations lead to massive intracellular retention of COMP, chondrocyte death and loss of growth plate chondrocytes that are necessary for linear growth. In contrast, COMP null mice have only minor growth plate abnormalities, normal growth and longevity. This suggests that reducing mutant and wild-type COMP expression in chondrocytes may prevent the toxic cellular phenotype causing the skeletal dysplasias. We tested this hypothesis using RNA interference to reduce steady state levels of COMP mRNA. A panel of shRNAs directed against COMP was tested. One shRNA (3B reduced endogenous and recombinant COMP mRNA dramatically, regardless of expression levels. The activity of the shRNA against COMP mRNA was maintained for up to 10 weeks. We also demonstrate that this treatment reduced ER stress. Moreover, we show that reducing steady state levels of COMP mRNA alleviates intracellular retention of other extracellular matrix proteins associated with the pseudoachondroplasia cellular pathology. These findings are a proof of principle and the foundation for the development of a therapeutic intervention based on reduction of COMP expression.

Reduced endothelial thioredoxin-interacting protein protects arteries from damage induced by metabolic stress in vivo.

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Bedarida, Tatiana; Domingues, Alison; Baron, Stephanie; Ferreira, Chrystophe; Vibert, Francoise; Cottart, Charles-Henry; Paul, Jean-Louis; Escriou, Virginie; Bigey, Pascal; Gaussem, Pascale; Leguillier, Teddy; Nivet-Antoine, Valerie

2018-06-01

Although thioredoxin-interacting protein (TXNIP) is involved in a variety of biologic functions, the contribution of endothelial TXNIP has not been well defined. To investigate the endothelial function of TXNIP, we generated a TXNIP knockout mouse on the Cdh5-cre background (TXNIP fl/fl cdh5 cre ). Control (TXNIP fl/fl ) and TXNIP fl/fl cdh5 cre mice were fed a high protein-low carbohydrate (HP-LC) diet for 3 mo to induce metabolic stress. We found that TXNIP fl/fl and TXNIP fl/fl cdh5 cre mice on an HP-LC diet displayed impaired glucose tolerance and dyslipidemia concretizing the metabolic stress induced. We evaluated the impact of this metabolic stress on mice with reduced endothelial TXNIP expression with regard to arterial structure and function. TXNIP fl/fl cdh5 cre mice on an HP-LC diet exhibited less endothelial dysfunction than littermate mice on an HP-LC diet. These mice were protected from decreased aortic medial cell content, impaired aortic distensibility, and increased plasminogen activator inhibitor 1 secretion. This protective effect came with lower oxidative stress and lower inflammation, with a reduced NLRP3 inflammasome expression, leading to a decrease in cleaved IL-1β. We also show the major role of TXNIP in inflammation with a knockdown model, using a TXNIP-specific, small interfering RNA included in a lipoplex. These findings demonstrate a key role for endothelial TXNIP in arterial impairments induced by metabolic stress, making endothelial TXNIP a potential therapeutic target.-Bedarida, T., Domingues, A., Baron, S., Ferreira, C., Vibert, F., Cottart, C.-H., Paul, J.-L., Escriou, V., Bigey, P., Gaussem, P., Leguillier, T., Nivet-Antoine, V. Reduced endothelial thioredoxin-interacting protein protects arteries from damage induced by metabolic stress in vivo.

Fish protein intake induces fast-muscle hypertrophy and reduces liver lipids and serum glucose levels in rats.

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Kawabata, Fuminori; Mizushige, Takafumi; Uozumi, Keisuke; Hayamizu, Kohsuke; Han, Li; Tsuji, Tomoko; Kishida, Taro

2015-01-01

In our previous study, fish protein was proven to reduce serum lipids and body fat accumulation by skeletal muscle hypertrophy and enhancing basal energy expenditure in rats. In the present study, we examined the precise effects of fish protein intake on different skeletal muscle fiber types and metabolic gene expression of the muscle. Fish protein increased fast-twitch muscle weight, reduced liver triglycerides and serum glucose levels, compared with the casein diet after 6 or 8 weeks of feeding. Furthermore, fish protein upregulated the gene expressions of a fast-twitch muscle-type marker and a glucose transporter in the muscle. These results suggest that fish protein induces fast-muscle hypertrophy, and the enhancement of basal energy expenditure by muscle hypertrophy and the increase in muscle glucose uptake reduced liver lipids and serum glucose levels. The present results also imply that fish protein intake causes a slow-to-fast shift in muscle fiber type.

Building alternate protein structures using the elastic network model.

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Yang, Qingyi; Sharp, Kim A

2009-02-15

We describe a method for efficiently generating ensembles of alternate, all-atom protein structures that (a) differ significantly from the starting structure, (b) have good stereochemistry (bonded geometry), and (c) have good steric properties (absence of atomic overlap). The method uses reconstruction from a series of backbone framework structures that are obtained from a modified elastic network model (ENM) by perturbation along low-frequency normal modes. To ensure good quality backbone frameworks, the single force parameter ENM is modified by introducing two more force parameters to characterize the interaction between the consecutive carbon alphas and those within the same secondary structure domain. The relative stiffness of the three parameters is parameterized to reproduce B-factors, while maintaining good bonded geometry. After parameterization, violations of experimental Calpha-Calpha distances and Calpha-Calpha-Calpha pseudo angles along the backbone are reduced to less than 1%. Simultaneously, the average B-factor correlation coefficient improves to R = 0.77. Two applications illustrate the potential of the approach. (1) 102,051 protein backbones spanning a conformational space of 15 A root mean square deviation were generated from 148 nonredundant proteins in the PDB database, and all-atom models with minimal bonded and nonbonded violations were produced from this ensemble of backbone structures using the SCWRL side chain building program. (2) Improved backbone templates for homology modeling. Fifteen query sequences were each modeled on two targets. For each of the 30 target frameworks, dozens of improved templates could be produced In all cases, improved full atom homology models resulted, of which 50% could be identified blind using the D-Fire statistical potential. (c) 2008 Wiley-Liss, Inc.

Protein adsorption on nanoparticles: model development using computer simulation

International Nuclear Information System (INIS)

Shao, Qing; Hall, Carol K

2016-01-01

The adsorption of proteins on nanoparticles results in the formation of the protein corona, the composition of which determines how nanoparticles influence their biological surroundings. We seek to better understand corona formation by developing models that describe protein adsorption on nanoparticles using computer simulation results as data. Using a coarse-grained protein model, discontinuous molecular dynamics simulations are conducted to investigate the adsorption of two small proteins (Trp-cage and WW domain) on a model nanoparticle of diameter 10.0 nm at protein concentrations ranging from 0.5 to 5 mM. The resulting adsorption isotherms are well described by the Langmuir, Freundlich, Temkin and Kiselev models, but not by the Elovich, Fowler–Guggenheim and Hill–de Boer models. We also try to develop a generalized model that can describe protein adsorption equilibrium on nanoparticles of different diameters in terms of dimensionless size parameters. The simulation results for three proteins (Trp-cage, WW domain, and GB3) on four nanoparticles (diameter  =  5.0, 10.0, 15.0, and 20.0 nm) illustrate both the promise and the challenge associated with developing generalized models of protein adsorption on nanoparticles. (paper)

Pharmacological inhibition of dynamin II reduces constitutive protein secretion from primary human macrophages.

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Maaike Kockx

Full Text Available Dynamins are fission proteins that mediate endocytic and exocytic membrane events and are pharmacological therapeutic targets. These studies investigate whether dynamin II regulates constitutive protein secretion and show for the first time that pharmacological inhibition of dynamin decreases secretion of apolipoprotein E (apoE and several other proteins constitutively secreted from primary human macrophages. Inhibitors that target recruitment of dynamin to membranes (MiTMABs or directly target the GTPase domain (Dyngo or Dynole series, dose- and time- dependently reduced the secretion of apoE. SiRNA oligo's targeting all isoforms of dynamin II confirmed the involvement of dynamin II in apoE secretion. Inhibition of secretion was not mediated via effects on mRNA or protein synthesis. 2D-gel electrophoresis showed that inhibition occurred after apoE was processed and glycosylated in the Golgi and live cell imaging showed that inhibited secretion was associated with reduced post-Golgi movement of apoE-GFP-containing vesicles. The effect was not restricted to macrophages, and was not mediated by the effects of the inhibitors on microtubules. Inhibition of dynamin also altered the constitutive secretion of other proteins, decreasing the secretion of fibronectin, matrix metalloproteinase 9, Chitinase-3-like protein 1 and lysozyme but unexpectedly increasing the secretion of the inflammatory mediator cyclophilin A. We conclude that pharmacological inhibitors of dynamin II modulate the constitutive secretion of macrophage apoE as a class effect, and that their capacity to modulate protein secretion may affect a range of biological processes.

Ginsenoside F2 reduces hair loss by controlling apoptosis through the sterol regulatory element-binding protein cleavage activating protein and transforming growth factor-β pathways in a dihydrotestosterone-induced mouse model.

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Shin, Heon-Sub; Park, Sang-Yong; Hwang, Eun-Son; Lee, Don-Gil; Mavlonov, Gafurjon Turdalievich; Yi, Tae-Hoo

2014-01-01

This study was conducted to test whether ginsenoside F2 can reduce hair loss by influencing sterol regulatory element-binding protein (SREBP) cleavage-activating protein (SCAP) and the transforming growth factor beta (TGF-β) pathway of apoptosis in dihydrotestosterone (DHT)-treated hair cells and in a DHT-induced hair loss model in mice. Results for ginsenoside F2 were compared with finasteride. DHT inhibits proliferation of hair cells and induces androgenetic alopecia and was shown to activate an apoptosis signal pathway both in vitro and in vivo. The cell-based 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay showed that the proliferation rates of DHT-treated human hair dermal papilla cells (HHDPCs) and HaCaTs increased by 48% in the ginsenoside F2-treated group and by 12% in the finasteride-treated group. Western blot analysis showed that ginsenoside F2 decreased expression of TGF-β2 related factors involved in hair loss. The present study suggested a hair loss related pathway by changing SCAP related apoptosis pathway, which has been known to control cholesterol metabolism. SCAP, sterol regulatory element-binding protein (SREBP) and caspase-12 expression in the ginsenoside F2-treated group were decreased compared to the DHT and finasteride-treated group. C57BL/6 mice were also prepared by injection with DHT and then treated with ginsenoside F2 or finasteride. Hair growth rate, density, thickness measurements and tissue histotological analysis in these groups suggested that ginsenoside F2 suppressed hair cell apoptosis and premature entry to catagen more effectively than finasteride. Our results indicated that ginsenoside F2 decreased the expression of TGF-β2 and SCAP proteins, which have been suggested to be involved in apoptosis and entry into catagen. This study provides evidence those factors in the SCAP pathway could be targets for hair loss prevention drugs.

Heat-treatment reduces anti-nutritional phytochemicals and maintains protein quality in genetically improved hulled soybean flour

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Ariela Werneck de Carvalho

2013-06-01

Full Text Available The soybean is a protein source of high biological value. However, the presence of anti-nutritional factors affects its protein quality and limits the bioavailability of other nutrients. The effect of heat-treatment, 150 ºC for 30 minutes, on hulled and hull-less soybean flour from the cultivar UFVTN 105AP on urease, trypsin inhibitor activity, protein solubility, amino acid profile, and in vivo protein quality was investigated. The treatment reduced the trypsin inhibitor activity and urease, but it did not affect protein solubility. Protein Efficiency Coefficient (PER values of the flours were similar, and the PER of the hull-less soybean flour did not differ from casein. The Net Protein Ratio (NPR did not differ between the experimental groups. The True Digestibility (TD of the flours did not differ, but both were lower in casein and the Protein Digestibility Corrected Amino Acid Score (PDCCAS was lower than the TD, due to limited valine determined by the chemical score. Therefore, the flours showed reduced anti-nutritional phytochemicals and similar protein quality, and therefore the whole flours can be used as a source of high quality protein.

On nonlinear reduced order modeling

International Nuclear Information System (INIS)

Abdel-Khalik, Hany S.

2011-01-01

When applied to a model that receives n input parameters and predicts m output responses, a reduced order model estimates the variations in the m outputs of the original model resulting from variations in its n inputs. While direct execution of the forward model could provide these variations, reduced order modeling plays an indispensable role for most real-world complex models. This follows because the solutions of complex models are expensive in terms of required computational overhead, thus rendering their repeated execution computationally infeasible. To overcome this problem, reduced order modeling determines a relationship (often referred to as a surrogate model) between the input and output variations that is much cheaper to evaluate than the original model. While it is desirable to seek highly accurate surrogates, the computational overhead becomes quickly intractable especially for high dimensional model, n ≫ 10. In this manuscript, we demonstrate a novel reduced order modeling method for building a surrogate model that employs only 'local first-order' derivatives and a new tensor-free expansion to efficiently identify all the important features of the original model to reach a predetermined level of accuracy. This is achieved via a hybrid approach in which local first-order derivatives (i.e., gradient) of a pseudo response (a pseudo response represents a random linear combination of original model’s responses) are randomly sampled utilizing a tensor-free expansion around some reference point, with the resulting gradient information aggregated in a subspace (denoted by the active subspace) of dimension much less than the dimension of the input parameters space. The active subspace is then sampled employing the state-of-the-art techniques for global sampling methods. The proposed method hybridizes the use of global sampling methods for uncertainty quantification and local variational methods for sensitivity analysis. In a similar manner to

Modulation of GDP-fucose level for generating proteins with reduced rate of fucosylation (WO2010141855).

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Taupin, Philippe

2011-09-01

The application (WO2010141855) is in the field of glycobiology, and involves the control of the rate of fucosylation of proteins by exogenous factors. It aims at controlling the rate of protein fucosylation with inhibitors (drugs or nucleic acid antagonists) of enzymes involved in the synthesis of GDP-fucose. Mammalian cell lines were cultured in the presence of inhibitors, for example, siRNA. The rates of GDP-fucose in cells and during protein fucosylation were characterized. The level of protein fucosylation decreases rapidly in response to a decrease in GDP-fucose level. The relationship between the rate of fucosylation of proteins and the level of GDP-fucose in a cell is non-linear. Reduction in the rate of protein fucosylation can be achieved with a minimal reduction of the level of GDP-fucose in cells. The paradigm may be used to synthesize proteins and antibodies, with a reduced rate of fucosylation. The application claims that the use of drugs or nucleic acid antagonists that inhibit the enzymes involved in GDP-fucose biosynthesis optimizes the level of GDP-fucose present in cells, and reduces the rate of fucosylation of glycoproteins.

An autoclave treatment reduces the solubility and antigenicity of an allergenic protein found in buckwheat flour.

Science.gov (United States)

Tomotake, Hiroyuki; Yamazaki, Rikio; Yamato, Masayuki

2012-06-01

The effects of an autoclave treatment of buckwheat flour on a 24-kDa allergenic protein were investigated by measuring reduction in solubility and antibody binding. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis showed that the intensity of the major bands, including that of the 24-kDa allergen, was reduced by the autoclave treatment. The protein solubility in buckwheat flour was variably decreased by the autoclave treatment. Enzyme-linked immunosorbent assay analysis using a monoclonal antibody specific for buckwheat 24-kDa protein showed that the reactivity of protein extracts (10 μg/ml) from buckwheat flour was lowered by the autoclave treatment. The autoclave treatment may reduce the major allergen content of buckwheat. Future studies will determine if autoclaving treatments affect the allergenicity of the 24-kDa buckwheat protein.

Quantitative chemogenomics: machine-learning models of protein-ligand interaction.

Science.gov (United States)

Andersson, Claes R; Gustafsson, Mats G; Strömbergsson, Helena

2011-01-01

Chemogenomics is an emerging interdisciplinary field that lies in the interface of biology, chemistry, and informatics. Most of the currently used drugs are small molecules that interact with proteins. Understanding protein-ligand interaction is therefore central to drug discovery and design. In the subfield of chemogenomics known as proteochemometrics, protein-ligand-interaction models are induced from data matrices that consist of both protein and ligand information along with some experimentally measured variable. The two general aims of this quantitative multi-structure-property-relationship modeling (QMSPR) approach are to exploit sparse/incomplete information sources and to obtain more general models covering larger parts of the protein-ligand space, than traditional approaches that focuses mainly on specific targets or ligands. The data matrices, usually obtained from multiple sparse/incomplete sources, typically contain series of proteins and ligands together with quantitative information about their interactions. A useful model should ideally be easy to interpret and generalize well to new unseen protein-ligand combinations. Resolving this requires sophisticated machine-learning methods for model induction, combined with adequate validation. This review is intended to provide a guide to methods and data sources suitable for this kind of protein-ligand-interaction modeling. An overview of the modeling process is presented including data collection, protein and ligand descriptor computation, data preprocessing, machine-learning-model induction and validation. Concerns and issues specific for each step in this kind of data-driven modeling will be discussed. © 2011 Bentham Science Publishers

Immunotherapy Added to Antibiotic Treatment Reduces Relapse of Disease in a Mouse Model of Tuberculosis.

Science.gov (United States)

Mourik, Bas C; Leenen, Pieter J M; de Knegt, Gerjo J; Huizinga, Ruth; van der Eerden, Bram C J; Wang, Jinshan; Krois, Charles R; Napoli, Joseph L; Bakker-Woudenberg, Irma A J M; de Steenwinkel, Jurriaan E M

2017-02-01

Immune-modulating drugs that target myeloid-derived suppressor cells or stimulate natural killer T cells have been shown to reduce mycobacterial loads in tuberculosis (TB). We aimed to determine if a combination of these drugs as adjunct immunotherapy to conventional antibiotic treatment could also increase therapeutic efficacy against TB. In our model of pulmonary TB in mice, we applied treatment with isoniazid, rifampicin, and pyrazinamide for 13 weeks alone or combined with immunotherapy consisting of all-trans retinoic acid, 1,25(OH) 2 -vitamin D3, and α-galactosylceramide. Outcome parameters were mycobacterial load during treatment (therapeutic activity) and 13 weeks after termination of treatment (therapeutic efficacy). Moreover, cellular changes were analyzed using flow cytometry and cytokine expression was assessed at the mRNA and protein levels. Addition of immunotherapy was associated with lower mycobacterial loads after 5 weeks of treatment and significantly reduced relapse of disease after a shortened 13-week treatment course compared with antibiotic treatment alone. This was accompanied by reduced accumulation of immature myeloid cells in the lungs at the end of treatment and increased TNF-α protein levels throughout the treatment period. We demonstrate, in a mouse model of pulmonary TB, that immunotherapy consisting of three clinically approved drugs can improve the therapeutic efficacy of standard antibiotic treatment.

Characterizing and modeling protein-surface interactions in lab-on-chip devices

Science.gov (United States)

Katira, Parag

Protein adsorption on surfaces determines the response of other biological species present in the surrounding solution. This phenomenon plays a major role in the design of biomedical and biotechnological devices. While specific protein adsorption is essential for device function, non-specific protein adsorption leads to the loss of device function. For example, non-specific protein adsorption on bioimplants triggers foreign body response, in biosensors it leads to reduced signal to noise ratios, and in hybrid bionanodevices it results in the loss of confinement and directionality of molecular shuttles. Novel surface coatings are being developed to reduce or completely prevent the non-specific adsorption of proteins to surfaces. A novel quantification technique for extremely low protein coverage on surfaces has been developed. This technique utilizes measurement of the landing rate of microtubule filaments on kinesin proteins adsorbed on a surface to determine the kinesin density. Ultra-low limits of detection, dynamic range, ease of detection and availability of a ready-made kinesin-microtubule kit makes this technique highly suitable for detecting protein adsorption below the detection limits of standard techniques. Secondly, a random sequential adsorption model is presented for protein adsorption to PEO-coated surfaces. The derived analytical expressions accurately predict the observed experimental results from various research groups, suggesting that PEO chains act as almost perfect steric barriers to protein adsorption. These expressions can be used to predict the performance of a variety of systems towards resisting protein adsorption and can help in the design of better non-fouling surface coatings. Finally, in biosensing systems, target analytes are captured and concentrated on specifically adsorbed proteins for detection. Non-specific adsorption of proteins results in the loss of signal, and an increase in the background. The use of nanoscale transducers as

Physiologically Based Pharmacokinetic Modeling of Therapeutic Proteins.

Science.gov (United States)

Wong, Harvey; Chow, Timothy W

2017-09-01

Biologics or therapeutic proteins are becoming increasingly important as treatments for disease. The most common class of biologics are monoclonal antibodies (mAbs). Recently, there has been an increase in the use of physiologically based pharmacokinetic (PBPK) modeling in the pharmaceutical industry in drug development. We review PBPK models for therapeutic proteins with an emphasis on mAbs. Due to their size and similarity to endogenous antibodies, there are distinct differences between PBPK models for small molecules and mAbs. The high-level organization of a typical mAb PBPK model consists of a whole-body PBPK model with organ compartments interconnected by both blood and lymph flows. The whole-body PBPK model is coupled with tissue-level submodels used to describe key mechanisms governing mAb disposition including tissue efflux via the lymphatic system, elimination by catabolism, protection from catabolism binding to the neonatal Fc (FcRn) receptor, and nonlinear binding to specific pharmacological targets of interest. The use of PBPK modeling in the development of therapeutic proteins is still in its infancy. Further application of PBPK modeling for therapeutic proteins will help to define its developing role in drug discovery and development. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Whey protein consumption after resistance exercise reduces energy intake at a post-exercise meal.

Science.gov (United States)

Monteyne, Alistair; Martin, Alex; Jackson, Liam; Corrigan, Nick; Stringer, Ellen; Newey, Jack; Rumbold, Penny L S; Stevenson, Emma J; James, Lewis J

2018-03-01

Protein consumption after resistance exercise potentiates muscle protein synthesis, but its effects on subsequent appetite in this context are unknown. This study examined appetite and energy intake following consumption of protein- and carbohydrate-containing drinks after resistance exercise. After familiarisation, 15 resistance training males (age 21 ± 1 years, body mass 78.0 ± 11.9 kg, stature 1.78 ± 0.07 m) completed two randomised, double-blind trials, consisting of lower-body resistance exercise, followed by consumption of a whey protein (PRO 23.9 ± 3.6 g protein) or dextrose (CHO 26.5 ± 3.8 g carbohydrate) drink in the 5 min post-exercise. An ad libitum meal was served 60 min later, with subjective appetite measured throughout. Drinks were flavoured and matched for energy content and volume. The PRO drink provided 0.3 g/kg body mass protein. Ad libitum energy intake (PRO 3742 ± 994 kJ; CHO 4172 ± 1132 kJ; P = 0.007) and mean eating rate (PRO 339 ± 102 kJ/min; CHO 405 ± 154 kJ/min; P = 0.009) were lower during PRO. The change in eating rate was associated with the change in energy intake (R = 0.661, P = 0.007). No interaction effects were observed for subjective measures of appetite. The PRO drink was perceived as creamier and thicker, and less pleasant, sweet and refreshing (P consumption after resistance exercise reduces subsequent energy intake, and this might be partially mediated by a reduced eating rate. Whilst this reduced energy intake is unlikely to impair hypertrophy, it may be of value in supporting an energy deficit for weight loss.

High protein flexibility and reduced hydration water dynamics are key pressure adaptive strategies in prokaryotes

KAUST Repository

Martinez, N.

2016-09-06

Water and protein dynamics on a nanometer scale were measured by quasi-elastic neutron scattering in the piezophile archaeon Thermococcus barophilus and the closely related pressure-sensitive Thermococcus kodakarensis, at 0.1 and 40 MPa. We show that cells of the pressure sensitive organism exhibit higher intrinsic stability. Both the hydration water dynamics and the fast protein and lipid dynamics are reduced under pressure. In contrast, the proteome of T. barophilus is more pressure sensitive than that of T. kodakarensis. The diffusion coefficient of hydration water is reduced, while the fast protein and lipid dynamics are slightly enhanced with increasing pressure. These findings show that the coupling between hydration water and cellular constituents might not be simply a master-slave relationship. We propose that the high flexibility of the T. barophilus proteome associated with reduced hydration water may be the keys to the molecular adaptation of the cells to high hydrostatic pressure.

High protein flexibility and reduced hydration water dynamics are key pressure adaptive strategies in prokaryotes

KAUST Repository

Martinez, N.; Michoud, Gregoire; Cario, A.; Ollivier, J.; Franzetti, B.; Jebbar, M.; Oger, P.; Peters, J.

2016-01-01

Water and protein dynamics on a nanometer scale were measured by quasi-elastic neutron scattering in the piezophile archaeon Thermococcus barophilus and the closely related pressure-sensitive Thermococcus kodakarensis, at 0.1 and 40 MPa. We show that cells of the pressure sensitive organism exhibit higher intrinsic stability. Both the hydration water dynamics and the fast protein and lipid dynamics are reduced under pressure. In contrast, the proteome of T. barophilus is more pressure sensitive than that of T. kodakarensis. The diffusion coefficient of hydration water is reduced, while the fast protein and lipid dynamics are slightly enhanced with increasing pressure. These findings show that the coupling between hydration water and cellular constituents might not be simply a master-slave relationship. We propose that the high flexibility of the T. barophilus proteome associated with reduced hydration water may be the keys to the molecular adaptation of the cells to high hydrostatic pressure.

Modeling of protein electrophoresis in silica colloidal crystals having brush layers of polyacrylamide

Science.gov (United States)

Birdsall, Robert E.; Koshel, Brooke M.; Hua, Yimin; Ratnayaka, Saliya N.; Wirth, Mary J.

2013-01-01

Sieving of proteins in silica colloidal crystals of mm dimensions is characterized for particle diameters of nominally 350 and 500 nm, where the colloidal crystals are chemically modified with a brush layer of polyacrylamide. A model is developed that relates the reduced electrophoretic mobility to the experimentally measurable porosity. The model fits the data with no adjustable parameters for the case of silica colloidal crystals packed in capillaries, for which independent measurements of the pore radii were made from flow data. The model also fits the data for electrophoresis in a highly ordered colloidal crystal formed in a channel, where the unknown pore radius was used as a fitting parameter. Plate heights as small as 0.4 μm point to the potential for miniaturized separations. Band broadening increases as the pore radius approaches the protein radius, indicating that the main contribution to broadening is the spatial heterogeneity of the pore radius. The results quantitatively support the notion that sieving occurs for proteins in silica colloidal crystals, and facilitate design of new separations that would benefit from miniaturization. PMID:23229163

A hidden markov model derived structural alphabet for proteins.

Science.gov (United States)

Camproux, A C; Gautier, R; Tufféry, P

2004-06-04

Understanding and predicting protein structures depends on the complexity and the accuracy of the models used to represent them. We have set up a hidden Markov model that discretizes protein backbone conformation as series of overlapping fragments (states) of four residues length. This approach learns simultaneously the geometry of the states and their connections. We obtain, using a statistical criterion, an optimal systematic decomposition of the conformational variability of the protein peptidic chain in 27 states with strong connection logic. This result is stable over different protein sets. Our model fits well the previous knowledge related to protein architecture organisation and seems able to grab some subtle details of protein organisation, such as helix sub-level organisation schemes. Taking into account the dependence between the states results in a description of local protein structure of low complexity. On an average, the model makes use of only 8.3 states among 27 to describe each position of a protein structure. Although we use short fragments, the learning process on entire protein conformations captures the logic of the assembly on a larger scale. Using such a model, the structure of proteins can be reconstructed with an average accuracy close to 1.1A root-mean-square deviation and for a complexity of only 3. Finally, we also observe that sequence specificity increases with the number of states of the structural alphabet. Such models can constitute a very relevant approach to the analysis of protein architecture in particular for protein structure prediction.

Reduced Insulin/IGF-1 Signaling Restores the Dynamic Properties of Key Stress Granule Proteins during Aging

Directory of Open Access Journals (Sweden)

Marie C. Lechler

2017-01-01

Full Text Available Summary: Low-complexity “prion-like” domains in key RNA-binding proteins (RBPs mediate the reversible assembly of RNA granules. Individual RBPs harboring these domains have been linked to specific neurodegenerative diseases. Although their aggregation in neurodegeneration has been extensively characterized, it remains unknown how the process of aging disturbs RBP dynamics. We show that a wide variety of RNA granule components, including stress granule proteins, become highly insoluble with age in C. elegans and that reduced insulin/insulin-like growth factor 1 (IGF-1 daf-2 receptor signaling efficiently prevents their aggregation. Importantly, stress-granule-related RBP aggregates are associated with reduced fitness. We show that heat shock transcription factor 1 (HSF-1 is a main regulator of stress-granule-related RBP aggregation in both young and aged animals. During aging, increasing DAF-16 activity restores dynamic stress-granule-related RBPs, partly by decreasing the buildup of other misfolded proteins that seed RBP aggregation. Longevity-associated mechanisms found to maintain dynamic RBPs during aging could be relevant for neurodegenerative diseases. : Lechler et al. show that RNA-binding proteins (RBPs including stress granule proteins are prone to aggregate with age in C. elegans. Aggregation of stress granule RBPs with “prion-like” domains is associated with reduced fitness. Their aggregation is prevented by longevity pathways and promoted by the aggregation of other misfolded proteins. Keywords: neurodegenerative diseases, Caenorhabditis elegans, protein aggregation, aging, RNA-binding proteins, stress granules, HSF-1, DAF-2, longevity

DockQ: A Quality Measure for Protein-Protein Docking Models

Science.gov (United States)

Basu, Sankar

2016-01-01

The state-of-the-art to assess the structural quality of docking models is currently based on three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and standardized by CAPRI. These quality measures quantify different aspects of the quality of a particular docking model and need to be viewed together to reveal the true quality, e.g. a model with relatively poor LRMS (>10Å) might still qualify as 'acceptable' with a descent Fnat (>0.50) and iRMS (iRMS to a single score in the range [0, 1] that can be used to assess the quality of protein docking models. By using DockQ on CAPRI models it is possible to almost completely reproduce the original CAPRI classification into Incorrect, Acceptable, Medium and High quality. An average PPV of 94% at 90% Recall demonstrating that there is no need to apply predefined ad-hoc cutoffs to classify docking models. Since DockQ recapitulates the CAPRI classification almost perfectly, it can be viewed as a higher resolution version of the CAPRI classification, making it possible to estimate model quality in a more quantitative way using Z-scores or sum of top ranked models, which has been so valuable for the CASP community. The possibility to directly correlate a quality measure to a scoring function has been crucial for the development of scoring functions for protein structure prediction, and DockQ should be useful in a similar development in the protein docking field. DockQ is available at http://github.com/bjornwallner/DockQ/ PMID:27560519

Beta-carotene encapsulated in food protein nanoparticles reduces peroxyl radical oxidation in Caco-2 cells

Science.gov (United States)

Beta-carotene (BC) was encapsulated by sodium caseinate (SC), whey protein isolate (WPI), and soybean protein isolate (SPI) by the homogenization-evaporation method forming nanoparticles of 78, 90 and 370 nm diameter. Indices of the chemical antioxidant assays, the reducing power, DPPH radical scave...

The Gcn4 transcription factor reduces protein synthesis capacity and extends yeast lifespan.

Science.gov (United States)

Mittal, Nitish; Guimaraes, Joao C; Gross, Thomas; Schmidt, Alexander; Vina-Vilaseca, Arnau; Nedialkova, Danny D; Aeschimann, Florian; Leidel, Sebastian A; Spang, Anne; Zavolan, Mihaela

2017-09-06

In Saccharomyces cerevisiae, deletion of large ribosomal subunit protein-encoding genes increases the replicative lifespan in a Gcn4-dependent manner. However, how Gcn4, a key transcriptional activator of amino acid biosynthesis genes, increases lifespan, is unknown. Here we show that Gcn4 acts as a repressor of protein synthesis. By analyzing the messenger RNA and protein abundance, ribosome occupancy and protein synthesis rate in various yeast strains, we demonstrate that Gcn4 is sufficient to reduce protein synthesis and increase yeast lifespan. Chromatin immunoprecipitation reveals Gcn4 binding not only at genes that are activated, but also at genes, some encoding ribosomal proteins, that are repressed upon Gcn4 overexpression. The promoters of repressed genes contain Rap1 binding motifs. Our data suggest that Gcn4 is a central regulator of protein synthesis under multiple perturbations, including ribosomal protein gene deletions, calorie restriction, and rapamycin treatment, and provide an explanation for its role in longevity and stress response.The transcription factor Gcn4 is known to regulate yeast amino acid synthesis. Here, the authors show that Gcn4 also acts as a repressor of protein biosynthesis in a range of conditions that enhance yeast lifespan, such as ribosomal protein knockout, calorie restriction or mTOR inhibition.

Whey protein reduces early life weight gain in mice fed a high-fat diet

DEFF Research Database (Denmark)

Tranberg, Britt; Hellgren, Lars; Lykkesfeldt, Jens

2013-01-01

An increasing number of studies indicate that dairy products, including whey protein, alleviate several disorders of the metabolic syndrome. Here, we investigated the effects of whey protein isolate (whey) in mice fed a high-fat diet hypothesising that the metabolic effects of whey would...... be associated with changes in the gut microbiota composition. Five-week-old male C57BL/6 mice were fed a high-fat diet ad libitum for 14 weeks with the protein source being either whey or casein. Faeces were collected at week 0, 7, and 13 and the fecal microbiota was analysed by denaturing gradient gel...... reduced weight gain in young C57BL/6 mice fed a high-fat diet compared to casein. Although the effect on weight gain ceased, whey alleviated glucose intolerance, improved insulin sensitivity and reduced plasma cholesterol. These findings could not be explained by changes in food intake or gut microbiota...

Models of protein-ligand crystal structures: trust, but verify.

Science.gov (United States)

Deller, Marc C; Rupp, Bernhard

2015-09-01

X-ray crystallography provides the most accurate models of protein-ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein-ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein-ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein-ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein-ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein-ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein-ligand models for their computational and biological studies, and we provide an overview of how this can be achieved.

Markov dynamic models for long-timescale protein motion.

KAUST Repository

Chiang, Tsung-Han

2010-06-01

Molecular dynamics (MD) simulation is a well-established method for studying protein motion at the atomic scale. However, it is computationally intensive and generates massive amounts of data. One way of addressing the dual challenges of computation efficiency and data analysis is to construct simplified models of long-timescale protein motion from MD simulation data. In this direction, we propose to use Markov models with hidden states, in which the Markovian states represent potentially overlapping probabilistic distributions over protein conformations. We also propose a principled criterion for evaluating the quality of a model by its ability to predict long-timescale protein motions. Our method was tested on 2D synthetic energy landscapes and two extensively studied peptides, alanine dipeptide and the villin headpiece subdomain (HP-35 NleNle). One interesting finding is that although a widely accepted model of alanine dipeptide contains six states, a simpler model with only three states is equally good for predicting long-timescale motions. We also used the constructed Markov models to estimate important kinetic and dynamic quantities for protein folding, in particular, mean first-passage time. The results are consistent with available experimental measurements.

Markov dynamic models for long-timescale protein motion.

KAUST Repository

Chiang, Tsung-Han; Hsu, David; Latombe, Jean-Claude

2010-01-01

Molecular dynamics (MD) simulation is a well-established method for studying protein motion at the atomic scale. However, it is computationally intensive and generates massive amounts of data. One way of addressing the dual challenges of computation efficiency and data analysis is to construct simplified models of long-timescale protein motion from MD simulation data. In this direction, we propose to use Markov models with hidden states, in which the Markovian states represent potentially overlapping probabilistic distributions over protein conformations. We also propose a principled criterion for evaluating the quality of a model by its ability to predict long-timescale protein motions. Our method was tested on 2D synthetic energy landscapes and two extensively studied peptides, alanine dipeptide and the villin headpiece subdomain (HP-35 NleNle). One interesting finding is that although a widely accepted model of alanine dipeptide contains six states, a simpler model with only three states is equally good for predicting long-timescale motions. We also used the constructed Markov models to estimate important kinetic and dynamic quantities for protein folding, in particular, mean first-passage time. The results are consistent with available experimental measurements.

Short communication: Effect of whey protein addition and transglutaminase treatment on the physical and sensory properties of reduced-fat ice cream.

Science.gov (United States)

Danesh, Erfan; Goudarzi, Mostafa; Jooyandeh, Hossein

2017-07-01

The effects of whey protein addition and transglutaminase treatment, alone and in combination, on the physical and sensory properties of reduced-fat ice cream were investigated. Adding whey protein with or without enzyme treatment decreased melting rate, overrun, and hardness of the reduced-fat ice cream; however, the enzyme-treated sample had a higher melting rate and overrun and softer texture. Whey protein-fortified samples showed higher melting resistance, but lower overrun and firmer texture compared with the enzyme-treated sample without added whey protein. Whey protein addition with or without transglutaminase treatment caused an increase in apparent viscosity and a decrease in flow index of the reduced-fat ice cream; nevertheless, the flow behavior of full-fat sample was most similar to the enzyme-treated reduced-fat sample with no added whey protein. Descriptive sensory analyses showed that neither whey protein addition nor transglutaminase treatment significantly influenced the flavor and odor of reduced-fat ice cream, but they both noticeably improved the color and texture of the final product. The results of this study suggest that whey protein addition with transglutaminase treatment improves the physical and sensory properties of reduced-fat ice cream more favorably than does whey protein addition or transglutaminase treatment alone. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The protein C omega-loop substitution Asn2Ile is associated with reduced protein C anticoagulant activity.

LENUS (Irish Health Repository)

Preston, Roger J S

2012-02-01

We report a kindred with heritable protein C (PC) deficiency in which two siblings with severe thrombosis showed a composite type I and IIb PC deficiency phenotype, identified using commercial PC assays (proband: PC antigen 42 u\\/dl, amidolytic activity 40 u\\/dl, anticoagulant activity 9 u\\/dl). The independent PROC nucleotide variations c.669C>A (predictive of Ser181Arg) and c.131C>T (predictive of Asn2Ile) segregated with the type I and type IIb PC deficiency phenotypes respectively, but co-segregated in the siblings with severe thrombosis. Soluble thrombomodulin (sTM)-mediated inhibition of plasma thrombin generation from an individual with PC-Asn2Ile was lower (endogenous thrombin potential (ETP) 56 +\\/- 1% that of ETP determined without sTM) than control plasma (ETP 15 +\\/- 2%) indicating reduced PC anticoagulant activity. Recombinant APC-Asn2Ile exhibited normal amidolytic activity but impaired anticoagulant activity. Protein S (PS)-dependent anticoagulant activity of recombinant APC-Asn2Ile and binding of recombinant APC-Asn2Ile to endothelial protein C receptor (EPCR) were reduced compared to recombinant wild-type APC. Asn2 lies within the omega-loop of the PC\\/APC Gla domain and this region is critical for calcium-induced folding and subsequent interactions with anionic phospholipids, EPCR and PS. The disruption of these interactions in this naturally-occurring PC variant highlights their collective importance in mediating APC anticoagulant activity in vivo.

α-Synuclein-induced lysosomal dysfunction occurs through disruptions in protein trafficking in human midbrain synucleinopathy models.

Science.gov (United States)

Mazzulli, Joseph R; Zunke, Friederike; Isacson, Ole; Studer, Lorenz; Krainc, Dimitri

2016-02-16

Parkinson's disease (PD) is an age-related neurodegenerative disorder characterized by the accumulation of protein aggregates comprised of α-synuclein (α-syn). A major barrier in treatment discovery for PD is the lack of identifiable therapeutic pathways capable of reducing aggregates in human neuronal model systems. Mutations in key components of protein trafficking and cellular degradation machinery represent important risk factors for PD; however, their precise role in disease progression and interaction with α-syn remains unclear. Here, we find that α-syn accumulation reduced lysosomal degradation capacity in human midbrain dopamine models of synucleinopathies through disrupting hydrolase trafficking. Accumulation of α-syn at the cell body resulted in aberrant association with cis-Golgi-tethering factor GM130 and disrupted the endoplasmic reticulum-Golgi localization of rab1a, a key mediator of vesicular transport. Overexpression of rab1a restored Golgi structure, improved hydrolase trafficking and activity, and reduced pathological α-syn in patient neurons. Our work suggests that enhancement of lysosomal hydrolase trafficking may prove beneficial in synucleinopathies and indicates that human midbrain disease models may be useful for identifying critical therapeutic pathways in PD and related disorders.

Ultraviolet-ozone treatment reduces levels of disease-associated prion protein and prion infectivity

Science.gov (United States)

Johnson, C.J.; Gilbert, P.; McKenzie, D.; Pedersen, J.A.; Aiken, Judd M.

2009-01-01

Background. Transmissible spongiform encephalopathies (TSEs) are a group of fatal neurodegenerative diseases caused by novel infectious agents referred to as prions. Prions appear to be composed primarily, if not exclusively, of a misfolded isoform of the cellular prion protein. TSE infectivity is remarkably stable and can resist many aggressive decontamination procedures, increasing human, livestock and wildlife exposure to TSEs. Findings. We tested the hypothesis that UV-ozone treatment reduces levels of the pathogenic prion protein and inactivates the infectious agent. We found that UV-ozone treatment decreased the carbon and prion protein content in infected brain homogenate to levels undetectable by dry-ashing carbon analysis or immunoblotting, respectively. After 8 weeks of ashing, UV-ozone treatment reduced the infectious titer of treated material by a factor of at least 105. A small amount of infectivity, however, persisted despite UV-ozone treatment. When bound to either montmorillonite clay or quartz surfaces, PrPTSE was still susceptible to degradation by UV-ozone. Conclusion. Our findings strongly suggest that UV-ozone treatment can degrade pathogenic prion protein and inactivate prions, even when the agent is associated with surfaces. Using larger UV-ozone doses or combining UV-ozone treatment with other decontaminant methods may allow the sterilization of TSE-contaminated materials. ?? 2009 Aiken et al; licensee BioMed Central Ltd.

Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences

Directory of Open Access Journals (Sweden)

Ji-Yong An

2016-01-01

Full Text Available We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM model and Local Phase Quantization (LPQ to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM, reducing the influence of noise using a Principal Component Analysis (PCA, and using a Relevance Vector Machine (RVM based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.

Binding free energy analysis of protein-protein docking model structures by evERdock.

Science.gov (United States)

Takemura, Kazuhiro; Matubayasi, Nobuyuki; Kitao, Akio

2018-03-14

To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.

Anti-inflammatory effects of Tat-Annexin protein on ovalbumin-induced airway inflammation in a mouse model of asthma

Energy Technology Data Exchange (ETDEWEB)

Lee, Sun Hwa; Kim, Dae Won; Kim, Hye Ri; Woo, Su Jung; Kim, So Mi; Jo, Hyo Sang [Department of Biomedical Science and Research Institute of Bioscience and Biotechnology, Hallym University, Chunchon 200-702 (Korea, Republic of); Jeon, Seong Gyu [Department of Life Science, Pohang University of Science and Technology, Pohang 790-784 (Korea, Republic of); Cho, Sung-Woo [Department of Biochemistry and Molecular Biology, University of Ulsan, College of Medicine, Seoul 138-736 (Korea, Republic of); Park, Jong Hoon [Department of Biological Science, Sookmyung Women' s University, Seoul 140-742 (Korea, Republic of); Won, Moo Ho [Department of Neurobiology, School of Medicine, Kangwon National University, Chuncheon 200-701 (Korea, Republic of); Park, Jinseu [Department of Biomedical Science and Research Institute of Bioscience and Biotechnology, Hallym University, Chunchon 200-702 (Korea, Republic of); Eum, Won Sik, E-mail: wseum@hallym.ac.kr [Department of Biomedical Science and Research Institute of Bioscience and Biotechnology, Hallym University, Chunchon 200-702 (Korea, Republic of); Choi, Soo Young, E-mail: sychoi@hallym.ac.kr [Department of Biomedical Science and Research Institute of Bioscience and Biotechnology, Hallym University, Chunchon 200-702 (Korea, Republic of)

2012-01-20

Highlights: Black-Right-Pointing-Pointer We construct a cell permeable Tat-ANX1 fusion protein. Black-Right-Pointing-Pointer We examined the protective effects of Tat-ANX1 protein on OVA-induced asthma in animal models. Black-Right-Pointing-Pointer Transduced Tat-ANX1 protein protects from the OVA-induced production of cytokines and eosinophils in BAL fluid. Black-Right-Pointing-Pointer Tat-ANX1 protein markedly reduced OVA-induced MAPK in lung tissues. Black-Right-Pointing-Pointer Tat-ANX1 protein could be useful as a therapeutic agent for lung disorders including asthma. -- Abstract: Chronic airway inflammation is a key feature of bronchial asthma. Annexin-1 (ANX1) is an anti-inflammatory protein that is an important modulator and plays a key role in inflammation. Although the precise action of ANX1 remains unclear, it has emerged as a potential drug target for inflammatory diseases such as asthma. To examine the protective effects of ANX1 protein on ovalbumin (OVA)-induced asthma in animal models, we used a cell-permeable Tat-ANX1 protein. Mice sensitized and challenged with OVA antigen had an increased amount of cytokines and eosinophils in their bronchoalveolar lavage (BAL) fluid. However, administration of Tat-ANX1 protein before OVA challenge significantly decreased the levels of cytokines (interleukin (IL)-4, IL-5, and IL-13) and BAL fluid in lung tissues. Furthermore, OVA significantly increased the activation of mitogen-activated protein kinase (MAPK) in lung tissues, whereas Tat-ANX1 protein markedly reduced phosphorylation of MAPKs such as extracellular signal-regulated protein kinase, p38, and stress-activated protein kinase/c-Jun N-terminal kinase. These results suggest that transduced Tat-ANX1 protein may be a potential protein therapeutic agent for the treatment of lung disorders including asthma.

Aspirin reduces lipopolysaccharide-induced pulmonary inflammation in human models of ARDS.

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Hamid, U; Krasnodembskaya, A; Fitzgerald, M; Shyamsundar, M; Kissenpfennig, A; Scott, C; Lefrancais, E; Looney, M R; Verghis, R; Scott, J; Simpson, A J; McNamee, J; McAuley, D F; O'Kane, C M

2017-11-01

Platelets play an active role in the pathogenesis of acute respiratory distress syndrome (ARDS). Animal and observational studies have shown aspirin's antiplatelet and immunomodulatory effects may be beneficial in ARDS. To test the hypothesis that aspirin reduces inflammation in clinically relevant human models that recapitulate pathophysiological mechanisms implicated in the development of ARDS. Healthy volunteers were randomised to receive placebo or aspirin 75  or 1200 mg (1:1:1) for seven days prior to lipopolysaccharide (LPS) inhalation, in a double-blind, placebo-controlled, allocation-concealed study. Bronchoalveolar lavage (BAL) was performed 6 hours after inhaling 50 µg of LPS. The primary outcome measure was BAL IL-8. Secondary outcome measures included markers of alveolar inflammation (BAL neutrophils, cytokines, neutrophil proteases), alveolar epithelial cell injury, systemic inflammation (neutrophils and plasma C-reactive protein (CRP)) and platelet activation (thromboxane B2, TXB2). Human lungs, perfused and ventilated ex vivo (EVLP) were randomised to placebo or 24 mg aspirin and injured with LPS. BAL was carried out 4 hours later. Inflammation was assessed by BAL differential cell counts and histological changes. In the healthy volunteer (n=33) model, data for the aspirin groups were combined. Aspirin did not reduce BAL IL-8. However, aspirin reduced pulmonary neutrophilia and tissue damaging neutrophil proteases (Matrix Metalloproteinase (MMP)-8/-9), reduced BAL concentrations of tumour necrosis factor α and reduced systemic and pulmonary TXB2. There was no difference between high-dose and low-dose aspirin. In the EVLP model, aspirin reduced BAL neutrophilia and alveolar injury as measured by histological damage. These are the first prospective human data indicating that aspirin inhibits pulmonary neutrophilic inflammation, at both low and high doses. Further clinical studies are indicated to assess the role of aspirin in the

Subcellular localization of proteins in the anaerobic sulfate reducer Desulfovibrio vulgaris via SNAP-tag labeling and photoconversion

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Gorur, A.; Leung, C. M.; Jorgens, D.; Tauscher, A.; Remis, J. P.; Ball, D. A.; Chhabra, S.; Fok, V.; Geller, J. T.; Singer, M.; Hazen, T. C.; Juba, T.; Elias, D.; Wall, J.; Biggin, M.; Downing, K. H.; Auer, M.

2010-06-01

Systems Biology studies the temporal and spatial 3D distribution of macromolecular complexes with the aim that such knowledge will allow more accurate modeling of biological function and will allow mathematical prediction of cellular behavior. However, in order to accomplish accurate modeling precise knowledge of spatial 3D organization and distribution inside cells is necessary. And while a number of macromolecular complexes may be identified by its 3D structure and molecular characteristics alone, the overwhelming number of proteins will need to be localized using a reporter tag. GFP and its derivatives (XFPs) have been traditionally employed for subcelllar localization using photoconversion approaches, but this approach cannot be taken for obligate anaerobic bacteria, where the intolerance towards oxygen prevents XFP approaches. As part of the GTL-funded PCAP project (now ENIGMA) genetic tools have been developed for the anaerobe sulfate reducer Desulfovibrio vulgaris that allow the high-throughput generation of tagged-protein mutant strains, with a focus on the commercially available SNAP-tag cell system (New England Biolabs, Ipswich, MA), which is based on a modified O6-alkylguanine-DNA alkyltransferase (AGT) tag, that has a dead-end reaction with a modified O6-benzylguanine (BG) derivative and has been shown to function under anaerobic conditions. After initial challenges with respect to variability, robustness and specificity of the labeling signal we have optimized the labeling. Over the last year, as a result of the optimized labeling protocol, we now obtain robust labeling of 20 out of 31 SNAP strains. Labeling for 13 strains were confirmed at least five times. We have also successfully performed photoconversion on 5 of these 13 strains, with distinct labeling patterns for different strains. For example, DsrC robustly localizes to the periplasmic portion of the inner membrane, where as a DNA-binding protein localizes to the center of the cell, where the

Digestibility of gluten proteins is reduced by baking and enhanced by starch digestion.

Science.gov (United States)

Smith, Frances; Pan, Xiaoyan; Bellido, Vincent; Toole, Geraldine A; Gates, Fred K; Wickham, Martin S J; Shewry, Peter R; Bakalis, Serafim; Padfield, Philip; Mills, E N Clare

2015-10-01

Resistance of proteins to gastrointestinal digestion may play a role in determining immune-mediated adverse reactions to foods. However, digestion studies have largely been restricted to purified proteins and the impact of food processing and food matrices on protein digestibility is poorly understood. Digestibility of a total gliadin fraction (TGF), flour (cv Hereward), and bread was assessed using in vitro batch digestion with simulated oral, gastric, and duodenal phases. Protein digestion was monitored by SDS-PAGE and immunoblotting using monoclonal antibodies specific for celiac-toxic sequences (QQSF, QPFP) and starch digestion by measuring undigested starch. Whereas the TGF was rapidly digested during the gastric phase the gluten proteins in bread were virtually undigested and digested rapidly during the duodenal phase only if amylase was included. Duodenal starch digestion was also slower in the absence of duodenal proteases. The baking process reduces the digestibility of wheat gluten proteins, including those containing sequences active in celiac disease. Starch digestion affects the extent of protein digestion, probably because of gluten-starch complex formation during baking. Digestion studies using purified protein fractions alone are therefore not predictive of digestion in complex food matrices. © 2015 The Authors. Molecular Nutrition & Food Research published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance.

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Patel, Kashyap A; Kettunen, Jarno; Laakso, Markku; Stančáková, Alena; Laver, Thomas W; Colclough, Kevin; Johnson, Matthew B; Abramowicz, Marc; Groop, Leif; Miettinen, Päivi J; Shepherd, Maggie H; Flanagan, Sarah E; Ellard, Sian; Inagaki, Nobuya; Hattersley, Andrew T; Tuomi, Tiinamaija; Cnop, Miriam; Weedon, Michael N

2017-10-12

Finding new causes of monogenic diabetes helps understand glycaemic regulation in humans. To find novel genetic causes of maturity-onset diabetes of the young (MODY), we sequenced MODY cases with unknown aetiology and compared variant frequencies to large public databases. From 36 European patients, we identify two probands with novel RFX6 heterozygous nonsense variants. RFX6 protein truncating variants are enriched in the MODY discovery cohort compared to the European control population within ExAC (odds ratio = 131, P = 1 × 10 -4 ). We find similar results in non-Finnish European (n = 348, odds ratio = 43, P = 5 × 10 -5 ) and Finnish (n = 80, odds ratio = 22, P = 1 × 10 -6 ) replication cohorts. RFX6 heterozygotes have reduced penetrance of diabetes compared to common HNF1A and HNF4A-MODY mutations (27, 70 and 55% at 25 years of age, respectively). The hyperglycaemia results from beta-cell dysfunction and is associated with lower fasting and stimulated gastric inhibitory polypeptide (GIP) levels. Our study demonstrates that heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance.Maturity-onset diabetes of the young (MODY) is the most common subtype of familial diabetes. Here, Patel et al. use targeted DNA sequencing of MODY patients and large-scale publically available data to show that RFX6 heterozygous protein truncating variants cause reduced penetrance MODY.

A scalable and accurate method for classifying protein-ligand binding geometries using a MapReduce approach.

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Estrada, T; Zhang, B; Cicotti, P; Armen, R S; Taufer, M

2012-07-01

We present a scalable and accurate method for classifying protein-ligand binding geometries in molecular docking. Our method is a three-step process: the first step encodes the geometry of a three-dimensional (3D) ligand conformation into a single 3D point in the space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our method for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allow screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for docking trials for 23 protein-ligand complexes for HIV protease, 21 protein-ligand complexes for Trypsin, and 12 protein-ligand complexes for P38alpha kinase. We also analyze cross docking trials for 24 ligands, each docking into 24 protein conformations of the HIV protease, and receptor ensemble docking trials for 24 ligands, each docking in a pool of HIV protease receptors. Our method demonstrates significant improvement over energy-only scoring for the accurate identification of native ligand geometries in all these docking assessments. The advantages of our clustering approach make it attractive for complex applications in real-world drug design efforts. We demonstrate that our method is particularly useful for clustering docking results using a minimal ensemble of representative protein conformational states (receptor ensemble docking), which is now a common strategy to address protein flexibility in molecular docking. Copyright © 2012 Elsevier Ltd. All rights reserved.

Model for calculation of electrostatic contribution into protein stability

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Kundrotas, Petras; Karshikoff, Andrey

2003-03-01

Existing models of the denatured state of proteins consider only one possible spatial distribution of protein charges and therefore are applicable to a limited number of cases. In this presentation a more general framework for the modeling of the denatured state is proposed. It is based on the assumption that the titratable groups of an unfolded protein can adopt a quasi-random distribution, restricted by the protein sequence. The model was tested on two proteins, barnase and N-terminal domain of the ribosomal protein L9. The calculated free energy of denaturation, Δ G( pH), reproduces the experimental data essentially better than the commonly used null approximation (NA). It was demonstrated that the seemingly good agreement with experimental data obtained by NA originates from the compensatory effect between the pair-wise electrostatic interactions and the desolvation energy of the individual sites. It was also found that the ionization properties of denatured proteins are influenced by the protein sequence.

Polyphenol-enriched berry extracts naturally modulate reactive proteins in model foods.

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Lila, Mary Ann; Schneider, Maggie; Devlin, Amy; Plundrich, Nathalie; Laster, Scott; Foegeding, E Allen

2017-12-13

Healthy foods like polyphenol-rich berries and high quality edible proteins are in demand in today's functional food marketplace, but it can be difficult to formulate convenient food products with physiologically-relevant amounts of these ingredients and still maintain product quality. In part, this is because proteins can interact with other food ingredients and precipitate destabilizing events, which can disrupt food structure and diminish shelf life. Proteins in foods can also interact with human receptors to provoke adverse consequences such as allergies. When proteins and polyphenols were pre-aggregated into stable colloidal particles prior to use as ingredients, highly palatable food formulations (with reduced astringency of polyphenols) could be prepared, and the overall structural properties of food formulations were significantly improved. All of the nutritive and phytoactive benefits of the proteins and concentrated polyphenols remained highly bioavailable, but the protein molecules in the particle matrix did not self-aggregate into networks or react with other food ingredients. Both the drainage half-life (a marker of structural stability) and the yield stress (resistance to flow) of model foams made with the protein-polyphenol particles were increased in a dose-dependent manner. Of high significance in this complexation process, the reactive allergenic epitopes of certain proteins were effectively blunted by binding with polyphenols, attenuating the allergenicity of the food proteins. Porcine macrophages produced TNF-α proinflammatory cytokine when provoked with whey protein, but, this response was blocked completely when the cells were stimulated with particles that complexed whey protein with cinnamon-derived polyphenols. Cytokine and chemokine production characteristic of allergic reactions were blocked by the polyphenols, allowing for the potential creation of hypoallergenic protein-berry polyphenol enriched foods.

Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

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Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2016-10-06

Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

Discrete persistent-chain model for protein binding on DNA.

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Lam, Pui-Man; Zhen, Yi

2011-04-01

We describe and solve a discrete persistent-chain model of protein binding on DNA, involving an extra σ(i) at a site i of the DNA. This variable takes the value 1 or 0, depending on whether or not the site is occupied by a protein. In addition, if the site is occupied by a protein, there is an extra energy cost ɛ. For a small force, we obtain analytic expressions for the force-extension curve and the fraction of bound protein on the DNA. For higher forces, the model can be solved numerically to obtain force-extension curves and the average fraction of bound proteins as a function of applied force. Our model can be used to analyze experimental force-extension curves of protein binding on DNA, and hence deduce the number of bound proteins in the case of nonspecific binding. ©2011 American Physical Society

Morphine Reduces Myocardial Infarct Size via Heat Shock Protein 90 in Rodents

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Bryce A. Small

2015-01-01

Full Text Available Opioids reduce injury from myocardial ischemia-reperfusion in humans. In experimental models, this mechanism involves GSK3β inhibition. HSP90 regulates mitochondrial protein import, with GSK3β inhibition increasing HSP90 mitochondrial content. Therefore, we determined whether morphine-induced cardioprotection is mediated by HSP90 and if the protective effect is downstream of GSK3β inhibition. Male Sprague-Dawley rats, aged 8–10 weeks, were subjected to an in vivo myocardial ischemia-reperfusion injury protocol involving 30 minutes of ischemia followed by 2 hours of reperfusion. Hemodynamics were continually monitored and myocardial infarct size determined. Rats received morphine (0.3 mg/kg, the GSK3β inhibitor, SB216763 (0.6 mg/kg, or saline, 10 minutes prior to ischemia. Some rats received selective HSP90 inhibitors, radicicol (0.3 mg/kg, or deoxyspergualin (DSG, 0.6 mg/kg alone or 5 minutes prior to morphine or SB216763. Morphine reduced myocardial infarct size when compared to control (42 ± 2% versus 60 ± 1%. This protection was abolished by prior treatment of radicicol or DSG (59 ± 1%, 56 ± 2%. GSK3β inhibition also reduced myocardial infarct size (41 ± 2% with HSP90 inhibition by radicicol or DSG partially inhibiting SB216763-induced infarct size reduction (54 ± 3%, 47 ± 1%, resp.. These data suggest that opioid-induced cardioprotection is mediated by HSP90. Part of this protection afforded by HSP90 is downstream of GSK3β, potentially via the HSP-TOM mitochondrial import pathway.

AMP-activated protein kinase reduces inflammatory responses and cellular senescence in pulmonary emphysema.

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Cheng, Xiao-Yu; Li, Yang-Yang; Huang, Cheng; Li, Jun; Yao, Hong-Wei

2017-04-04

Current drug therapy fails to reduce lung destruction of chronic obstructive pulmonary disease (COPD). AMP-activated protein kinase (AMPK) has emerged as an important integrator of signals that control energy balance and lipid metabolism. However, there are no studies regarding the role of AMPK in reducing inflammatory responses and cellular senescence during the development of emphysema. Therefore, we hypothesize that AMPK reduces inflammatroy responses, senescence, and lung injury. To test this hypothesis, human bronchial epithelial cells (BEAS-2B) and small airway epithelial cells (SAECs) were treated with cigarette smoke extract (CSE) in the presence of a specific AMPK activator (AICAR, 1 mM) and inhibitor (Compound C, 5 μM). Elastase injection was performed to induce mouse emphysema, and these mice were treated with a specific AMPK activator metformin as well as Compound C. AICAR reduced, whereas Compound C increased CSE-induced increase in IL-8 and IL-6 release and expression of genes involved in cellular senescence. Knockdown of AMPKα1/α2 increased expression of pro-senescent genes (e.g., p16, p21, and p66shc) in BEAS-2B cells. Prophylactic administration of an AMPK activator metformin (50 and 250 mg/kg) reduced while Compound C (4 and 20 mg/kg) aggravated elastase-induced airspace enlargement, inflammatory responses and cellular senescence in mice. This is in agreement with therapeutic effect of metformin (50 mg/kg) on airspace enlargement. Furthermore, metformin prophylactically protected against but Compound C further reduced mitochondrial proteins SOD2 and SIRT3 in emphysematous lungs. In conclusion, AMPK reduces abnormal inflammatory responses and cellular senescence, which implicates as a potential therapeutic target for COPD/emphysema.

Protein Folding: Search for Basic Physical Models

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Ivan Y. Torshin

2003-01-01

Full Text Available How a unique three-dimensional structure is rapidly formed from the linear sequence of a polypeptide is one of the important questions in contemporary science. Apart from biological context of in vivo protein folding (which has been studied only for a few proteins, the roles of the fundamental physical forces in the in vitro folding remain largely unstudied. Despite a degree of success in using descriptions based on statistical and/or thermodynamic approaches, few of the current models explicitly include more basic physical forces (such as electrostatics and Van Der Waals forces. Moreover, the present-day models rarely take into account that the protein folding is, essentially, a rapid process that produces a highly specific architecture. This review considers several physical models that may provide more direct links between sequence and tertiary structure in terms of the physical forces. In particular, elaboration of such simple models is likely to produce extremely effective computational techniques with value for modern genomics.

Models of crk adaptor proteins in cancer.

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Bell, Emily S; Park, Morag

2012-05-01

The Crk family of adaptor proteins (CrkI, CrkII, and CrkL), originally discovered as the oncogene fusion product, v-Crk, of the CT10 chicken retrovirus, lacks catalytic activity but engages with multiple signaling pathways through their SH2 and SH3 domains. Crk proteins link upstream tyrosine kinase and integrin-dependent signals to downstream effectors, acting as adaptors in diverse signaling pathways and cellular processes. Crk proteins are now recognized to play a role in the malignancy of many human cancers, stimulating renewed interest in their mechanism of action in cancer progression. The contribution of Crk signaling to malignancy has been predominantly studied in fibroblasts and in hematopoietic models and more recently in epithelial models. A mechanistic understanding of Crk proteins in cancer progression in vivo is still poorly understood in part due to the highly pleiotropic nature of Crk signaling. Recent advances in the structural organization of Crk domains, new roles in kinase regulation, and increased knowledge of the mechanisms and frequency of Crk overexpression in human cancers have provided an incentive for further study in in vivo models. An understanding of the mechanisms through which Crk proteins act as oncogenic drivers could have important implications in therapeutic targeting.

Omega-3 fatty acid docosahexaenoic acid increases SorLA/LR11, a sorting protein with reduced expression in sporadic Alzheimer's disease (AD): relevance to AD prevention.

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Ma, Qiu-Lan; Teter, Bruce; Ubeda, Oliver J; Morihara, Takashi; Dhoot, Dilsher; Nyby, Michael D; Tuck, Michael L; Frautschy, Sally A; Cole, Greg M

2007-12-26

Environmental and genetic factors, notably ApoE4, contribute to the etiology of late-onset Alzheimer's disease (LOAD). Reduced mRNA and protein for an apolipoprotein E (ApoE) receptor family member, SorLA (LR11) has been found in LOAD but not early-onset AD, suggesting that LR11 loss is not secondary to pathology. LR11 is a neuronal sorting protein that reduces amyloid precursor protein (APP) trafficking to secretases that generate beta-amyloid (Abeta). Genetic polymorphisms that reduce LR11 expression are associated with increased AD risk. However these polymorphisms account for only a fraction of cases with LR11 deficits, suggesting involvement of environmental factors. Because lipoprotein receptors are typically lipid-regulated, we postulated that LR11 is regulated by docosahexaenoic acid (DHA), an essential omega-3 fatty acid related to reduced AD risk and reduced Abeta accumulation. In this study, we report that DHA significantly increases LR11 in multiple systems, including primary rat neurons, aged non-Tg mice and an aged DHA-depleted APPsw AD mouse model. DHA also increased LR11 in a human neuronal line. In vivo elevation of LR11 was also observed with dietary fish oil in young rats with insulin resistance, a model for type II diabetes, another AD risk factor. These data argue that DHA induction of LR11 does not require DHA-depleting diets and is not age dependent. Because reduced LR11 is known to increase Abeta production and may be a significant genetic cause of LOAD, our results indicate that DHA increases in SorLA/LR11 levels may play an important role in preventing LOAD.

Model predictive control based on reduced order models applied to belt conveyor system.

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Chen, Wei; Li, Xin

2016-11-01

In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Modelling Protein Dynamics on the Microsecond Time Scale

DEFF Research Database (Denmark)

Siuda, Iwona Anna

Recent years have shown an increase in coarse-grained (CG) molecular dynamics simulations, providing structural and dynamic details of large proteins and enabling studies of self-assembly of biological materials. It is not easy to acquire such data experimentally, and access is also still limited...... in atomistic simulations. During her PhD studies, Iwona Siuda used MARTINI CG models to study the dynamics of different globular and membrane proteins. In several cases, the MARTINI model was sufficient to study conformational changes of small, purely alpha-helical proteins. However, in studies of larger......ELNEDIN was therefore proposed as part of the work. Iwona Siuda’s results from the CG simulations had biological implications that provide insights into possible mechanisms of the periplasmic leucine-binding protein, the sarco(endo)plasmic reticulum calcium pump, and several proteins from the saposin-like proteins...

Small molecule proteostasis regulators that reprogram the ER to reduce extracellular protein aggregation

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Plate, Lars; Cooley, Christina B; Chen, John J; Paxman, Ryan J; Gallagher, Ciara M; Madoux, Franck; Genereux, Joseph C; Dobbs, Wesley; Garza, Dan; Spicer, Timothy P; Scampavia, Louis; Brown, Steven J; Rosen, Hugh; Powers, Evan T; Walter, Peter; Hodder, Peter; Wiseman, R Luke; Kelly, Jeffery W

2016-01-01

Imbalances in endoplasmic reticulum (ER) proteostasis are associated with etiologically-diverse degenerative diseases linked to excessive extracellular protein misfolding and aggregation. Reprogramming of the ER proteostasis environment through genetic activation of the Unfolded Protein Response (UPR)-associated transcription factor ATF6 attenuates secretion and extracellular aggregation of amyloidogenic proteins. Here, we employed a screening approach that included complementary arm-specific UPR reporters and medium-throughput transcriptional profiling to identify non-toxic small molecules that phenocopy the ATF6-mediated reprogramming of the ER proteostasis environment. The ER reprogramming afforded by our molecules requires activation of endogenous ATF6 and occurs independent of global ER stress. Furthermore, our molecules phenocopy the ability of genetic ATF6 activation to selectively reduce secretion and extracellular aggregation of amyloidogenic proteins. These results show that small molecule-dependent ER reprogramming, achieved through preferential activation of the ATF6 transcriptional program, is a promising strategy to ameliorate imbalances in ER function associated with degenerative protein aggregation diseases. DOI: http://dx.doi.org/10.7554/eLife.15550.001 PMID:27435961

Identifying biological concepts from a protein-related corpus with a probabilistic topic model

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Lu Xinghua

2006-02-01

Full Text Available Abstract Background Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE© titles and abstracts by applying a probabilistic topic model. Results The latent Dirichlet allocation (LDA model was applied to the corpus. Based on the Bayesian model selection, 300 major topics were extracted from the corpus. The majority of identified topics/concepts was found to be semantically coherent and most represented biological objects or concepts. The identified topics/concepts were further mapped to the controlled vocabulary of the Gene Ontology (GO terms based on mutual information. Conclusion The major and recurring biological concepts within a collection of MEDLINE documents can be extracted by the LDA model. The identified topics/concepts provide parsimonious and semantically-enriched representation of the texts in a semantic space with reduced dimensionality and can be used to index text.

Non-uniform tube representation of proteins

DEFF Research Database (Denmark)

Hansen, Mikael Sonne

Treating the full protein structure is often neither computationally nor physically possible. Instead one is forced to consider various reduced models capturing the properties of interest. Previous work have used tubular neighborhoods of the C-alpha backbone. However, assigning a unique radius...... might not correctly capture volume exclusion - of crucial importance when trying to understand a proteins $3$d-structure. We propose a new reduced model treating the protein as a non-uniform tube with a radius reflecting the positions of atoms. The tube representation is well suited considering X......-ray crystallographic resolution ~ 3Å while a varying radius accounts for the different sizes of side chains. Such a non-uniform tube better capture the protein geometry and has numerous applications in structural/computational biology from the classification of protein structures to sequence-structure prediction....

Immunogenicity of therapeutic proteins: the use of animal models.

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Brinks, Vera; Jiskoot, Wim; Schellekens, Huub

2011-10-01

Immunogenicity of therapeutic proteins lowers patient well-being and drastically increases therapeutic costs. Preventing immunogenicity is an important issue to consider when developing novel therapeutic proteins and applying them in the clinic. Animal models are increasingly used to study immunogenicity of therapeutic proteins. They are employed as predictive tools to assess different aspects of immunogenicity during drug development and have become vital in studying the mechanisms underlying immunogenicity of therapeutic proteins. However, the use of animal models needs critical evaluation. Because of species differences, predictive value of such models is limited, and mechanistic studies can be restricted. This review addresses the suitability of animal models for immunogenicity prediction and summarizes the insights in immunogenicity that they have given so far.

Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

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Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

2015-11-01

Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

Fluphenazine reduces proteotoxicity in C. elegans and mammalian models of alpha-1-antitrypsin deficiency.

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Jie Li

Full Text Available The classical form of α1-antitrypsin deficiency (ATD is associated with hepatic fibrosis and hepatocellular carcinoma. It is caused by the proteotoxic effect of a mutant secretory protein that aberrantly accumulates in the endoplasmic reticulum of liver cells. Recently we developed a model of this deficiency in C. elegans and adapted it for high-content drug screening using an automated, image-based array scanning. Screening of the Library of Pharmacologically Active Compounds identified fluphenazine (Flu among several other compounds as a drug which reduced intracellular accumulation of mutant α1-antitrypsin Z (ATZ. Because it is representative of the phenothiazine drug class that appears to have autophagy enhancer properties in addition to mood stabilizing activity, and can be relatively easily re-purposed, we further investigated its effects on mutant ATZ. The results indicate that Flu reverses the phenotypic effects of ATZ accumulation in the C. elegans model of ATD at doses which increase the number of autophagosomes in vivo. Furthermore, in nanomolar concentrations, Flu enhances the rate of intracellular degradation of ATZ and reduces the cellular ATZ load in mammalian cell line models. In the PiZ mouse model Flu reduces the accumulation of ATZ in the liver and mediates a decrease in hepatic fibrosis. These results show that Flu can reduce the proteotoxicity of ATZ accumulation in vivo and, because it has been used safely in humans, this drug can be moved rapidly into trials for liver disease due to ATD. The results also provide further validation for drug discovery using C. elegans models that can be adapted to high-content drug screening platforms and used together with mammalian cell line and animal models.

Hybrid reduced order modeling for assembly calculations

Energy Technology Data Exchange (ETDEWEB)

Bang, Youngsuk, E-mail: ysbang00@fnctech.com [FNC Technology, Co. Ltd., Yongin-si (Korea, Republic of); Abdel-Khalik, Hany S., E-mail: abdelkhalik@purdue.edu [Purdue University, West Lafayette, IN (United States); Jessee, Matthew A., E-mail: jesseema@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States); Mertyurek, Ugur, E-mail: mertyurek@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States)

2015-12-15

Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.

Hybrid reduced order modeling for assembly calculations

International Nuclear Information System (INIS)

Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; Mertyurek, Ugur

2015-01-01

Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.

Predicting nucleic acid binding interfaces from structural models of proteins.

Science.gov (United States)

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2012-02-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

Discovery of rare protein-coding genes in model methylotroph Methylobacterium extorquens AM1.

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Kumar, Dhirendra; Mondal, Anupam Kumar; Yadav, Amit Kumar; Dash, Debasis

2014-12-01

Proteogenomics involves the use of MS to refine annotation of protein-coding genes and discover genes in a genome. We carried out comprehensive proteogenomic analysis of Methylobacterium extorquens AM1 (ME-AM1) from publicly available proteomics data with a motive to improve annotation for methylotrophs; organisms capable of surviving in reduced carbon compounds such as methanol. Besides identifying 2482(50%) proteins, 29 new genes were discovered and 66 annotated gene models were revised in ME-AM1 genome. One such novel gene is identified with 75 peptides, lacks homolog in other methylobacteria but has glycosyl transferase and lipopolysaccharide biosynthesis protein domains, indicating its potential role in outer membrane synthesis. Many novel genes are present only in ME-AM1 among methylobacteria. Distant homologs of these genes in unrelated taxonomic classes and low GC-content of few genes suggest lateral gene transfer as a potential mode of their origin. Annotations of methylotrophy related genes were also improved by the discovery of a short gene in methylotrophy gene island and redefining a gene important for pyrroquinoline quinone synthesis, essential for methylotrophy. The combined use of proteogenomics and rigorous bioinformatics analysis greatly enhanced the annotation of protein-coding genes in model methylotroph ME-AM1 genome. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Enzymatic Hydrolysis Does Not Reduce the Biological Reactivity of Soybean Proteins for All Allergic Subjects.

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Panda, Rakhi; Tetteh, Afua O; Pramod, Siddanakoppalu N; Goodman, Richard E

2015-11-04

Many soybean protein products are processed by enzymatic hydrolysis to attain desirable functional food properties or in some cases to reduce allergenicity. However, few studies have investigated the effects of enzymatic hydrolysis on the allergenicity of soybean products. In this study the allergenicity of soybean protein isolates (SPI) hydrolyzed by Alcalase, trypsin, chymotrypsin, bromelain, or papain was evaluated by IgE immunoblots using eight soybean-allergic patient sera. The biological relevance of IgE binding was evaluated by a functional assay using a humanized rat basophilic leukemia (hRBL) cell line and serum from one subject. Results indicated that hydrolysis of SPI by the enzymes did not reduce the allergenicity, and hydrolysis by chymotrypsin or bromelain has the potential to increase the allergenicity of SPI. Two-dimensional (2D) immunoblot and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of the chymotrypsin-hydrolyzed samples indicated fragments of β-conglycinin protein are responsible for the apparent higher allergenic potential of digested SPI.

Maternal protein-energy malnutrition during early pregnancy in sheep impacts the fetal ornithine cycle to reduce fetal kidney microvascular development.

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Dunford, Louise J; Sinclair, Kevin D; Kwong, Wing Y; Sturrock, Craig; Clifford, Bethan L; Giles, Tom C; Gardner, David S

2014-11-01

This paper identifies a common nutritional pathway relating maternal through to fetal protein-energy malnutrition (PEM) and compromised fetal kidney development. Thirty-one twin-bearing sheep were fed either a control (n=15) or low-protein diet (n=16, 17 vs. 8.7 g crude protein/MJ metabolizable energy) from d 0 to 65 gestation (term, ∼ 145 d). Effects on the maternal and fetal nutritional environment were characterized by sampling blood and amniotic fluid. Kidney development was characterized by histology, immunohistochemistry, vascular corrosion casts, and molecular biology. PEM had little measureable effect on maternal and fetal macronutrient balance (glucose, total protein, total amino acids, and lactate were unaffected) or on fetal growth. PEM decreased maternal and fetal urea concentration, which blunted fetal ornithine availability and affected fetal hepatic polyamine production. For the first time in a large animal model, we associated these nutritional effects with reduced micro- but not macrovascular development in the fetal kidney. Maternal PEM specifically impacts the fetal ornithine cycle, affecting cellular polyamine metabolism and microvascular development of the fetal kidney, effects that likely underpin programming of kidney development and function by a maternal low protein diet. © FASEB.

Fast loop modeling for protein structures

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Zhang, Jiong; Nguyen, Son; Shang, Yi; Xu, Dong; Kosztin, Ioan

2015-03-01

X-ray crystallography is the main method for determining 3D protein structures. In many cases, however, flexible loop regions of proteins cannot be resolved by this approach. This leads to incomplete structures in the protein data bank, preventing further computational study and analysis of these proteins. For instance, all-atom molecular dynamics (MD) simulation studies of structure-function relationship require complete protein structures. To address this shortcoming, we have developed and implemented an efficient computational method for building missing protein loops. The method is database driven and uses deep learning and multi-dimensional scaling algorithms. We have implemented the method as a simple stand-alone program, which can also be used as a plugin in existing molecular modeling software, e.g., VMD. The quality and stability of the generated structures are assessed and tested via energy scoring functions and by equilibrium MD simulations. The proposed method can also be used in template-based protein structure prediction. Work supported by the National Institutes of Health [R01 GM100701]. Computer time was provided by the University of Missouri Bioinformatics Consortium.

High-Pressure-High-Temperature Processing Reduces Maillard Reaction and Viscosity in Whey Protein-Sugar Solutions.

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Avila Ruiz, Geraldine; Xi, Bingyan; Minor, Marcel; Sala, Guido; van Boekel, Martinus; Fogliano, Vincenzo; Stieger, Markus

2016-09-28

The aim of the study was to determine the influence of pressure in high-pressure-high-temperature (HPHT) processing on Maillard reactions and protein aggregation of whey protein-sugar solutions. Solutions of whey protein isolate containing either glucose or trehalose at pH 6, 7, and 9 were treated by HPHT processing or conventional high-temperature (HT) treatments. Browning was reduced, and early and advanced Maillard reactions were retarded under HPHT processing at all pH values compared to HT treatment. HPHT induced a larger pH drop than HT treatments, especially at pH 9, which was not associated with Maillard reactions. After HPHT processing at pH 7, protein aggregation and viscosity of whey protein isolate-glucose/trehalose solutions remained unchanged. It was concluded that HPHT processing can potentially improve the quality of protein-sugar-containing foods, for which browning and high viscosities are undesired, such as high-protein beverages.

Moderate, but not vigorous, intensity exercise training reduces C-reactive protein.

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Fedewa, Michael V; Hathaway, Elizabeth D; Higgins, Simon; Forehand, Ronald L; Schmidt, Michael D; Evans, Ellen M

2018-06-01

Sprint interval cycle training is a contemporary popular mode of training but its relative efficacy, under conditions of matched energy expenditure, to reduce risk factors for cardiometabolic disease is incompletely characterised, especially in young women. The purpose of this investigation was to determine the relative efficacy of six weeks of moderate-intensity cycling (MOD-C) and vigorous sprint-interval cycling (VIG-SIC) on lipid profile, insulin (INS) and insulin resistance using the homeostatic model assessment (HOMA-IR) and C-reactive protein (CRP) in inactive, overweight/obese (OW/OB) young women. Participants (BMI ≥25 kg/m 2 , waist circumference ≥88 cm) were randomly assigned to MOD-C (20-30 min at 60-70% of heart rate reserve(HRR)) or VIG-SIC (5-7 repeated bouts 30-second maximal effort sprints, followed by four minutes of active recovery) supervised training three days/week for six weeks, with each group matched on energy expenditure. Adiposity (%Fat) was measured using dual x-ray absorptiometry. Forty-four participants (20.4 ± 1.6 years, 65.9% Caucasian, 29.8 ± 4.1 kg/m 2 ) were included in the analysis. The improvement in CRP observed in the MOD-C group was larger than the VIG-C group (p = .034). Overall, high-density lipoprotein (HDL-C) and low-density lipoprotein (LDL-C) levels improved following training (p  .05). These results indicate MOD-C training may be more effective in reducing CRP than VIG-SIC.

Modeling protein structures: construction and their applications.

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Ring, C S; Cohen, F E

1993-06-01

Although no general solution to the protein folding problem exists, the three-dimensional structures of proteins are being successfully predicted when experimentally derived constraints are used in conjunction with heuristic methods. In the case of interleukin-4, mutagenesis data and CD spectroscopy were instrumental in the accurate assignment of secondary structure. In addition, the tertiary structure was highly constrained by six cysteines separated by many residues that formed three disulfide bridges. Although the correct structure was a member of a short list of plausible structures, the "best" structure was the topological enantiomer of the experimentally determined conformation. For many proteases, other experimentally derived structures can be used as templates to identify the secondary structure elements. In a procedure called modeling by homology, the structure of a known protein is used as a scaffold to predict the structure of another related protein. This method has been used to model a serine and a cysteine protease that are important in the schistosome and malarial life cycles, respectively. The model structures were then used to identify putative small molecule enzyme inhibitors computationally. Experiments confirm that some of these nonpeptidic compounds are active at concentrations of less than 10 microM.

A computational model of the LGI1 protein suggests a common binding site for ADAM proteins.

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Emanuela Leonardi

Full Text Available Mutations of human leucine-rich glioma inactivated (LGI1 gene encoding the epitempin protein cause autosomal dominant temporal lateral epilepsy (ADTLE, a rare familial partial epileptic syndrome. The LGI1 gene seems to have a role on the transmission of neuronal messages but the exact molecular mechanism remains unclear. In contrast to other genes involved in epileptic disorders, epitempin shows no homology with known ion channel genes but contains two domains, composed of repeated structural units, known to mediate protein-protein interactions.A three dimensional in silico model of the two epitempin domains was built to predict the structure-function relationship and propose a functional model integrating previous experimental findings. Conserved and electrostatic charged regions of the model surface suggest a possible arrangement between the two domains and identifies a possible ADAM protein binding site in the β-propeller domain and another protein binding site in the leucine-rich repeat domain. The functional model indicates that epitempin could mediate the interaction between proteins localized to different synaptic sides in a static way, by forming a dimer, or in a dynamic way, by binding proteins at different times.The model was also used to predict effects of known disease-causing missense mutations. Most of the variants are predicted to alter protein folding while several other map to functional surface regions. In agreement with experimental evidence, this suggests that non-secreted LGI1 mutants could be retained within the cell by quality control mechanisms or by altering interactions required for the secretion process.

Reduced Wall Acetylation Proteins Play Vital and Distinct Roles in Cell Wall O-Acetylation in Arabidopsis

DEFF Research Database (Denmark)

Manabe, Yuzuki; Verhertbruggen, Yves; Gille, Sascha

2013-01-01

The Reduced Wall Acetylation (RWA) proteins are involved in cell wall acetylation in plants. Previously, we described a single mutant, rwa2, which has about 20% lower level of O-acetylation in leaf cell walls and no obvious growth or developmental phenotype. In this study, we generated double....... The quadruple rwa mutant can be completely complemented with the RWA2 protein expressed under 35S promoter, indicating the functional redundancy of the RWA proteins. Nevertheless, the degree of acetylation of xylan, (gluco) mannan, and xyloglucan as well as overall cell wall acetylation is affected differently...... in different combinations of triple mutants, suggesting their diversity in substrate preference. The overall degree of wall acetylation in the rwa quadruple mutant was reduced by 63% compared with the wild type, and histochemical analysis of the rwa quadruple mutant stem indicates defects in cell...

Nonperturbative treatment of reduced model with fermions

International Nuclear Information System (INIS)

Gutierrez, W.R.

1983-01-01

A nonperturbative method is presented to show that the reduced model produces the correct leading large-N contribution to the fermion Green's functions. A new form of the reduced model is introduced, which avoids the quenching procedure. Also the equation for the meson bound states is discussed. The method is illustrated in the case of two-dimensional QCD

Whey Protein Reduces Early Life Weight Gain in Mice Fed a High-Fat Diet

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Tranberg, Britt; Hellgren, Lars I.; Lykkesfeldt, Jens; Sejrsen, Kristen; Jeamet, Aymeric; Rune, Ida; Ellekilde, Merete; Nielsen, Dennis S.; Hansen, Axel Kornerup

2013-01-01

An increasing number of studies indicate that dairy products, including whey protein, alleviate several disorders of the metabolic syndrome. Here, we investigated the effects of whey protein isolate (whey) in mice fed a high-fat diet hypothesising that the metabolic effects of whey would be associated with changes in the gut microbiota composition. Five-week-old male C57BL/6 mice were fed a high-fat diet ad libitum for 14 weeks with the protein source being either whey or casein. Faeces were collected at week 0, 7, and 13 and the fecal microbiota was analysed by denaturing gradient gel electrophoresis analyses of PCR-derived 16S rRNA gene (V3-region) amplicons. At the end of the study, plasma samples were collected and assayed for glucose, insulin and lipids. Whey significantly reduced body weight gain during the first four weeks of the study compared with casein (Pwhey group relative to casein (34.0±1.0 g vs. 40.2±1.3 g, Pwhey group (Pwhey compared to casein (Pwhey and casein. In conclusion, whey initially reduced weight gain in young C57BL/6 mice fed a high-fat diet compared to casein. Although the effect on weight gain ceased, whey alleviated glucose intolerance, improved insulin sensitivity and reduced plasma cholesterol. These findings could not be explained by changes in food intake or gut microbiota composition. Further studies are needed to clarify the mechanisms behind the metabolic effects of whey. PMID:23940754

Folding 19 proteins to their native state and stability of large proteins from a coarse-grained model.

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Kapoor, Abhijeet; Travesset, Alex

2014-03-01

We develop an intermediate resolution model, where the backbone is modeled with atomic resolution but the side chain with a single bead, by extending our previous model (Proteins (2013) DOI: 10.1002/prot.24269) to properly include proline, preproline residues and backbone rigidity. Starting from random configurations, the model properly folds 19 proteins (including a mutant 2A3D sequence) into native states containing β sheet, α helix, and mixed α/β. As a further test, the stability of H-RAS (a 169 residue protein, critical in many signaling pathways) is investigated: The protein is stable, with excellent agreement with experimental B-factors. Despite that proteins containing only α helices fold to their native state at lower backbone rigidity, and other limitations, which we discuss thoroughly, the model provides a reliable description of the dynamics as compared with all atom simulations, but does not constrain secondary structures as it is typically the case in more coarse-grained models. Further implications are described. Copyright © 2013 Wiley Periodicals, Inc.

Cooking Chicken Breast Reduces Dialyzable Iron Resulting from Digestion of Muscle Proteins

Directory of Open Access Journals (Sweden)

Aditya S. Gokhale

2014-01-01

Full Text Available The purpose of this research was to study the effect of cooking chicken breast on the production of dialyzable iron (an in vitro indicator of bioavailable iron from added ferric iron. Chicken breast muscle was cooked by boiling, baking, sautéing, or deep-frying. Cooked samples were mixed with ferric iron and either extracted with acid or digested with pepsin and pancreatin. Total and ferrous dialyzable iron was measured after extraction or digestion and compared to raw chicken samples. For uncooked samples, dialyzable iron was significantly enhanced after both extraction and digestion. All cooking methods led to markedly reduced levels of dialyzable iron both by extraction and digestion. In most cooked, digested samples dialyzable iron was no greater than the iron-only (no sample control. Cooked samples showed lower levels of histidine and sulfhydryls but protein digestibility was not reduced, except for the sautéed sample. The results showed that, after cooking, little if any dialyzable iron results from digestion of muscle proteins. Our research indicates that, in cooked chicken, residual acid-extractable components are the most important source of dialyzable iron.

Cooking Chicken Breast Reduces Dialyzable Iron Resulting from Digestion of Muscle Proteins.

Science.gov (United States)

Gokhale, Aditya S; Mahoney, Raymond R

2014-01-01

The purpose of this research was to study the effect of cooking chicken breast on the production of dialyzable iron (an in vitro indicator of bioavailable iron) from added ferric iron. Chicken breast muscle was cooked by boiling, baking, sautéing, or deep-frying. Cooked samples were mixed with ferric iron and either extracted with acid or digested with pepsin and pancreatin. Total and ferrous dialyzable iron was measured after extraction or digestion and compared to raw chicken samples. For uncooked samples, dialyzable iron was significantly enhanced after both extraction and digestion. All cooking methods led to markedly reduced levels of dialyzable iron both by extraction and digestion. In most cooked, digested samples dialyzable iron was no greater than the iron-only (no sample) control. Cooked samples showed lower levels of histidine and sulfhydryls but protein digestibility was not reduced, except for the sautéed sample. The results showed that, after cooking, little if any dialyzable iron results from digestion of muscle proteins. Our research indicates that, in cooked chicken, residual acid-extractable components are the most important source of dialyzable iron.

Transcriptomic changes underlie altered egg protein production and reduced fecundity in an estuarine model fish exposed to bifenthrin.

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Brander, Susanne M; Jeffries, Ken M; Cole, Bryan J; DeCourten, Bethany M; White, J Wilson; Hasenbein, Simone; Fangue, Nann A; Connon, Richard E

2016-05-01

Pyrethroid pesticides are a class of insecticides found to have endocrine disrupting properties in vertebrates such as fishes and in human cell lines. Endocrine disrupting chemicals (EDCs) are environmental contaminants that mimic or alter the process of hormone signaling. In particular, EDCs that alter estrogen and androgen signaling pathways are of major concern for fishes because these EDCs may alter reproductive physiology, behavior, and ultimately sex ratio. Bifenthrin, a pyrethroid with escalating usage, is confirmed to disrupt estrogen signaling in several species of fish, including Menidia beryllina (inland silverside), an Atherinid recently established as a euryhaline model. Our main objective was to broadly assess the molecular and physiological responses of M. beryllina to the ng/L concentrations of bifenthrin typically found in the environment, with a focus on endocrine-related effects, and to discern links between different tiers of the biological hierarchy. As such, we evaluated the response of juvenile Menidia to bifenthrin using a Menidia-specific microarray, quantitative real-time polymerase chain reaction (qPCR) on specific endocrine-related genes of interest, and a Menidia-specific ELISA to the egg-coat protein choriogenin, to evaluate a multitude of molecular-level responses that would inform mechanisms of toxicity and any underlying causes of change at higher biological levels of organization. The sublethal nominal concentrations tested (0.5, 5 and 50ng/L) were chosen to represent the range of concentrations observed in the environment and to provide coverage of a variety of potential responses. We then employed a 21-day reproductive assay to evaluate reproductive responses to bifenthrin (at 0.5ng/L) in a separate group of adult M. beryllina. The microarray analysis indicated that bifenthrin influences a diverse suite of molecular pathways, from baseline metabolic processes to carcinogenesis. A more targeted examination of gene expression via q

Trade-off between positive and negative design of protein stability: from lattice models to real proteins.

Directory of Open Access Journals (Sweden)

Orly Noivirt-Brik

2009-12-01

Full Text Available Two different strategies for stabilizing proteins are (i positive design in which the native state is stabilized and (ii negative design in which competing non-native conformations are destabilized. Here, the circumstances under which one strategy might be favored over the other are explored in the case of lattice models of proteins and then generalized and discussed with regard to real proteins. The balance between positive and negative design of proteins is found to be determined by their average "contact-frequency", a property that corresponds to the fraction of states in the conformational ensemble of the sequence in which a pair of residues is in contact. Lattice model proteins with a high average contact-frequency are found to use negative design more than model proteins with a low average contact-frequency. A mathematical derivation of this result indicates that it is general and likely to hold also for real proteins. Comparison of the results of correlated mutation analysis for real proteins with typical contact-frequencies to those of proteins likely to have high contact-frequencies (such as disordered proteins and proteins that are dependent on chaperonins for their folding indicates that the latter tend to have stronger interactions between residues that are not in contact in their native conformation. Hence, our work indicates that negative design is employed when insufficient stabilization is achieved via positive design owing to high contact-frequencies.

Roles of beta-turns in protein folding: from peptide models to protein engineering.

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Marcelino, Anna Marie C; Gierasch, Lila M

2008-05-01

Reverse turns are a major class of protein secondary structure; they represent sites of chain reversal and thus sites where the globular character of a protein is created. It has been speculated for many years that turns may nucleate the formation of structure in protein folding, as their propensity to occur will favor the approximation of their flanking regions and their general tendency to be hydrophilic will favor their disposition at the solvent-accessible surface. Reverse turns are local features, and it is therefore not surprising that their structural properties have been extensively studied using peptide models. In this article, we review research on peptide models of turns to test the hypothesis that the propensities of turns to form in short peptides will relate to the roles of corresponding sequences in protein folding. Turns with significant stability as isolated entities should actively promote the folding of a protein, and by contrast, turn sequences that merely allow the chain to adopt conformations required for chain reversal are predicted to be passive in the folding mechanism. We discuss results of protein engineering studies of the roles of turn residues in folding mechanisms. Factors that correlate with the importance of turns in folding indeed include their intrinsic stability, as well as their topological context and their participation in hydrophobic networks within the protein's structure.

An Integrated Framework Advancing Membrane Protein Modeling and Design.

Directory of Open Access Journals (Sweden)

Rebecca F Alford

2015-09-01

Full Text Available Membrane proteins are critical functional molecules in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to determine their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1 prediction of free energy changes upon mutation; (2 high-resolution structural refinement; (3 protein-protein docking; and (4 assembly of symmetric protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.

Flexibility damps macromolecular crowding effects on protein folding dynamics: Application to the murine prion protein (121-231)

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Bergasa-Caceres, Fernando; Rabitz, Herschel A.

2014-01-01

A model of protein folding kinetics is applied to study the combined effects of protein flexibility and macromolecular crowding on protein folding rate and stability. It is found that the increase in stability and folding rate promoted by macromolecular crowding is damped for proteins with highly flexible native structures. The model is applied to the folding dynamics of the murine prion protein (121-231). It is found that the high flexibility of the native isoform of the murine prion protein (121-231) reduces the effects of macromolecular crowding on its folding dynamics. The relevance of these findings for the pathogenic mechanism are discussed.

Protein (multi-)location prediction: utilizing interdependencies via a generative model.

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Simha, Ramanuja; Briesemeister, Sebastian; Kohlbacher, Oliver; Shatkay, Hagit

2015-06-15

Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein's function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. We introduce a probabilistic generative model for protein localization, and develop a system based on it-which we call MDLoc-that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. © The Author 2015. Published by Oxford University Press.

Reduced Fragment Diversity for Alpha and Alpha-Beta Protein Structure Prediction using Rosetta.

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Abbass, Jad; Nebel, Jean-Christophe

2017-01-01

Protein structure prediction is considered a main challenge in computational biology. The biannual international competition, Critical Assessment of protein Structure Prediction (CASP), has shown in its eleventh experiment that free modelling target predictions are still beyond reliable accuracy, therefore, much effort should be made to improve ab initio methods. Arguably, Rosetta is considered as the most competitive method when it comes to targets with no homologues. Relying on fragments of length 9 and 3 from known structures, Rosetta creates putative structures by assembling candidate fragments. Generally, the structure with the lowest energy score, also known as first model, is chosen to be the "predicted one". A thorough study has been conducted on the role and diversity of 3-mers involved in Rosetta's model "refinement" phase. Usage of the standard number of 3-mers - i.e. 200 - has been shown to degrade alpha and alpha-beta protein conformations initially achieved by assembling 9-mers. Therefore, a new prediction pipeline is proposed for Rosetta where the "refinement" phase is customised according to a target's structural class prediction. Over 8% improvement in terms of first model structure accuracy is reported for alpha and alpha-beta classes when decreasing the number of 3- mers. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Mechanical Modeling and Computer Simulation of Protein Folding

Science.gov (United States)

Prigozhin, Maxim B.; Scott, Gregory E.; Denos, Sharlene

2014-01-01

In this activity, science education and modern technology are bridged to teach students at the high school and undergraduate levels about protein folding and to strengthen their model building skills. Students are guided from a textbook picture of a protein as a rigid crystal structure to a more realistic view: proteins are highly dynamic…

Blunted hypothalamic ghrelin signaling reduces diet intake in rats fed a low-protein diet in late pregnancy

Science.gov (United States)

Diet intake in pregnant rats fed a low-protein (LP) diet was significantly reduced during late pregnancy despite elevated plasma levels of ghrelin. In this study, we hypothesized that ghrelin signaling in the hypothalamus is blunted under a low-protein diet condition and therefore, it does not stimu...

Generalized Reduced Order Model Generation, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — M4 Engineering proposes to develop a generalized reduced order model generation method. This method will allow for creation of reduced order aeroservoelastic state...

Molecular modeling of protein materials: case study of elastin

International Nuclear Information System (INIS)

Tarakanova, Anna; Buehler, Markus J

2013-01-01

Molecular modeling of protein materials is a quickly growing area of research that has produced numerous contributions in fields ranging from structural engineering to medicine and biology. We review here the history and methods commonly employed in molecular modeling of protein materials, emphasizing the advantages for using modeling as a complement to experimental work. We then consider a case study of the protein elastin, a critically important ‘mechanical protein’ to exemplify the approach in an area where molecular modeling has made a significant impact. We outline the progression of computational modeling studies that have considerably enhanced our understanding of this important protein which endows elasticity and recoil to the tissues it is found in, including the skin, lungs, arteries and the heart. A vast collection of literature has been directed at studying the structure and function of this protein for over half a century, the first molecular dynamics study of elastin being reported in the 1980s. We review the pivotal computational works that have considerably enhanced our fundamental understanding of elastin's atomistic structure and its extraordinary qualities—focusing on two in particular: elastin's superb elasticity and the inverse temperature transition—the remarkable ability of elastin to take on a more structured conformation at higher temperatures, suggesting its effectiveness as a biomolecular switch. Our hope is to showcase these methods as both complementary and enriching to experimental approaches that have thus far dominated the study of most protein-based materials. (topical review)

Skeletal muscle protein accretion rates and hindlimb growth are reduced in late gestation intrauterine growth-restricted fetal sheep.

Science.gov (United States)

Rozance, Paul J; Zastoupil, Laura; Wesolowski, Stephanie R; Goldstrohm, David A; Strahan, Brittany; Cree-Green, Melanie; Sheffield-Moore, Melinda; Meschia, Giacomo; Hay, William W; Wilkening, Randall B; Brown, Laura D

2018-01-01

Adults who were affected by intrauterine growth restriction (IUGR) suffer from reductions in muscle mass, which may contribute to insulin resistance and the development of diabetes. We demonstrate slower hindlimb linear growth and muscle protein synthesis rates that match the reduced hindlimb blood flow and oxygen consumption rates in IUGR fetal sheep. These adaptations resulted in hindlimb blood flow rates in IUGR that were similar to control fetuses on a weight-specific basis. Net hindlimb glucose uptake and lactate output rates were similar between groups, whereas amino acid uptake was significantly lower in IUGR fetal sheep. Among all fetuses, blood O 2 saturation and plasma glucose, insulin and insulin-like growth factor-1 were positively associated and norepinephrine was negatively associated with hindlimb weight. These results further our understanding of the metabolic and hormonal adaptations to reduced oxygen and nutrient supply with placental insufficiency that develop to slow hindlimb growth and muscle protein accretion. Reduced skeletal muscle mass in the fetus with intrauterine growth restriction (IUGR) persists into adulthood and may contribute to increased metabolic disease risk. To determine how placental insufficiency with reduced oxygen and nutrient supply to the fetus affects hindlimb blood flow, substrate uptake and protein accretion rates in skeletal muscle, late gestation control (CON) (n = 8) and IUGR (n = 13) fetal sheep were catheterized with aortic and femoral catheters and a flow transducer around the external iliac artery. Muscle protein kinetic rates were measured using isotopic tracers. Hindlimb weight, linear growth rate, muscle protein accretion rate and fractional synthetic rate were lower in IUGR compared to CON (P fetal norepinephrine and reduced IGF-1 and insulin. © 2017 The Authors. The Journal of Physiology © 2017 The Physiological Society.

Inhibition of Cartilage Acidic Protein 1 Reduces Ultraviolet B Irradiation Induced-Apoptosis through P38 Mitogen-Activated Protein Kinase and Jun Amino-Terminal Kinase Pathways

Directory of Open Access Journals (Sweden)

Yinghong Ji

2016-11-01

Full Text Available Background/Aims: Ultraviolet B (UVB irradiation can easily induce apoptosis in human lens epithelial cells (HLECs and further lead to various eye diseases including cataract. Here for the first time, we investigated the role of cartilage acidic protein 1 (CRTAC1 gene in UVB irradiation induced-apoptosis in HLECs. Methods: Three groups of HLECs were employed including model group, empty vector group, and CRTAC1 interference group. Results: After UVB irradiation, the percentage of primary apoptotic cells was obviously fewer in CRTAC1 interference group. Meanwhile, inhibition of CRTAC1 also reduced both reactive oxygen species (ROS production and intracellular Ca2+ concentration, but the level of mitochondrial membrane potential (Δψm was increased in HLECs. Further studies indicated that superoxide dismutase (SOD activity and total antioxidative (T-AOC level were significantly increased in CRTAC1-inhibited cells, while the levels of malondialdehyde (MDA and lactate dehydrogenase (LDH were significantly decreased. ELISA analysis of CRTAC1-inhibited cells showed that the concentrations of tumor necrosis factor-α (TNF-α and interleukin-6 (IL-6 were significantly decreased, but the concentration of interleukin-10 (IL-10 was significantly increased. Western blot analyses of eight apoptosis-associated proteins including Bax, Bcl-2, p38, phospho-p38 (p-p38, Jun amino-terminal kinases (JNK1/2, phospho-JNK1/2 (p-JNK1/2, calcium-sensing receptor (CasR, and Ca2+/calmodulin-dependent protein kinase II (CaMKII indicated that the inhibition of CRTAC1 alleviated oxidative stress and inflammation response, inactivated calcium-signaling pathway, p38 and JNK1/2 signal pathways, and eventually reduced UVB irradiation induced-apoptosis in HLECs. Conclusion: These results provided new insights into the mechanism of cataract development, and demonstrated that CRTAC1 could be a potentially novel target for cataract treatment.

Inhibition of Cartilage Acidic Protein 1 Reduces Ultraviolet B Irradiation Induced-Apoptosis through P38 Mitogen-Activated Protein Kinase and Jun Amino-Terminal Kinase Pathways.

Science.gov (United States)

Ji, Yinghong; Rong, Xianfang; Li, Dan; Cai, Lei; Rao, Jun; Lu, Yi

2016-01-01

Ultraviolet B (UVB) irradiation can easily induce apoptosis in human lens epithelial cells (HLECs) and further lead to various eye diseases including cataract. Here for the first time, we investigated the role of cartilage acidic protein 1 (CRTAC1) gene in UVB irradiation induced-apoptosis in HLECs. Three groups of HLECs were employed including model group, empty vector group, and CRTAC1 interference group. After UVB irradiation, the percentage of primary apoptotic cells was obviously fewer in CRTAC1 interference group. Meanwhile, inhibition of CRTAC1 also reduced both reactive oxygen species (ROS) production and intracellular Ca2+ concentration, but the level of mitochondrial membrane potential (Δψm) was increased in HLECs. Further studies indicated that superoxide dismutase (SOD) activity and total antioxidative (T-AOC) level were significantly increased in CRTAC1-inhibited cells, while the levels of malondialdehyde (MDA) and lactate dehydrogenase (LDH) were significantly decreased. ELISA analysis of CRTAC1-inhibited cells showed that the concentrations of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) were significantly decreased, but the concentration of interleukin-10 (IL-10) was significantly increased. Western blot analyses of eight apoptosis-associated proteins including Bax, Bcl-2, p38, phospho-p38 (p-p38), Jun amino-terminal kinases (JNK1/2), phospho-JNK1/2 (p-JNK1/2), calcium-sensing receptor (CasR), and Ca2+/calmodulin-dependent protein kinase II (CaMKII) indicated that the inhibition of CRTAC1 alleviated oxidative stress and inflammation response, inactivated calcium-signaling pathway, p38 and JNK1/2 signal pathways, and eventually reduced UVB irradiation induced-apoptosis in HLECs. These results provided new insights into the mechanism of cataract development, and demonstrated that CRTAC1 could be a potentially novel target for cataract treatment. © 2016 The Author(s) Published by S. Karger AG, Basel.

Protein (multi-)location prediction: utilizing interdependencies via a generative model

Science.gov (United States)

Shatkay, Hagit

2015-01-01

Motivation: Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein’s function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. Results: We introduce a probabilistic generative model for protein localization, and develop a system based on it—which we call MDLoc—that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. Availability and implementation: MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. Contact: shatkay@udel.edu. PMID:26072505

In silico modelling and validation of differential expressed proteins in lung cancer

Directory of Open Access Journals (Sweden)

Bhagavathi S

2012-05-01

Full Text Available Objective: The present study aims predict the three dimensional structure of three major proteins responsible for causing Lung cancer. Methods: These are the differentially expressed proteins in lung cancer dataset. Initially, the structural template for these proteins is identified from structural database using homology search and perform homology modelling approach to predict its native 3D structure. Three-dimensional model obtained was validated using Ramachandran plot analysis to find the reliability of the model. Results: Four proteins were differentially expressed and were significant proteins in causing lung cancer. Among the four proteins, Matrixmetallo proteinase (P39900 had a known 3D structure and hence was not considered for modelling. The remaining proteins Polo like kinase I Q58A51, Trophinin B1AKF1, Thrombomodulin P07204 were modelled and validated. Conclusions: The three dimensional structure of proteins provides insights about the functional aspect and regulatory aspect of the protein. Thus, this study will be a breakthrough for further lung cancer related studies.

Benzylglucosinolate Derived Isothiocyanate from Tropaeolum majus Reduces Gluconeogenic Gene and Protein Expression in Human Cells.

Directory of Open Access Journals (Sweden)

Valentina Guzmán-Pérez

Full Text Available Nasturtium (Tropaeolum majus L. contains high concentrations of benzylglcosinolate. We found that a hydrolysis product of benzyl glucosinolate-the benzyl isothiocyanate (BITC-modulates the intracellular localization of the transcription factor Forkhead box O 1 (FOXO1. FoxO transcription factors can antagonize insulin effects and trigger a variety of cellular processes involved in tumor suppression, longevity, development and metabolism. The current study evaluated the ability of BITC-extracted as intact glucosinolate from nasturtium and hydrolyzed with myrosinase-to modulate i the insulin-signaling pathway, ii the intracellular localization of FOXO1 and, iii the expression of proteins involved in gluconeogenesis, antioxidant response and detoxification. Stably transfected human osteosarcoma cells (U-2 OS with constitutive expression of FOXO1 protein labeled with GFP (green fluorescent protein were used to evaluate the effect of BITC on FOXO1. Human hepatoma HepG2 cell cultures were selected to evaluate the effect on gluconeogenic, antioxidant and detoxification genes and protein expression. BITC reduced the phosphorylation of protein kinase B (AKT/PKB and FOXO1; promoted FOXO1 translocation from cytoplasm into the nucleus antagonizing the insulin effect; was able to down-regulate the gene and protein expression of gluconeogenic enzymes; and induced the gene expression of antioxidant and detoxification enzymes. Knockdown analyses with specific siRNAs showed that the expression of gluconeogenic genes was dependent on nuclear factor (erythroid derived-like2 (NRF2 and independent of FOXO1, AKT and NAD-dependent deacetylase sirtuin-1 (SIRT1. The current study provides evidence that BITC might have a role in type 2 diabetes T2D by reducing hepatic glucose production and increasing antioxidant resistance.

Protein single-model quality assessment by feature-based probability density functions.

Science.gov (United States)

Cao, Renzhi; Cheng, Jianlin

2016-04-04

Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

Quality assessment of protein model-structures based on structural and functional similarities.

Science.gov (United States)

Konopka, Bogumil M; Nebel, Jean-Christophe; Kotulska, Malgorzata

2012-09-21

Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. GOBA--Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and

Simulation studies of protein-induced bilayer deformations, and lipid-induced protein tilting, on a mesoscopic model for lipid bilayers with embedded proteins

DEFF Research Database (Denmark)

Venturoli, M.; Smit, B.; Sperotto, Maria Maddalena

2005-01-01

membranes. Here we present a mesoscopic model for lipid bilayers with embedded proteins, which we have studied with the help of the dissipative particle dynamics simulation technique. Because hydrophobic matching is believed to be one of the main physical mechanisms regulating lipid-protein interactions......-induced protein tilt, with the hydrophobic mismatch ( positive and negative) between the protein hydrophobic length and the pure lipid bilayer hydrophobic thickness. The protein-induced bilayer perturbation was quantified in terms of a coherence length, xi(P), of the lipid bilayer hydrophobic thickness pro. le...... for positive values of mismatch; a dependence on the protein size appears as well. In the case of large model proteins experiencing extreme mismatch conditions, in the region next to the so-called lipid annulus, there appears an undershooting ( or overshooting) region where the bilayer hydrophobic thickness...

SynechoNET: integrated protein-protein interaction database of a model cyanobacterium Synechocystis sp. PCC 6803

OpenAIRE

Kim, Woo-Yeon; Kang, Sungsoo; Kim, Byoung-Chul; Oh, Jeehyun; Cho, Seongwoong; Bhak, Jong; Choi, Jong-Soon

2008-01-01

Background Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date. Description We report a database and website SynechoNET that provides predicted protein-protein interactions. SynechoNET shows cyanobacterial domain-domain interactio...

Minocycline Reduces Spontaneous Hemorrhage in Mouse Models of Cerebral Amyloid Angiopathy

Science.gov (United States)

Liao, Fan; Xiao, Qingli; Kraft, Andrew; Gonzales, Ernie; Perez, Ron; Greenberg, Steven M.; Holtzman, David; Lee, Jin-Moo

2015-01-01

Background and Purpose Cerebral Amyloid Angiopathy (CAA) is a common cause of recurrent intracerebral hemorrhage (ICH) in the elderly. Previous studies have shown that CAA induces inflammation and expression of matrix metalloproteinase-2 and -9 (gelatinases) in amyloid-laden vessels. Here, we inhibited both using minocycline in CAA mouse models to determine if spontaneous ICH could be reduced. Methods Tg2576 (n=16) and 5×FAD/ApoE4 knock-in mice (n=16), aged to 17 and 12 months, respectively, were treated with minocycline (50 mg/kg, i.p.) or saline every other day for two months. Brains were extracted and stained with X-34 (to quantify amyloid), Perl’s blue (to quantify hemorrhage), and immunostained to examined Aβ load, gliosis (GFAP, Iba-1), and vascular markers of blood-brain-barrier integrity (ZO-1 and collagen IV). Brain extracts were used to quantify mRNA for a variety of inflammatory genes. Results Minocycline treatment significantly reduced hemorrhage frequency in the brains of Tg2576 and 5×FAD/ApoE4 mice relative to the saline-treated mice, without affecting CAA load. Gliosis (GFAP and Iba-1 immunostaining), gelatinase activity, and expression of a variety of inflammatory genes (MMP-9, Nox4, CD45, S-100b, Iba-1) were also significantly reduced. Higher levels of microvascular tight junction and basal lamina proteins were found in the brains of minocycline-treated Tg2576 mice relative to saline-treated controls. Conclusions Minocycline reduced gliosis, inflammatory gene expression, gelatinase activity, and spontaneous hemorrhage in two different mouse models of CAA, supporting the importance of MMP-related and inflammatory pathways in ICH pathogenesis. As an FDA-approved drug, minocycline might be considered for clinical trials to test efficacy in preventing CAA-related ICH. PMID:25944329

Using modified soy protein to enhance foaming of egg white protein.

Science.gov (United States)

Wang, Guang; Troendle, Molly; Reitmeier, Cheryll A; Wang, Tong

2012-08-15

It is well known that the foaming properties of egg white protein are significantly reduced when a small amount of yolk is mixed in the white. To improve foaming properties of yolk-contaminated egg white protein, soy protein isolate (SPI) and egg proteins were modified to make basic proteins, and effects of these modified proteins on egg white foaming were evaluated in a model and an angel cake system. SPI and egg yolk proteins were modified to have an isoelectric point of 10, and sonication was used to increase protein dispersibility after the ethyl esterification reaction. However, only the addition of sonicated and modified SPI (SMSPI) showed improvement of foaming in the 5% egg protein model system with 0.4% yolk addition. SMSPI was then used in making angel food cake to examine whether the cake performance reduction due to yolk contamination of the white would be restored by such alkaline protein. Cake performance was improved when cream of tartar was used together with SMSPI. Basic soy protein can be made and used to improve egg white foaming properties and cake performance. Copyright © 2012 Society of Chemical Industry.

Macrocyclic peptides decrease c-Myc protein levels and reduce prostate cancer cell growth.

Science.gov (United States)

Mukhopadhyay, Archana; Hanold, Laura E; Thayele Purayil, Hamsa; Gisemba, Solomon A; Senadheera, Sanjeewa N; Aldrich, Jane V

2017-08-03

The oncoprotein c-Myc is often overexpressed in cancer cells, and the stability of this protein has major significance in deciding the fate of a cell. Thus, targeting c-Myc levels is an attractive approach for developing therapeutic agents for cancer treatment. In this study, we report the anti-cancer activity of the macrocyclic peptides [D-Trp]CJ-15,208 (cyclo[Phe-D-Pro-Phe-D-Trp]) and the natural product CJ-15,208 (cyclo[Phe-D-Pro-Phe-Trp]). [D-Trp]CJ-15,208 reduced c-Myc protein levels in prostate cancer cells and decreased cell proliferation with IC 50 values ranging from 2.0 to 16 µM in multiple PC cell lines. [D-Trp]CJ-15,208 induced early and late apoptosis in PC-3 cells following 48 hours treatment, and growth arrest in the G2 cell cycle phase following both 24 and 48 hours treatment. Down regulation of c-Myc in PC-3 cells resulted in loss of sensitivity to [D-Trp]CJ-15,208 treatment, while overexpression of c-Myc in HEK-293 cells imparted sensitivity of these cells to [D-Trp]CJ-15,208 treatment. This macrocyclic tetrapeptide also regulated PP2A by reducing the levels of its phosphorylated form which regulates the stability of cellular c-Myc protein. Thus [D-Trp]CJ-15,208 represents a new lead compound for the potential development of an effective treatment of prostate cancer.

Hydration dynamics near a model protein surface

International Nuclear Information System (INIS)

Russo, Daniela; Hura, Greg; Head-Gordon, Teresa

2003-01-01

The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces

The characterization of a full-thickness excision open foot wound model in n5-streptozotocin (STZ)-induced type 2 diabetic rats that mimics diabetic foot ulcer in terms of reduced blood circulation, higher C-reactive protein, elevated inflammation, and reduced cell proliferation.

Science.gov (United States)

Yu, Caroline Oi-Ling; Leung, Kwok-Sui; Fung, Kwok-Pui; Lam, Francis Fu-Yuen; Ng, Ethel Sau-Kuen; Lau, Kit-Man; Chow, Simon Kwoon-Ho; Cheung, Wing-Hoi

2017-08-05

Delayed foot wound healing is a major complication attributed to hyperglycemia in type 2 diabetes mellitus (DM) patients, and these wounds may develop into foot ulcers. There are at least two types of DM wound models used in rodents to study delayed wound healing. However, clinically relevant animal models are not common. Most models use type 1 DM rodents or wounds created on the back rather than on the foot. An open full-thickness excision wound on the footpad of type 2 DM rats is more clinically relevant, but such a model has not yet been characterized systematically. The objective of this study was to investigate and characterize how DM affected a full-thickness excision open foot wound in n5-streptozotocin (n5-STZ)-induced type 2 DM rats. We hypothesized that elevated inflammation, reduced blood circulation, and cell proliferation due to hyperglycemia could delay the wound healing of DM rats. The wounds of DM rats were compared with those of non-DM rats (Ctrl) at Days 1 and 8 post wounding. The wound healing process of the DM rats was significantly delayed compared with that of the Ctrl rats. The DM rats also had higher C-reactive protein (CRP) and lower blood circulation and proliferating cell nuclear antigen (PCNA) in DM wounds. This confirmed that elevated inflammation and reduced blood flow and cell proliferation delayed foot wound healing in the n5-STZ rats. Hence, this open foot wound animal model provides a good approach to study the process of delayed wound healing.

The characterization of a full-thickness excision open foot wound model in n5-streptozotocin (STZ)-induced type 2 diabetic rats that mimics diabetic foot ulcer in terms of reduced blood circulation, higher C-reactive protein, elevated inflammation, and reduced cell proliferation

Science.gov (United States)

Yu, Caroline Oi-Ling; Leung, Kwok-Sui; Fung, Kwok-Pui; Lam, Francis Fu-Yuen; Ng, Ethel Sau-Kuen; Lau, Kit-Man; Chow, Simon Kwoon-Ho; Cheung, Wing-Hoi

2017-01-01

Delayed foot wound healing is a major complication attributed to hyperglycemia in type 2 diabetes mellitus (DM) patients, and these wounds may develop into foot ulcers. There are at least two types of DM wound models used in rodents to study delayed wound healing. However, clinically relevant animal models are not common. Most models use type 1 DM rodents or wounds created on the back rather than on the foot. An open full-thickness excision wound on the footpad of type 2 DM rats is more clinically relevant, but such a model has not yet been characterized systematically. The objective of this study was to investigate and characterize how DM affected a full-thickness excision open foot wound in n5-streptozotocin (n5-STZ)-induced type 2 DM rats. We hypothesized that elevated inflammation, reduced blood circulation, and cell proliferation due to hyperglycemia could delay the wound healing of DM rats. The wounds of DM rats were compared with those of non-DM rats (Ctrl) at Days 1 and 8 post wounding. The wound healing process of the DM rats was significantly delayed compared with that of the Ctrl rats. The DM rats also had higher C-reactive protein (CRP) and lower blood circulation and proliferating cell nuclear antigen (PCNA) in DM wounds. This confirmed that elevated inflammation and reduced blood flow and cell proliferation delayed foot wound healing in the n5-STZ rats. Hence, this open foot wound animal model provides a good approach to study the process of delayed wound healing. PMID:28413186

Protein source in a high-protein diet modulates reductions in insulin resistance and hepatic steatosis in fa/fa Zucker rats.

Science.gov (United States)

Wojcik, Jennifer L; Devassy, Jessay G; Wu, Yinghong; Zahradka, Peter; Taylor, Carla G; Aukema, Harold M

2016-01-01

High-protein diets are being promoted to reduce insulin resistance and hepatic steatosis in metabolic syndrome. Therefore, the effect of protein source in high-protein diets on reducing insulin resistance and hepatic steatosis was examined. Fa/fa Zucker rats were provided normal-protein (15% of energy) casein, high-protein (35% of energy) casein, high-protein soy, or high-protein mixed diets with animal and plant proteins. The high-protein mixed diet reduced area under the curve for insulin during glucose tolerance testing, fasting serum insulin and free fatty acid concentrations, homeostatic model assessment index, insulin to glucose ratio, and pancreatic islet cell area. The high-protein mixed and the high-protein soy diets reduced hepatic lipid concentrations, liver to body weight ratio, and hepatic steatosis rating. These improvements were observed despite no differences in body weight, feed intake, or adiposity among high-protein diet groups. The high-protein casein diet had minimal benefits. A high-protein mixed diet was the most effective for modulating reductions in insulin resistance and hepatic steatosis independent of weight loss, indicating that the source of protein within a high-protein diet is critical for the management of these metabolic syndrome parameters. © 2015 The Obesity Society.

Whey protein reduces early life weight gain in mice fed a high-fat diet.

Directory of Open Access Journals (Sweden)

Britt Tranberg

Full Text Available An increasing number of studies indicate that dairy products, including whey protein, alleviate several disorders of the metabolic syndrome. Here, we investigated the effects of whey protein isolate (whey in mice fed a high-fat diet hypothesising that the metabolic effects of whey would be associated with changes in the gut microbiota composition. Five-week-old male C57BL/6 mice were fed a high-fat diet ad libitum for 14 weeks with the protein source being either whey or casein. Faeces were collected at week 0, 7, and 13 and the fecal microbiota was analysed by denaturing gradient gel electrophoresis analyses of PCR-derived 16S rRNA gene (V3-region amplicons. At the end of the study, plasma samples were collected and assayed for glucose, insulin and lipids. Whey significantly reduced body weight gain during the first four weeks of the study compared with casein (P<0.001-0.05. Hereafter weight gain was similar resulting in a 15% lower final body weight in the whey group relative to casein (34.0±1.0 g vs. 40.2±1.3 g, P<0.001. Food intake was unaffected by protein source throughout the study period. Fasting insulin was lower in the whey group (P<0.01 and glucose clearance was improved after an oral glucose challenge (P<0.05. Plasma cholesterol was lowered by whey compared to casein (P<0.001. The composition of the fecal microbiota differed between high- and low-fat groups at 13 weeks (P<0.05 whereas no difference was seen between whey and casein. In conclusion, whey initially reduced weight gain in young C57BL/6 mice fed a high-fat diet compared to casein. Although the effect on weight gain ceased, whey alleviated glucose intolerance, improved insulin sensitivity and reduced plasma cholesterol. These findings could not be explained by changes in food intake or gut microbiota composition. Further studies are needed to clarify the mechanisms behind the metabolic effects of whey.

potential for quality protein maize for reducing protein- energy

African Journals Online (AJOL)

ACSS

social systems hampering QPM promotion and adoption and to identify ... affects growth and development. Protein- energy ... to purchase QPM seed leading to PEU reduction. Education ..... decision support framework “targetCSA”. Agricultural ...

Stabilizing salt-bridge enhances protein thermostability by reducing the heat capacity change of unfolding.

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Chi-Ho Chan

Full Text Available Most thermophilic proteins tend to have more salt bridges, and achieve higher thermostability by up-shifting and broadening their protein stability curves. While the stabilizing effect of salt-bridge has been extensively studied, experimental data on how salt-bridge influences protein stability curves are scarce. Here, we used double mutant cycles to determine the temperature-dependency of the pair-wise interaction energy and the contribution of salt-bridges to ΔC(p in a thermophilic ribosomal protein L30e. Our results showed that the pair-wise interaction energies for the salt-bridges E6/R92 and E62/K46 were stabilizing and insensitive to temperature changes from 298 to 348 K. On the other hand, the pair-wise interaction energies between the control long-range ion-pair of E90/R92 were negligible. The ΔC(p of all single and double mutants were determined by Gibbs-Helmholtz and Kirchhoff analyses. We showed that the two stabilizing salt-bridges contributed to a reduction of ΔC(p by 0.8-1.0 kJ mol⁻¹ K⁻¹. Taken together, our results suggest that the extra salt-bridges found in thermophilic proteins enhance the thermostability of proteins by reducing ΔC(p, leading to the up-shifting and broadening of the protein stability curves.

Statistical-mechanical lattice models for protein-DNA binding in chromatin

International Nuclear Information System (INIS)

Teif, Vladimir B; Rippe, Karsten

2010-01-01

Statistical-mechanical lattice models for protein-DNA binding are well established as a method to describe complex ligand binding equilibria measured in vitro with purified DNA and protein components. Recently, a new field of applications has opened up for this approach since it has become possible to experimentally quantify genome-wide protein occupancies in relation to the DNA sequence. In particular, the organization of the eukaryotic genome by histone proteins into a nucleoprotein complex termed chromatin has been recognized as a key parameter that controls the access of transcription factors to the DNA sequence. New approaches have to be developed to derive statistical-mechanical lattice descriptions of chromatin-associated protein-DNA interactions. Here, we present the theoretical framework for lattice models of histone-DNA interactions in chromatin and investigate the (competitive) DNA binding of other chromosomal proteins and transcription factors. The results have a number of applications for quantitative models for the regulation of gene expression.

Reduced modeling of signal transduction – a modular approach

Directory of Open Access Journals (Sweden)

Ederer Michael

2007-09-01

Full Text Available Abstract Background Combinatorial complexity is a challenging problem in detailed and mechanistic mathematical modeling of signal transduction. This subject has been discussed intensively and a lot of progress has been made within the last few years. A software tool (BioNetGen was developed which allows an automatic rule-based set-up of mechanistic model equations. In many cases these models can be reduced by an exact domain-oriented lumping technique. However, the resulting models can still consist of a very large number of differential equations. Results We introduce a new reduction technique, which allows building modularized and highly reduced models. Compared to existing approaches further reduction of signal transduction networks is possible. The method also provides a new modularization criterion, which allows to dissect the model into smaller modules that are called layers and can be modeled independently. Hallmarks of the approach are conservation relations within each layer and connection of layers by signal flows instead of mass flows. The reduced model can be formulated directly without previous generation of detailed model equations. It can be understood and interpreted intuitively, as model variables are macroscopic quantities that are converted by rates following simple kinetics. The proposed technique is applicable without using complex mathematical tools and even without detailed knowledge of the mathematical background. However, we provide a detailed mathematical analysis to show performance and limitations of the method. For physiologically relevant parameter domains the transient as well as the stationary errors caused by the reduction are negligible. Conclusion The new layer based reduced modeling method allows building modularized and strongly reduced models of signal transduction networks. Reduced model equations can be directly formulated and are intuitively interpretable. Additionally, the method provides very good

Homology modeling of dissimilatory APS reductases (AprBA of sulfur-oxidizing and sulfate-reducing prokaryotes.

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Birte Meyer

Full Text Available BACKGROUND: The dissimilatory adenosine-5'-phosphosulfate (APS reductase (cofactors flavin adenine dinucleotide, FAD, and two [4Fe-4S] centers catalyzes the transformation of APS to sulfite and AMP in sulfate-reducing prokaryotes (SRP; in sulfur-oxidizing bacteria (SOB it has been suggested to operate in the reverse direction. Recently, the three-dimensional structure of the Archaeoglobus fulgidus enzyme has been determined in different catalytically relevant states providing insights into its reaction cycle. METHODOLOGY/PRINCIPAL FINDINGS: Full-length AprBA sequences from 20 phylogenetically distinct SRP and SOB species were used for homology modeling. In general, the average accuracy of the calculated models was sufficiently good to allow a structural and functional comparison between the beta- and alpha-subunit structures (78.8-99.3% and 89.5-96.8% of the AprB and AprA main chain atoms, respectively, had root mean square deviations below 1 A with respect to the template structures. Besides their overall conformity, the SRP- and SOB-derived models revealed the existence of individual adaptations at the electron-transferring AprB protein surface presumably resulting from docking to different electron donor/acceptor proteins. These structural alterations correlated with the protein phylogeny (three major phylogenetic lineages: (1 SRP including LGT-affected Archaeoglobi and SOB of Apr lineage II, (2 crenarchaeal SRP Caldivirga and Pyrobaculum, and (3 SOB of the distinct Apr lineage I and the presence of potential APS reductase-interacting redox complexes. The almost identical protein matrices surrounding both [4Fe-4S] clusters, the FAD cofactor, the active site channel and center within the AprB/A models of SRP and SOB point to a highly similar catalytic process of APS reduction/sulfite oxidation independent of the metabolism type the APS reductase is involved in and the species it has been originated from. CONCLUSIONS: Based on the comparative

Leucine supplementation stimulates protein synthesis and reduces degradation signal activation in muscle of newborn pigs during acute endotoxemia

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Sepsis disrupts skeletal muscle proteostasis and mitigates the anabolic response to leucine (Leu) in muscle of mature animals. We have shown that Leu stimulates muscle protein synthesis (PS) in healthy neonatal piglets. To determine if supplemental Leu can stimulate PS and reduce protein degradation...

Reduced Order Modeling of Combustion Instability in a Gas Turbine Model Combustor

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Arnold-Medabalimi, Nicholas; Huang, Cheng; Duraisamy, Karthik

2017-11-01

Hydrocarbon fuel based propulsion systems are expected to remain relevant in aerospace vehicles for the foreseeable future. Design of these devices is complicated by combustion instabilities. The capability to model and predict these effects at reduced computational cost is a requirement for both design and control of these devices. This work focuses on computational studies on a dual swirl model gas turbine combustor in the context of reduced order model development. Full fidelity simulations are performed utilizing URANS and Hybrid RANS-LES with finite rate chemistry. Following this, data decomposition techniques are used to extract a reduced basis representation of the unsteady flow field. These bases are first used to identify sensor locations to guide experimental interrogations and controller feedback. Following this, initial results on developing a control-oriented reduced order model (ROM) will be presented. The capability of the ROM will be further assessed based on different operating conditions and geometric configurations.

Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale

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Kuzu, Guray; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2013-01-01

Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than ‘blind’ docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested ‘difficult’ cases in a docking-benchmark dataset, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ~26% to 66%, and 57% of the interactions were successfully predicted in an ‘unbiased’ scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein-protein interaction predictions on an interactome-scale. We constructed the structural network of ERK interacting proteins as a case study. PMID:23590674

Stochastic lattice model of synaptic membrane protein domains.

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Li, Yiwei; Kahraman, Osman; Haselwandter, Christoph A

2017-05-01

Neurotransmitter receptor molecules, concentrated in synaptic membrane domains along with scaffolds and other kinds of proteins, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here in detail a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Our work sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.

SET overexpression in HEK293 cells regulates mitochondrial uncoupling proteins levels within a mitochondrial fission/reduced autophagic flux scenario

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Almeida, Luciana O.; Goto, Renata N. [Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Neto, Marinaldo P.C. [Department of Physics and Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Sousa, Lucas O. [Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Curti, Carlos [Department of Physics and Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Leopoldino, Andréia M., E-mail: andreiaml@usp.br [Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil)

2015-03-06

We hypothesized that SET, a protein accumulated in some cancer types and Alzheimer disease, is involved in cell death through mitochondrial mechanisms. We addressed the mRNA and protein levels of the mitochondrial uncoupling proteins UCP1, UCP2 and UCP3 (S and L isoforms) by quantitative real-time PCR and immunofluorescence as well as other mitochondrial involvements, in HEK293 cells overexpressing the SET protein (HEK293/SET), either in the presence or absence of oxidative stress induced by the pro-oxidant t-butyl hydroperoxide (t-BHP). SET overexpression in HEK293 cells decreased UCP1 and increased UCP2 and UCP3 (S/L) mRNA and protein levels, whilst also preventing lipid peroxidation and decreasing the content of cellular ATP. SET overexpression also (i) decreased the area of mitochondria and increased the number of organelles and lysosomes, (ii) increased mitochondrial fission, as demonstrated by increased FIS1 mRNA and FIS-1 protein levels, an apparent accumulation of DRP-1 protein, and an increase in the VDAC protein level, and (iii) reduced autophagic flux, as demonstrated by a decrease in LC3B lipidation (LC3B-II) in the presence of chloroquine. Therefore, SET overexpression in HEK293 cells promotes mitochondrial fission and reduces autophagic flux in apparent association with up-regulation of UCP2 and UCP3; this implies a potential involvement in cellular processes that are deregulated such as in Alzheimer's disease and cancer. - Highlights: • SET, UCPs and autophagy prevention are correlated. • SET action has mitochondrial involvement. • UCP2/3 may reduce ROS and prevent autophagy. • SET protects cell from ROS via UCP2/3.

CONFOLD2: improved contact-driven ab initio protein structure modeling.

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Adhikari, Badri; Cheng, Jianlin

2018-01-25

Contact-guided protein structure prediction methods are becoming more and more successful because of the latest advances in residue-residue contact prediction. To support contact-driven structure prediction, effective tools that can quickly build tertiary structural models of good quality from predicted contacts need to be developed. We develop an improved contact-driven protein modelling method, CONFOLD2, and study how it may be effectively used for ab initio protein structure prediction with predicted contacts as input. It builds models using various subsets of input contacts to explore the fold space under the guidance of a soft square energy function, and then clusters the models to obtain the top five models. CONFOLD2 obtains an average reconstruction accuracy of 0.57 TM-score for the 150 proteins in the PSICOV contact prediction dataset. When benchmarked on the CASP11 contacts predicted using CONSIP2 and CASP12 contacts predicted using Raptor-X, CONFOLD2 achieves a mean TM-score of 0.41 on both datasets. CONFOLD2 allows to quickly generate top five structural models for a protein sequence when its secondary structures and contacts predictions at hand. The source code of CONFOLD2 is publicly available at https://github.com/multicom-toolbox/CONFOLD2/ .

A novel mosquito ubiquitin targets viral envelope protein for degradation and reduces virion production during dengue virus infection.

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Troupin, Andrea; Londono-Renteria, Berlin; Conway, Michael J; Cloherty, Erin; Jameson, Samuel; Higgs, Stephen; Vanlandingham, Dana L; Fikrig, Erol; Colpitts, Tonya M

2016-09-01

Dengue virus (DENV) is a mosquito-borne flavivirus that causes significant human disease and mortality in the tropics and subtropics. By examining the effects of virus infection on gene expression, and interactions between virus and vector, new targets for prevention of infection and novel treatments may be identified in mosquitoes. We previously performed a microarray analysis of the Aedes aegypti transcriptome during infection with DENV and found that mosquito ubiquitin protein Ub3881 (AAEL003881) was specifically and highly down-regulated. Ubiquitin proteins have multiple functions in insects, including marking proteins for proteasomal degradation, regulating apoptosis and mediating innate immune signaling. We used qRT-PCR to quantify gene expression and infection, and RNAi to reduce Ub3881 expression. Mosquitoes were infected with DENV through blood feeding. We transfected DENV protein expression constructs to examine the effect of Ub3881 on protein degradation. We used site-directed mutagenesis and transfection to determine what amino acids are involved in Ub3881-mediated protein degradation. Immunofluorescence, Co-immunoprecipitation and Western blotting were used to examine protein interactions and co-localization. The overexpression of Ub3881, but not related ubiquitin proteins, decreased DENV infection in mosquito cells and live Ae. aegypti. The Ub3881 protein was demonstrated to be involved in DENV envelope protein degradation and reduce the number of infectious virions released. We conclude that Ub3881 has several antiviral functions in the mosquito, including specific viral protein degradation. Our data highlights Ub3881 as a target for future DENV prevention strategies in the mosquito transmission vector. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Are animal models predictive for human postmortem muscle protein degradation?

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Ehrenfellner, Bianca; Zissler, Angela; Steinbacher, Peter; Monticelli, Fabio C; Pittner, Stefan

2017-11-01

A most precise determination of the postmortem interval (PMI) is a crucial aspect in forensic casework. Although there are diverse approaches available to date, the high heterogeneity of cases together with the respective postmortal changes often limit the validity and sufficiency of many methods. Recently, a novel approach for time since death estimation by the analysis of postmortal changes of muscle proteins was proposed. It is however necessary to improve the reliability and accuracy, especially by analysis of possible influencing factors on protein degradation. This is ideally investigated on standardized animal models that, however, require legitimization by a comparison of human and animal tissue, and in this specific case of protein degradation profiles. Only if protein degradation events occur in comparable fashion within different species, respective findings can sufficiently be transferred from the animal model to application in humans. Therefor samples from two frequently used animal models (mouse and pig), as well as forensic cases with representative protein profiles of highly differing PMIs were analyzed. Despite physical and physiological differences between species, western blot analysis revealed similar patterns in most of the investigated proteins. Even most degradation events occurred in comparable fashion. In some other aspects, however, human and animal profiles depicted distinct differences. The results of this experimental series clearly indicate the huge importance of comparative studies, whenever animal models are considered. Although animal models could be shown to reflect the basic principles of protein degradation processes in humans, we also gained insight in the difficulties and limitations of the applicability of the developed methodology in different mammalian species regarding protein specificity and methodic functionality.

Hidden Markov model-derived structural alphabet for proteins: the learning of protein local shapes captures sequence specificity.

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Camproux, A C; Tufféry, P

2005-08-05

Understanding and predicting protein structures depend on the complexity and the accuracy of the models used to represent them. We have recently set up a Hidden Markov Model to optimally compress protein three-dimensional conformations into a one-dimensional series of letters of a structural alphabet. Such a model learns simultaneously the shape of representative structural letters describing the local conformation and the logic of their connections, i.e. the transition matrix between the letters. Here, we move one step further and report some evidence that such a model of protein local architecture also captures some accurate amino acid features. All the letters have specific and distinct amino acid distributions. Moreover, we show that words of amino acids can have significant propensities for some letters. Perspectives point towards the prediction of the series of letters describing the structure of a protein from its amino acid sequence.

Hidden markov model for the prediction of transmembrane proteins using MATLAB.

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Chaturvedi, Navaneet; Shanker, Sudhanshu; Singh, Vinay Kumar; Sinha, Dhiraj; Pandey, Paras Nath

2011-01-01

Since membranous proteins play a key role in drug targeting therefore transmembrane proteins prediction is active and challenging area of biological sciences. Location based prediction of transmembrane proteins are significant for functional annotation of protein sequences. Hidden markov model based method was widely applied for transmembrane topology prediction. Here we have presented a revised and a better understanding model than an existing one for transmembrane protein prediction. Scripting on MATLAB was built and compiled for parameter estimation of model and applied this model on amino acid sequence to know the transmembrane and its adjacent locations. Estimated model of transmembrane topology was based on TMHMM model architecture. Only 7 super states are defined in the given dataset, which were converted to 96 states on the basis of their length in sequence. Accuracy of the prediction of model was observed about 74 %, is a good enough in the area of transmembrane topology prediction. Therefore we have concluded the hidden markov model plays crucial role in transmembrane helices prediction on MATLAB platform and it could also be useful for drug discovery strategy. The database is available for free at bioinfonavneet@gmail.comvinaysingh@bhu.ac.in.

Modeling of axonal endoplasmic reticulum network by spastic paraplegia proteins.

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Yalçın, Belgin; Zhao, Lu; Stofanko, Martin; O'Sullivan, Niamh C; Kang, Zi Han; Roost, Annika; Thomas, Matthew R; Zaessinger, Sophie; Blard, Olivier; Patto, Alex L; Sohail, Anood; Baena, Valentina; Terasaki, Mark; O'Kane, Cahir J

2017-07-25

Axons contain a smooth tubular endoplasmic reticulum (ER) network that is thought to be continuous with ER throughout the neuron; the mechanisms that form this axonal network are unknown. Mutations affecting reticulon or REEP proteins, with intramembrane hairpin domains that model ER membranes, cause an axon degenerative disease, hereditary spastic paraplegia (HSP). We show that Drosophila axons have a dynamic axonal ER network, which these proteins help to model. Loss of HSP hairpin proteins causes ER sheet expansion, partial loss of ER from distal motor axons, and occasional discontinuities in axonal ER. Ultrastructural analysis reveals an extensive ER network in axons, which shows larger and fewer tubules in larvae that lack reticulon and REEP proteins, consistent with loss of membrane curvature. Therefore HSP hairpin-containing proteins are required for shaping and continuity of axonal ER, thus suggesting roles for ER modeling in axon maintenance and function.

Acute high-caffeine exposure increases autophagic flux and reduces protein synthesis in C2C12 skeletal myotubes.

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Hughes, M A; Downs, R M; Webb, G W; Crocker, C L; Kinsey, S T; Baumgarner, Bradley L

2017-04-01

Caffeine is a highly catabolic dietary stimulant. High caffeine concentrations (1-10 mM) have previously been shown to inhibit protein synthesis and increase protein degradation in various mammalian cell lines. The purpose of this study was to examine the effect of short-term caffeine exposure on cell signaling pathways that regulate protein metabolism in mammalian skeletal muscle cells. Fully differentiated C2C12 skeletal myotubes either received vehicle (DMSO) or 5 mM caffeine for 6 h. Our analysis revealed that caffeine promoted a 40% increase in autolysosome formation and a 25% increase in autophagic flux. In contrast, caffeine treatment did not significantly increase the expression of the skeletal muscle specific ubiquitin ligases MAFbx and MuRF1 or 20S proteasome activity. Caffeine treatment significantly reduced mTORC1 signaling, total protein synthesis and myotube diameter in a CaMKKβ/AMPK-dependent manner. Further, caffeine promoted a CaMKII-dependent increase in myostatin mRNA expression that did not significantly contribute to the caffeine-dependent reduction in protein synthesis. Our results indicate that short-term caffeine exposure significantly reduced skeletal myotube diameter by increasing autophagic flux and promoting a CaMKKβ/AMPK-dependent reduction in protein synthesis.

A model in which heat shock protein 90 targets protein-folding clefts: rationale for a new approach to neuroprotective treatment of protein folding diseases.

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Pratt, William B; Morishima, Yoshihiro; Gestwicki, Jason E; Lieberman, Andrew P; Osawa, Yoichi

2014-11-01

In an EBM Minireview published in 2010, we proposed that the heat shock protein (Hsp)90/Hsp70-based chaperone machinery played a major role in determining the selection of proteins that have undergone oxidative or other toxic damage for ubiquitination and proteasomal degradation. The proposal was based on a model in which the Hsp90 chaperone machinery regulates signaling by modulating ligand-binding clefts. The model provides a framework for thinking about the development of neuroprotective therapies for protein-folding diseases like Alzheimer's disease (AD), Parkinson's disease (PD), and the polyglutamine expansion disorders, such as Huntington's disease (HD) and spinal and bulbar muscular atrophy (SBMA). Major aberrant proteins that misfold and accumulate in these diseases are "client" proteins of the abundant and ubiquitous stress chaperone Hsp90. These Hsp90 client proteins include tau (AD), α-synuclein (PD), huntingtin (HD), and the expanded glutamine androgen receptor (polyQ AR) (SBMA). In this Minireview, we update our model in which Hsp90 acts on protein-folding clefts and show how it forms a rational basis for developing drugs that promote the targeted elimination of these aberrant proteins. © 2014 by the Society for Experimental Biology and Medicine.

Models of protein and amino acid requirements for cattle

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Luis Orlindo Tedeschi

2015-03-01

Full Text Available Protein supply and requirements by ruminants have been studied for more than a century. These studies led to the accumulation of lots of scientific information about digestion and metabolism of protein by ruminants as well as the characterization of the dietary protein in order to maximize animal performance. During the 1980s and 1990s, when computers became more accessible and powerful, scientists began to conceptualize and develop mathematical nutrition models, and to program them into computers to assist with ration balancing and formulation for domesticated ruminants, specifically dairy and beef cattle. The most commonly known nutrition models developed during this period were the National Research Council (NRC in the United States, Agricultural Research Council (ARC in the United Kingdom, Institut National de la Recherche Agronomique (INRA in France, and the Commonwealth Scientific and Industrial Research Organization (CSIRO in Australia. Others were derivative works from these models with different degrees of modifications in the supply or requirement calculations, and the modeling nature (e.g., static or dynamic, mechanistic, or deterministic. Circa 1990s, most models adopted the metabolizable protein (MP system over the crude protein (CP and digestible CP systems to estimate supply of MP and the factorial system to calculate MP required by the animal. The MP system included two portions of protein (i.e., the rumen-undegraded dietary CP - RUP - and the contributions of microbial CP - MCP as the main sources of MP for the animal. Some models would explicitly account for the impact of dry matter intake (DMI on the MP required for maintenance (MPm; e.g., Cornell Net Carbohydrate and Protein System - CNCPS, the Dutch system - DVE/OEB, while others would simply account for scurf, urinary, metabolic fecal, and endogenous contributions independently of DMI. All models included milk yield and its components in estimating MP required for lactation

A reduced order model of a quadruped walking system

International Nuclear Information System (INIS)

Sano, Akihito; Furusho, Junji; Naganuma, Nobuyuki

1990-01-01

Trot walking has recently been studied by several groups because of its stability and realizability. In the trot, diagonally opposed legs form pairs. While one pair of legs provides support, the other pair of legs swings forward in preparation for the next step. In this paper, we propose a reduced order model for the trot walking. The reduced order model is derived by using two dominant modes of the closed loop system in which the local feedback at each joint is implemented. It is shown by numerical examples that the obtained reduced order model can well approximate the original higher order model. (author)

A resource for benchmarking the usefulness of protein structure models.

Science.gov (United States)

Carbajo, Daniel; Tramontano, Anna

2012-08-02

Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by non-academics: No.

A resource for benchmarking the usefulness of protein structure models

Directory of Open Access Journals (Sweden)

Carbajo Daniel

2012-08-01

Full Text Available Abstract Background Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. Results This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. Conclusions The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. Implementation, availability and requirements Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php. Operating system(s: Platform independent. Programming language: Perl-BioPerl (program; mySQL, Perl DBI and DBD modules (database; php, JavaScript, Jmol scripting (web server. Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet and PSAIA. License: Free. Any

A resource for benchmarking the usefulness of protein structure models.

KAUST Repository

Carbajo, Daniel

2012-08-02

BACKGROUND: Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. RESULTS: This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. CONCLUSIONS: The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by

A resource for benchmarking the usefulness of protein structure models.

KAUST Repository

Carbajo, Daniel; Tramontano, Anna

2012-01-01

BACKGROUND: Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. RESULTS: This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. CONCLUSIONS: The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by

Frequency distribution of the reduced unit cells of centred lattices from the Protein Data Bank.

Science.gov (United States)

Swaminathan, Kunchithapadam

2012-03-01

In crystallography, a centred conventional lattice unit cell has its corresponding reduced primitive unit cell. This study presents the frequency distribution of the reduced unit cells of all centred lattice entries of the Protein Data Bank (as of 23 August 2011) in four unit-cell-dimension-based groups and seven interaxial-angle-based subgroups. This frequency distribution is an added layer of support during space-group assignment in new crystals. In addition, some interesting patterns of distribution are discussed as well as how some reduced unit cells could be wrongly accepted as primitive lattices in a different crystal system.

Reduced protein bound uraemic toxins in vegetarian kidney failure patients treated by haemodiafiltration.

Science.gov (United States)

Kandouz, Sakina; Mohamed, Ali Shendi; Zheng, Yishan; Sandeman, Susan; Davenport, Andrew

2016-10-01

Introduction Indoxyl sulfate (IS) and p cresyl sulfate (PCS) are protein bound toxins which accumulate with chronic kidney disease. Haemodiafiltration (HDF) increases middle molecule clearances and has been suggested to increase IS and PCS clearance. We therefore wished to establish whether higher convective clearances with HDF would reduce IS and PCS concentrations. Methods We measured total plasma IS and PCS in a cohort of 138 CKD5d patients treated by On-line HDF (Ol-HDF), by high pressure liquid chromatography. Findings Mean patient age was 64.6 ± 16.5 years, 60.1% male, 57.3% diabetic, median dialysis vintage 25.9 months (12.4-62.0). The mean ICS concentration was 79.8 ± 56.4 umol/L and PCS 140.3 ± 101.8 umol/L. On multivariate analysis, IS was associated with serum albumin (β 4.31,P vegetarian diet(β-28.3, P = 0.048) and PCS negatively with log C reactive protein (β-75.8, P vegetarian diet (β-109, P = 0.001). Vegetarian patients had lower IS and PCS levels (median 41.5 (24.2-71.9) vs. 78.1 (49.5-107.5) and PCS (41.6 (14.2-178.3) vs. 127.3 (77.4-205.6) µmol/L, respectively, P Vegetarian patients had lower preOl-HDF serum urea, and phosphate (13.8 ±3.8 vs. 18.4 ± 5.2 mmol/L, and 1.33 ± 0.21 vs. 1.58 ± 0.45 mmol/L), and estimated urea nitrogen intake (1.25 ± 0.28 vs. 1.62 ± 0.5 g/kg/day), respectively, all P vegetarian diet had reduced IS and PCS concentrations. Although this could be due to differences in dietary protein intake, a vegetarian diet may also potentially reduce IS and PCS production by the intestinal microbiome. © 2016 International Society for Hemodialysis.

Preclinical models used for immunogenicity prediction of therapeutic proteins.

Science.gov (United States)

Brinks, Vera; Weinbuch, Daniel; Baker, Matthew; Dean, Yann; Stas, Philippe; Kostense, Stefan; Rup, Bonita; Jiskoot, Wim

2013-07-01

All therapeutic proteins are potentially immunogenic. Antibodies formed against these drugs can decrease efficacy, leading to drastically increased therapeutic costs and in rare cases to serious and sometimes life threatening side-effects. Many efforts are therefore undertaken to develop therapeutic proteins with minimal immunogenicity. For this, immunogenicity prediction of candidate drugs during early drug development is essential. Several in silico, in vitro and in vivo models are used to predict immunogenicity of drug leads, to modify potentially immunogenic properties and to continue development of drug candidates with expected low immunogenicity. Despite the extensive use of these predictive models, their actual predictive value varies. Important reasons for this uncertainty are the limited/insufficient knowledge on the immune mechanisms underlying immunogenicity of therapeutic proteins, the fact that different predictive models explore different components of the immune system and the lack of an integrated clinical validation. In this review, we discuss the predictive models in use, summarize aspects of immunogenicity that these models predict and explore the merits and the limitations of each of the models.

Model test on the relationship feed energy and protein ratio to the production and quality of milk protein

Science.gov (United States)

Hartanto, R.; Jantra, M. A. C.; Santosa, S. A. B.; Purnomoadi, A.

2018-01-01

The purpose of this research was to find an appropriate relationship model between the feed energy and protein ratio with the amount of production and quality of milk proteins. This research was conducted at Getasan Sub-district, Semarang Regency, Central Java Province, Indonesia using 40 samples (Holstein Friesian cattle, lactation period II-III and lactation month 3-4). Data were analyzed using linear and quadratic regressions, to predict the production and quality of milk protein from feed energy and protein ratio that describe the diet. The significance of model was tested using analysis of variance. Coefficient of determination (R2), residual variance (RV) and root mean square prediction error (RMSPE) were reported for the developed equations as an indicator of the goodness of model fit. The results showed no relationship in milk protein (kg), milk casein (%), milk casein (kg) and milk urea N (mg/dl) as function of CP/TDN. The significant relationship was observed in milk production (L or kg) and milk protein (%) as function of CP/TDN, both in linear and quadratic models. In addition, a quadratic change in milk production (L) (P = 0.003), milk production (kg) (P = 0.003) and milk protein concentration (%) (P = 0.026) were observed with increase of CP/TDN. It can be concluded that quadratic equation was the good fitting model for this research, because quadratic equation has larger R2, smaller RV and smaller RMSPE than those of linear equation.

Generalized reduced fluid model with finite ion-gyroradius effects

International Nuclear Information System (INIS)

Hsu, C.T.; Hazeltine, R.D.; Morrison, P.J.

1985-04-01

Reduced fluid models have become important tools for studying the nonlinear dynamics of plasma in a large aspect-ratio tokamak. A self-consistent nonlinear reduced fluid model, with finite ion-gyroradius effects is presented. The model is distinctive in allowing for arbitrary beta and in satisfying an exact, relatively simple energy conservation law

Protein structure analysis using the resonant recognition model and wavelet transforms

International Nuclear Information System (INIS)

Fang, Q.; Cosic, I.

1998-01-01

An approach based on the resonant recognition model and the discrete wavelet transform is introduced here for characterising proteins' biological function. The protein sequence is converted into a numerical series by assigning the electron-ion interaction potential to each amino acid from N-terminal to C-terminal. A set of peaks is found after performing a wavelet transform onto a numerical series representing a group of homologous proteins. These peaks are related to protein structural and functional properties and named characteristic vector of that protein group. Further more, the amino acids contributing mostly to a protein's biological functions, the so-called 'hot spots' amino acids, are predicted by the continuous wavelet transform. It is found that the hot spots are clustered around the protein's cleft structure. The wavelets approach provides a novel methods for amino acid sequence analysis as well as an expansion for the newly established macromolecular interaction model: the resonant recognition model. Copyright (1998) Australasian Physical and Engineering Sciences in Medicine

The APT model as reduced-rank regression

NARCIS (Netherlands)

Bekker, P.A.; Dobbelstein, P.; Wansbeek, T.J.

Integrating the two steps of an arbitrage pricing theory (APT) model leads to a reduced-rank regression (RRR) model. So the results on RRR can be used to estimate APT models, making estimation very simple. We give a succinct derivation of estimation of RRR, derive the asymptotic variance of RRR

A generative, probabilistic model of local protein structure

DEFF Research Database (Denmark)

Boomsma, Wouter; Mardia, Kanti V.; Taylor, Charles C.

2008-01-01

Despite significant progress in recent years, protein structure prediction maintains its status as one of the prime unsolved problems in computational biology. One of the key remaining challenges is an efficient probabilistic exploration of the structural space that correctly reflects the relative...... conformational stabilities. Here, we present a fully probabilistic, continuous model of local protein structure in atomic detail. The generative model makes efficient conformational sampling possible and provides a framework for the rigorous analysis of local sequence-structure correlations in the native state...

[SNACK HIGH WHEY PROTEIN IMPROVES THE LEVEL OF SATIETY AND REDUCES APPETITE HEALTHY WOMEN].

Science.gov (United States)

Reyna, Nadia; Moreno-Rojas, Rafael; Mendoza, Laura; Urdaneta, Andrés; Artigas, Carlos; Reyna, Eduardo; Cámara Martos, Fernando

2015-10-01

the nutritional content and energy density of foods is related to greater control of appetite, satiety and reducing food intake. the randomized crossover study included 20 healthy women, aged 20 and 30 years with a BMI of 20 to 24.9 kg/m2 and who completed that included 3 day trial comparing 8 hours 130 kcal snacks consumed afternoon: yoghurt with added whey protein (PSL), biscuits and chocolate. Participants consumed a standardized menu; snack was consumed 3 hours after lunch. Perceived hunger and fullness were evaluated during the afternoon until dinner voluntary intake ad libitum. They repeat the same snack 3 times. consumption of yogurt with PSL led to a further reduction of appetite in the afternoon in front of the snack of chocolate and biscuits (p snack, yogurt there was a significant reduction in caloric intake compared to other snacks (p snacks with less energy density and rich in protein (yogurt with PSL) improve the control of appetite, satiety and reduces food intake in healthy women later. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Modeling disordered regions in proteins using Rosetta.

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Ray Yu-Ruei Wang

Full Text Available Protein structure prediction methods such as Rosetta search for the lowest energy conformation of the polypeptide chain. However, the experimentally observed native state is at a minimum of the free energy, rather than the energy. The neglect of the missing configurational entropy contribution to the free energy can be partially justified by the assumption that the entropies of alternative folded states, while very much less than unfolded states, are not too different from one another, and hence can be to a first approximation neglected when searching for the lowest free energy state. The shortcomings of current structure prediction methods may be due in part to the breakdown of this assumption. Particularly problematic are proteins with significant disordered regions which do not populate single low energy conformations even in the native state. We describe two approaches within the Rosetta structure modeling methodology for treating such regions. The first does not require advance knowledge of the regions likely to be disordered; instead these are identified by minimizing a simple free energy function used previously to model protein folding landscapes and transition states. In this model, residues can be either completely ordered or completely disordered; they are considered disordered if the gain in entropy outweighs the loss of favorable energetic interactions with the rest of the protein chain. The second approach requires identification in advance of the disordered regions either from sequence alone using for example the DISOPRED server or from experimental data such as NMR chemical shifts. During Rosetta structure prediction calculations the disordered regions make only unfavorable repulsive contributions to the total energy. We find that the second approach has greater practical utility and illustrate this with examples from de novo structure prediction, NMR structure calculation, and comparative modeling.

Hybrid reduced order modeling for assembly calculations

Energy Technology Data Exchange (ETDEWEB)

Bang, Y.; Abdel-Khalik, H. S. [North Carolina State University, Raleigh, NC (United States); Jessee, M. A.; Mertyurek, U. [Oak Ridge National Laboratory, Oak Ridge, TN (United States)

2013-07-01

While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system. (authors)

Surfactant Protein-B 121ins2 Heterozygosity, Reduced Pulmonary Function and COPD in Smokers

DEFF Research Database (Denmark)

Bækvad-Hansen, Marie; Dahl, Morten; Tybjærg-Hansen, Anne

2010-01-01

.2-4.8) for spirometry defined COPD and of 2.2(1.0-5.1) for hospitalization due to COPD. Among never smokers, 121ins2 heterozygotes did not differ from wildtypes in lung function or risk of COPD. CONCLUSIONS: Surfactant protein-B 121ins2 heterozygosity is associated with reduced lung function and increased risk for COPD......2 mutation have reduced lung function and increased risk for chronic obstructive pulmonary disease (COPD) among smokers. METHODS: We genotyped 47,600 individuals from the adult Danish general population and recorded smoking habits, spirometry and hospital admissions due to COPD. The study...... that the effect of genotype differ by smoking status. Among smokers, 121ins2 heterozygotes had 9% reduced FEV1%predicted(p=0.0008), 6% reduced FVC%predicted(p=0.01) and 6% reduced FEV1/FVC(p=0.00007), compared with wildtypes. Also among smokers, 121ins2 heterozygotes had odds ratios of 2.4(95%CI 1...

Whey protein reduces early life weight gain in mice fed a high-fat diet

DEFF Research Database (Denmark)

Tranberg, Britt; Hellgren, Lars; Lykkesfeldt, Jens

2013-01-01

An increasing number of studies indicate that dairy products, including whey protein, alleviate several disorders of the metabolic syndrome. Here, we investigated the effects of whey protein isolate (whey) in mice fed a high-fat diet hypothesising that the metabolic effects of whey would...... be associated with changes in the gut microbiota composition. Five-week-old male C57BL/6 mice were fed a high-fat diet ad libitum for 14 weeks with the protein source being either whey or casein. Faeces were collected at week 0, 7, and 13 and the fecal microbiota was analysed by denaturing gradient gel...... electrophoresis analyses of PCR-derived 16S rRNA gene (V3-region) amplicons. At the end of the study, plasma samples were collected and assayed for glucose, insulin and lipids. Whey significantly reduced body weight gain during the first four weeks of the study compared with casein (P

A Protein Extract from Chicken Reduces Plasma Homocysteine in Rats

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Vegard Lysne

2015-06-01

Full Text Available The present study aimed to evaluate effects of a water-soluble protein fraction of chicken (CP, with a low methionine/glycine ratio, on plasma homocysteine and metabolites related to homocysteine metabolism. Male Wistar rats were fed either a control diet with 20% w/w casein as the protein source, or an experimental diet where 6, 14 or 20% w/w of the casein was replaced with the same amount of CP for four weeks. Rats fed CP had reduced plasma total homocysteine level and markedly increased levels of the choline pathway metabolites betaine, dimethylglycine, sarcosine, glycine and serine, as well as the transsulfuration pathway metabolites cystathionine and cysteine. Hepatic mRNA level of enzymes involved in homocysteine remethylation, methionine synthase and betaine-homocysteine S-methyltransferase, were unchanged, whereas cystathionine gamma-lyase of the transsulfuration pathway was increased in the CP treated rats. Plasma concentrations of vitamin B2, folate, cobalamin, and the B-6 catabolite pyridoxic acid were increased in the 20% CP-treated rats. In conclusion, the CP diet was associated with lower plasma homocysteine concentration and higher levels of serine, choline oxidation and transsulfuration metabolites compared to a casein diet. The status of related B-vitamins was also affected by CP.

Conformational Sampling in Template-Free Protein Loop Structure Modeling: An Overview

OpenAIRE

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a “mini protein folding problem” under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increas...

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

KAUST Repository

Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z.; Gao, Xin

2017-01-01

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

KAUST Repository

Najibi, Seyed Morteza

2017-02-08

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

A branch-heterogeneous model of protein evolution for efficient inference of ancestral sequences.

Science.gov (United States)

Groussin, M; Boussau, B; Gouy, M

2013-07-01

Most models of nucleotide or amino acid substitution used in phylogenetic studies assume that the evolutionary process has been homogeneous across lineages and that composition of nucleotides or amino acids has remained the same throughout the tree. These oversimplified assumptions are refuted by the observation that compositional variability characterizes extant biological sequences. Branch-heterogeneous models of protein evolution that account for compositional variability have been developed, but are not yet in common use because of the large number of parameters required, leading to high computational costs and potential overparameterization. Here, we present a new branch-nonhomogeneous and nonstationary model of protein evolution that captures more accurately the high complexity of sequence evolution. This model, henceforth called Correspondence and likelihood analysis (COaLA), makes use of a correspondence analysis to reduce the number of parameters to be optimized through maximum likelihood, focusing on most of the compositional variation observed in the data. The model was thoroughly tested on both simulated and biological data sets to show its high performance in terms of data fitting and CPU time. COaLA efficiently estimates ancestral amino acid frequencies and sequences, making it relevant for studies aiming at reconstructing and resurrecting ancestral amino acid sequences. Finally, we applied COaLA on a concatenate of universal amino acid sequences to confirm previous results obtained with a nonhomogeneous Bayesian model regarding the early pattern of adaptation to optimal growth temperature, supporting the mesophilic nature of the Last Universal Common Ancestor.

Alpha-1 antitrypsin protein and gene therapies decrease autoimmunity and delay arthritis development in mouse model

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Atkinson Mark A

2011-02-01

Full Text Available Abstract Background Alpha-1 antitrypsin (AAT is a multi-functional protein that has anti-inflammatory and tissue protective properties. We previously reported that human AAT (hAAT gene therapy prevented autoimmune diabetes in non-obese diabetic (NOD mice and suppressed arthritis development in combination with doxycycline in mice. In the present study we investigated the feasibility of hAAT monotherapy for the treatment of chronic arthritis in collagen-induced arthritis (CIA, a mouse model of rheumatoid arthritis (RA. Methods DBA/1 mice were immunized with bovine type II collagen (bCII to induce arthritis. These mice were pretreated either with hAAT protein or with recombinant adeno-associated virus vector expressing hAAT (rAAV-hAAT. Control groups received saline injections. Arthritis development was evaluated by prevalence of arthritis and arthritic index. Serum levels of B-cell activating factor of the TNF-α family (BAFF, antibodies against both bovine (bCII and mouse collagen II (mCII were tested by ELISA. Results Human AAT protein therapy as well as recombinant adeno-associated virus (rAAV8-mediated hAAT gene therapy significantly delayed onset and ameliorated disease development of arthritis in CIA mouse model. Importantly, hAAT therapies significantly reduced serum levels of BAFF and autoantibodies against bCII and mCII, suggesting that the effects are mediated via B-cells, at least partially. Conclusion These results present a new drug for arthritis therapy. Human AAT protein and gene therapies are able to ameliorate and delay arthritis development and reduce autoimmunity, indicating promising potential of these therapies as a new treatment strategy for RA.

Reduced homeobox protein MSX1 in human endometrial tissue is linked to infertility.

Science.gov (United States)

Bolnick, Alan D; Bolnick, Jay M; Kilburn, Brian A; Stewart, Tamika; Oakes, Jonathan; Rodriguez-Kovacs, Javier; Kohan-Ghadr, Hamid-Reza; Dai, Jing; Diamond, Michael P; Hirota, Yasushi; Drewlo, Sascha; Dey, Sudhansu K; Armant, D Randall

2016-09-01

Is protein expression of the muscle segment homeobox gene family member MSX1 altered in the human secretory endometrium by cell type, developmental stage or fertility? MSX1 protein levels, normally elevated in the secretory phase endometrium, were significantly reduced in endometrial biopsies obtained from women of infertile couples. Molecular changes in the endometrium are important for fertility in both animals and humans. Msx1 is expressed in the preimplantation mouse uterus and regulates uterine receptivity for implantation. The MSX protein persists a short time, after its message has been down-regulated. Microarray analysis of the human endometrium reveals a similar pattern of MSX1 mRNA expression that peaks before the receptive period, with depressed expression at implantation. Targeted deletion of uterine Msx1 and Msx2 in mice prevents the loss of epithelial cell polarity during implantation and causes infertility. MSX1 mRNA and cell type-specific levels of MSX1 protein were quantified from two retrospective cohorts during the human endometrial cycle. MSX1 protein expression patterns were compared between fertile and infertile couples. Selected samples were dual-labeled by immunofluorescence microscopy to localize E-cadherin and β-catenin in epithelial cells. MSX1 mRNA was quantified by PCR in endometrium from hysterectomies (n = 14) determined by endometrial dating to be in the late-proliferative (cycle days 10-13), early-secretory (cycle days 14-19) or mid-secretory (cycle days 20-24) phase. MSX1 protein was localized using high-throughput, semi-quantitative immunohistochemistry with sectioned endometrial biopsy tissues from fertile (n = 89) and infertile (n = 89) couples. Image analysis measured stain intensity specifically within the luminal epithelium, glands and stroma during the early-, mid- and late- (cycle days 25-28) secretory phases. MSX1 transcript increased 5-fold (P MSX1 protein displayed strong nuclear localization in the luminal epithelium

Can molecular dynamics simulations help in discriminating correct from erroneous protein 3D models?

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Gibrat Jean-François

2008-01-01

Full Text Available Abstract Background Recent approaches for predicting the three-dimensional (3D structure of proteins such as de novo or fold recognition methods mostly rely on simplified energy potential functions and a reduced representation of the polypeptide chain. These simplifications facilitate the exploration of the protein conformational space but do not permit to capture entirely the subtle relationship that exists between the amino acid sequence and its native structure. It has been proposed that physics-based energy functions together with techniques for sampling the conformational space, e.g., Monte Carlo or molecular dynamics (MD simulations, are better suited to the task of modelling proteins at higher resolutions than those of models obtained with the former type of methods. In this study we monitor different protein structural properties along MD trajectories to discriminate correct from erroneous models. These models are based on the sequence-structure alignments provided by our fold recognition method, FROST. We define correct models as being built from alignments of sequences with structures similar to their native structures and erroneous models from alignments of sequences with structures unrelated to their native structures. Results For three test sequences whose native structures belong to the all-α, all-β and αβ classes we built a set of models intended to cover the whole spectrum: from a perfect model, i.e., the native structure, to a very poor model, i.e., a random alignment of the test sequence with a structure belonging to another structural class, including several intermediate models based on fold recognition alignments. We submitted these models to 11 ns of MD simulations at three different temperatures. We monitored along the corresponding trajectories the mean of the Root-Mean-Square deviations (RMSd with respect to the initial conformation, the RMSd fluctuations, the number of conformation clusters, the evolution of

Threonine supplementation reduces dietary protein and improves lipid metabolism in Pekin ducks.

Science.gov (United States)

Jiang, Y; Tang, J; Xie, M; Wen, Z G; Qiao, S Y; Hou, S S

2017-12-01

1. This study was conducted to investigate the efficiency of threonine (Thr) supplementation on reducing dietary crude protein (CP) content and the effects of Thr on lipid metabolism in Pekin ducks. The effects of dietary CP concentration (160, 190 and 220 g/kg) and Thr supplemental concentration (0, 0.7, 1.4, 2.1 and 2.8 g/kg) on growth performance, carcass, liver lipid and plasma profiles were determined in Pekin ducks from 1-21 d of age. 2. A total of 720-d-old male Pekin ducks were randomly allotted to 1 of 15 dietary treatments with 6 replicate cages of 8 birds per cage for each treatment according to average body weight. 3. Dietary Thr supplementation improved growth performance and breast muscle percentage at all CP diets, and ducks fed Thr-supplemented diets had higher plasma concentrations of some plasma amino acids. Thr supplementation reduced the concentrations of total lipid, triglyceride, cholesterol in liver, and plasma low density lipoprotein cholesterin concentration at 160 and 190 g/kg CP, whereas it increased triglyceride concentration at 160 g/kg CP. 4. Thr requirements based on quadratic broken-line model estimation were 6.6 and 7.0 g/kg for optimal average daily gain (ADG), and 6.7 and 7.3 g/kg for breast muscle percentage of Pekin ducks from 1-21 d of age at 190 and 220 g/kg CP, respectively. The dietary Thr requirements and estimated ADG (55.18 vs. 55.86 g/d/bird) and breast muscle percentage (2.79% vs. 2.75%) of Pekin ducks did not differ between 190 and 220 g/kg CP according to the t-test results. 5. Dietary CP level could be reduced to 190 g/kg in Pekin ducks from 1-21 d of age with Thr supplementation to balance dietary amino acids, and Thr supplementation prevented excess liver lipid deposition in this instance.

Obeticholic acid raises LDL-cholesterol and reduces HDL-cholesterol in the Diet-Induced NASH (DIN) hamster model.

Science.gov (United States)

Briand, François; Brousseau, Emmanuel; Quinsat, Marjolaine; Burcelin, Rémy; Sulpice, Thierry

2018-01-05

The use of rat and mouse models limits the translation to humans for developing novel drugs targeting nonalcoholic steatohepatitis (NASH). Obeticholic acid (OCA) illustrates this limitation since its dyslipidemic effect in humans cannot be observed in these rodents. Conversely, Golden Syrian hamsters have a lipoprotein metabolism mimicking human dyslipidemia since it does express the cholesteryl ester transfer protein (CETP). We therefore developed a Diet-Induced NASH (DIN) hamster model and evaluated the impact of OCA. Compared with chow fed controls, hamsters fed for 20 weeks with a free-choice (FC) diet, developed obesity, insulin resistance, dyslipidemia and NASH (microvesicular steatosis, inflammation, hepatocyte ballooning and perisinusoidal to bridging fibrosis). After 20 weeks of diet, FC fed hamsters were treated without or with obeticholic acid (15mg/kg/day) for 5 weeks. Although a non-significant trend towards higher dietary caloric intake was observed, OCA significantly lowered body weight after 5 weeks of treatment. OCA significantly increased CETP activity and LDL-C levels by 20% and 27%, and reduced HDL-C levels by 20%. OCA blunted hepatic gene expression of Cyp7a1 and Cyp8b1 and reduced fecal bile acids mass excretion by 64% (P OCA showed a trend towards higher scavenger receptor Class B type I (SR-BI) and lower LDL-receptor hepatic protein expression. OCA reduced NAS score for inflammation (P OCA as observed in humans, and should be useful for evaluating novel drugs targeting NASH. Copyright © 2017 Elsevier B.V. All rights reserved.

Model of a DNA-protein complex of the architectural monomeric protein MC1 from Euryarchaea.

Directory of Open Access Journals (Sweden)

Françoise Paquet

Full Text Available In Archaea the two major modes of DNA packaging are wrapping by histone proteins or bending by architectural non-histone proteins. To supplement our knowledge about the binding mode of the different DNA-bending proteins observed across the three domains of life, we present here the first model of a complex in which the monomeric Methanogen Chromosomal protein 1 (MC1 from Euryarchaea binds to the concave side of a strongly bent DNA. In laboratory growth conditions MC1 is the most abundant architectural protein present in Methanosarcina thermophila CHTI55. Like most proteins that strongly bend DNA, MC1 is known to bind in the minor groove. Interaction areas for MC1 and DNA were mapped by Nuclear Magnetic Resonance (NMR data. The polarity of protein binding was determined using paramagnetic probes attached to the DNA. The first structural model of the DNA-MC1 complex we propose here was obtained by two complementary docking approaches and is in good agreement with the experimental data previously provided by electron microscopy and biochemistry. Residues essential to DNA-binding and -bending were highlighted and confirmed by site-directed mutagenesis. It was found that the Arg25 side-chain was essential to neutralize the negative charge of two phosphates that come very close in response to a dramatic curvature of the DNA.

Protein homology model refinement by large-scale energy optimization.

Science.gov (United States)

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

A class frequency mixture model that adjusts for site-specific amino acid frequencies and improves inference of protein phylogeny

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Li Karen

2008-12-01

Full Text Available Abstract Background Widely used substitution models for proteins, such as the Jones-Taylor-Thornton (JTT or Whelan and Goldman (WAG models, are based on empirical amino acid interchange matrices estimated from databases of protein alignments that incorporate the average amino acid frequencies of the data set under examination (e.g JTT + F. Variation in the evolutionary process between sites is typically modelled by a rates-across-sites distribution such as the gamma (Γ distribution. However, sites in proteins also vary in the kinds of amino acid interchanges that are favoured, a feature that is ignored by standard empirical substitution matrices. Here we examine the degree to which the pattern of evolution at sites differs from that expected based on empirical amino acid substitution models and evaluate the impact of these deviations on phylogenetic estimation. Results We analyzed 21 large protein alignments with two statistical tests designed to detect deviation of site-specific amino acid distributions from data simulated under the standard empirical substitution model: JTT+ F + Γ. We found that the number of states at a given site is, on average, smaller and the frequencies of these states are less uniform than expected based on a JTT + F + Γ substitution model. With a four-taxon example, we show that phylogenetic estimation under the JTT + F + Γ model is seriously biased by a long-branch attraction artefact if the data are simulated under a model utilizing the observed site-specific amino acid frequencies from an alignment. Principal components analyses indicate the existence of at least four major site-specific frequency classes in these 21 protein alignments. Using a mixture model with these four separate classes of site-specific state frequencies plus a fifth class of global frequencies (the JTT + cF + Γ model, significant improvements in model fit for real data sets can be achieved. This simple mixture model also reduces the long

The research methods and model of protein turnover in animal

International Nuclear Information System (INIS)

Wu Xilin; Yang Feng

2002-01-01

The author discussed the concept and research methods of protein turnover in animal body. The existing problems and the research results of animal protein turnover in recent years were presented. Meanwhile, the measures to improve the models of animal protein turnover were analyzed

Improving N-terminal protein annotation of Plasmodium species based on signal peptide prediction of orthologous proteins

Directory of Open Access Journals (Sweden)

Neto Armando

2012-11-01

Full Text Available Abstract Background Signal peptide is one of the most important motifs involved in protein trafficking and it ultimately influences protein function. Considering the expected functional conservation among orthologs it was hypothesized that divergence in signal peptides within orthologous groups is mainly due to N-terminal protein sequence misannotation. Thus, discrepancies in signal peptide prediction of orthologous proteins were used to identify misannotated proteins in five Plasmodium species. Methods Signal peptide (SignalP and orthology (OrthoMCL were combined in an innovative strategy to identify orthologous groups showing discrepancies in signal peptide prediction among their protein members (Mixed groups. In a comparative analysis, multiple alignments for each of these groups and gene models were visually inspected in search of misannotated proteins and, whenever possible, alternative gene models were proposed. Thresholds for signal peptide prediction parameters were also modified to reduce their impact as a possible source of discrepancy among orthologs. Validation of new gene models was based on RT-PCR (few examples or on experimental evidence already published (ApiLoc. Results The rate of misannotated proteins was significantly higher in Mixed groups than in Positive or Negative groups, corroborating the proposed hypothesis. A total of 478 proteins were reannotated and change of signal peptide prediction from negative to positive was the most common. Reannotations triggered the conversion of almost 50% of all Mixed groups, which were further reduced by optimization of signal peptide prediction parameters. Conclusions The methodological novelty proposed here combining orthology and signal peptide prediction proved to be an effective strategy for the identification of proteins showing wrongly N-terminal annotated sequences, and it might have an important impact in the available data for genome-wide searching of potential vaccine and drug

A simple quantitative model of macromolecular crowding effects on protein folding: Application to the murine prion protein(121-231)

Science.gov (United States)

Bergasa-Caceres, Fernando; Rabitz, Herschel A.

2013-06-01

A model of protein folding kinetics is applied to study the effects of macromolecular crowding on protein folding rate and stability. Macromolecular crowding is found to promote a decrease of the entropic cost of folding of proteins that produces an increase of both the stability and the folding rate. The acceleration of the folding rate due to macromolecular crowding is shown to be a topology-dependent effect. The model is applied to the folding dynamics of the murine prion protein (121-231). The differential effect of macromolecular crowding as a function of protein topology suffices to make non-native configurations relatively more accessible.

Reverse time migration by Krylov subspace reduced order modeling

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Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali

2018-04-01

Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.

Evaluating and reducing a model of radiocaesium soil-plant uptake

Energy Technology Data Exchange (ETDEWEB)

Tarsitano, D.; Young, S.D. [School of Biosciences, University of Nottingham, University Park, Nottingham, NG7 2RD (United Kingdom); Crout, N.M.J., E-mail: neil.crout@nottingham.ac.u [School of Biosciences, University of Nottingham, University Park, Nottingham, NG7 2RD (United Kingdom)

2011-03-15

An existing model of radiocaesium transfer to grasses was extended to include wheat and barley and parameterised using data from a wide range of soils and contact times. The model structure was revised and evaluated using a subset of the available data which was not used for model parameterisation. The resulting model was then used as a basis for systematic model reduction to test the utility of the model components. This analysis suggested that the use of 4 model variables (relating to radiocaesium adsorption on organic matter and the pH sensitivity of soil solution potassium concentration) and 1 model input (pH) are not required. The results of this analysis were used to develop a reduced model which was further evaluated in terms of comparisons to observations. The reduced model had an improved empirical performance and fewer adjustable parameters and soil characteristic inputs. - Research highlights: {yields} A model of plant radiocesium uptake is evaluated and re-parameterised. {yields} The representation of time dependent changes in plant uptake is improved. {yields} Model reduction is applied to evaluate the model structure. {yields} A reduced model is identified which outperforms the previously reported model. {yields} The reduced model requires fewer soil specific inputs.

Possibilities of microscopic detection of isolated porcine proteins in model meat products

Directory of Open Access Journals (Sweden)

Michaela Petrášová

2016-05-01

Full Text Available In recent years, various protein additives intended for manufacture of meat products have increasing importance in the food industry. These ingredients include both, plant-origin as well as animal-origin proteins. Among animal proteins, blood plasma, milk protein or collagen are used most commonly. Collagen is obtained from pork, beef, and poultry or fish skin. Collagen does not contain all the essential amino acids, thus it is not a full protein in terms of essential amino acids supply for one's organism. However, it is rather rich in amino acids of glycine, hydroxyproline and proline which are almost absent in other proteins and their synthesis is very energy intensive. Collagen, which is added to the soft and small meat products in the form of isolated porcine protein, significantly affects the organoleptic properties of these products. This work focused on detection of isolated porcine protein in model meat products where detection of isolated porcine protein was verified by histological staining and light microscopy. Seven model meat products from poultry meat and 7 model meat products from beef and pork in the ratio of 1:1, which contained 2.5% concentration of various commercially produced isolated porcine proteins, were examined. These model meat products were histologically processed by means of cryosections and stained with hematoxylin-eosin staining, toluidine blue staining and Calleja. For the validation phase, Calleja was utilized. To determine the sensitivity and specificity, five model meat products containing the addition of isolated porcine protein and five model meat products free of it were used. The sensitivity was determined for isolated porcine protein at 1.00 and specificity was determined at 1.00. The detection limit of the method was at the level of 0.001% addition. Repeatability of the method was carried out using products with addition as well as without addition of isolated porcine protein and detection was repeated

A linear programming model for protein inference problem in shotgun proteomics.

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Huang, Ting; He, Zengyou

2012-11-15

Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is an important issue in shotgun proteomics. The objective of protein inference is to find a subset of proteins that are truly present in the sample. Although many methods have been proposed for protein inference, several issues such as peptide degeneracy still remain unsolved. In this article, we present a linear programming model for protein inference. In this model, we use a transformation of the joint probability that each peptide/protein pair is present in the sample as the variable. Then, both the peptide probability and protein probability can be expressed as a formula in terms of the linear combination of these variables. Based on this simple fact, the protein inference problem is formulated as an optimization problem: minimize the number of proteins with non-zero probabilities under the constraint that the difference between the calculated peptide probability and the peptide probability generated from peptide identification algorithms should be less than some threshold. This model addresses the peptide degeneracy issue by forcing some joint probability variables involving degenerate peptides to be zero in a rigorous manner. The corresponding inference algorithm is named as ProteinLP. We test the performance of ProteinLP on six datasets. Experimental results show that our method is competitive with the state-of-the-art protein inference algorithms. The source code of our algorithm is available at: https://sourceforge.net/projects/prolp/. zyhe@dlut.edu.cn. Supplementary data are available at Bioinformatics Online.

Development of a Model Protein Interaction Pair as a Benchmarking Tool for the Quantitative Analysis of 2-Site Protein-Protein Interactions.

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Yamniuk, Aaron P; Newitt, John A; Doyle, Michael L; Arisaka, Fumio; Giannetti, Anthony M; Hensley, Preston; Myszka, David G; Schwarz, Fred P; Thomson, James A; Eisenstein, Edward

2015-12-01

A significant challenge in the molecular interaction field is to accurately determine the stoichiometry and stepwise binding affinity constants for macromolecules having >1 binding site. The mission of the Molecular Interactions Research Group (MIRG) of the Association of Biomolecular Resource Facilities (ABRF) is to show how biophysical technologies are used to quantitatively characterize molecular interactions, and to educate the ABRF members and scientific community on the utility and limitations of core technologies [such as biosensor, microcalorimetry, or analytic ultracentrifugation (AUC)]. In the present work, the MIRG has developed a robust model protein interaction pair consisting of a bivalent variant of the Bacillus amyloliquefaciens extracellular RNase barnase and a variant of its natural monovalent intracellular inhibitor protein barstar. It is demonstrated that this system can serve as a benchmarking tool for the quantitative analysis of 2-site protein-protein interactions. The protein interaction pair enables determination of precise binding constants for the barstar protein binding to 2 distinct sites on the bivalent barnase binding partner (termed binase), where the 2 binding sites were engineered to possess affinities that differed by 2 orders of magnitude. Multiple MIRG laboratories characterized the interaction using isothermal titration calorimetry (ITC), AUC, and surface plasmon resonance (SPR) methods to evaluate the feasibility of the system as a benchmarking model. Although general agreement was seen for the binding constants measured using solution-based ITC and AUC approaches, weaker affinity was seen for surface-based method SPR, with protein immobilization likely affecting affinity. An analysis of the results from multiple MIRG laboratories suggests that the bivalent barnase-barstar system is a suitable model for benchmarking new approaches for the quantitative characterization of complex biomolecular interactions.

Identify High-Quality Protein Structural Models by Enhanced K-Means.

Science.gov (United States)

Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

Antioxidant Treatment and Induction of Autophagy Cooperate to Reduce Desmin Aggregation in a Cellular Model of Desminopathy.

Directory of Open Access Journals (Sweden)

Eva Cabet

Full Text Available Desminopathies, a subgroup of myofibrillar myopathies (MFMs, the progressive muscular diseases characterized by the accumulation of granulofilamentous desmin-positive aggregates, result from mutations in the desmin gene (DES, encoding a muscle-specific intermediate filament. Desminopathies often lead to severe disability and premature death from cardiac and/or respiratory failure; no specific treatment is currently available. To identify drug-targetable pathophysiological pathways, we performed pharmacological studies in C2C12 myoblastic cells expressing mutant DES. We found that inhibition of the Rac1 pathway (a G protein signaling pathway involved in diverse cellular processes, antioxidant treatment, and stimulation of macroautophagy reduced protein aggregation by up to 75% in this model. Further, a combination of two or three of these treatments was more effective than any of them alone. These results pave the way towards the development of the first treatments for desminopathies and are potentially applicable to other muscle or brain diseases associated with abnormal protein aggregation.

Inhibition of Cyclic Adenosine Monophosphate (cAMP-response Element-binding Protein (CREB-binding Protein (CBP/β-Catenin Reduces Liver Fibrosis in Mice

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Yosuke Osawa

2015-11-01

Full Text Available Wnt/β-catenin is involved in every aspect of embryonic development and in the pathogenesis of many human diseases, and is also implicated in organ fibrosis. However, the role of β-catenin-mediated signaling on liver fibrosis remains unclear. To explore this issue, the effects of PRI-724, a selective inhibitor of the cAMP-response element-binding protein-binding protein (CBP/β-catenin interaction, on liver fibrosis were examined using carbon tetrachloride (CCl4- or bile duct ligation (BDL-induced mouse liver fibrosis models. Following repetitive CCl4 administrations, the nuclear translocation of β-catenin was observed only in the non-parenchymal cells in the liver. PRI-724 treatment reduced the fibrosis induced by CCl4 or BDL. C-82, an active form of PRI-724, inhibited the activation of isolated primary mouse quiescent hepatic stellate cells (HSCs and promoted cell death in culture-activated HSCs. During the fibrosis resolution period, an increase in F4/80+ CD11b+ and Ly6Clow CD11b+ macrophages was induced by CCl4 and was sustained for two weeks thereafter, even after having stopped CCl4 treatment. PRI-724 accelerated the resolution of CCl4-induced liver fibrosis, and this was accompanied by increased matrix metalloproteinase (MMP-9, MMP-2, and MMP-8 expression in intrahepatic leukocytes. In conclusion, targeting the CBP/β-catenin interaction may become a new therapeutic strategy in treating liver fibrosis.

Anabolic sensitivity of postprandial muscle protein synthesis to the ingestion of a protein-dense food is reduced in overweight and obese young adults.

Science.gov (United States)

Beals, Joseph W; Sukiennik, Richard A; Nallabelli, Julian; Emmons, Russell S; van Vliet, Stephan; Young, Justin R; Ulanov, Alexander V; Li, Zhong; Paluska, Scott A; De Lisio, Michael; Burd, Nicholas A

2016-10-01

Excess body fat diminishes muscle protein synthesis rates in response to hyperinsulinemic-hyperaminoacidemic clamps. However, muscle protein synthetic responses after the ingestion of a protein-dense food source across a range of body mass indexes (BMIs) have not been compared. We compared the myofibrillar protein synthetic response and underlying nutrient-sensing mechanisms after the ingestion of lean pork between obese, overweight, and healthy-weight adults. Ten healthy-weight [HW; BMI (in kg/m 2 ): 22.7 ± 0.4], 10 overweight (OW; BMI: 27.1 ± 0.5), and 10 obese (OB; BMI: 35.9 ± 1.3) adults received primed continuous l-[ring- 13 C 6 ]phenylalanine infusions. Blood and muscle biopsy samples were collected before and after the ingestion of 170 g pork (36 g protein and 3 g fat) to assess skeletal muscle anabolic signaling, amino acid transporters [large neutral and small neutral amino acid transporters (LAT1, SNAT2) and CD98], and myofibrillar protein synthesis. At baseline, OW and OB groups showed greater relative amounts of mammalian target of rapamycin complex 1 (mTORC1) protein than the HW group. Pork ingestion increased mTORC1 phosphorylation only in the HW group (P = 0.001). LAT1 and SNAT2 protein content increased during the postprandial period in all groups (time effect, P anabolic signals, that reduces muscle sensitivity to food ingestion. This trial was registered at clinicaltrials.gov as NCT02613767. © 2016 American Society for Nutrition.

NASCENT: an automatic protein interaction network generation tool for non-model organisms.

Science.gov (United States)

Banky, Daniel; Ordog, Rafael; Grolmusz, Vince

2009-04-24

Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.

DeepQA: Improving the estimation of single protein model quality with deep belief networks

OpenAIRE

Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-01-01

Background Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. Results We introduce a novel single-model quality assessment method DeepQA based on deep belie...

A semi-nonparametric mixture model for selecting functionally consistent proteins.

Science.gov (United States)

Yu, Lianbo; Doerge, Rw

2010-09-28

High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein.

Fast Proton Titration Scheme for Multiscale Modeling of Protein Solutions.

Science.gov (United States)

Teixeira, Andre Azevedo Reis; Lund, Mikael; da Silva, Fernando Luís Barroso

2010-10-12

Proton exchange between titratable amino acid residues and the surrounding solution gives rise to exciting electric processes in proteins. We present a proton titration scheme for studying acid-base equilibria in Metropolis Monte Carlo simulations where salt is treated at the Debye-Hückel level. The method, rooted in the Kirkwood model of impenetrable spheres, is applied on the three milk proteins α-lactalbumin, β-lactoglobulin, and lactoferrin, for which we investigate the net-charge, molecular dipole moment, and charge capacitance. Over a wide range of pH and salt conditions, excellent agreement is found with more elaborate simulations where salt is explicitly included. The implicit salt scheme is orders of magnitude faster than the explicit analog and allows for transparent interpretation of physical mechanisms. It is shown how the method can be expanded to multiscale modeling of aqueous salt solutions of many biomolecules with nonstatic charge distributions. Important examples are protein-protein aggregation, protein-polyelectrolyte complexation, and protein-membrane association.

Reovirus FAST Protein Enhances Vesicular Stomatitis Virus Oncolytic Virotherapy in Primary and Metastatic Tumor Models

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Fabrice Le Boeuf

2017-09-01

Full Text Available The reovirus fusion-associated small transmembrane (FAST proteins are the smallest known viral fusogens (∼100–150 amino acids and efficiently induce cell-cell fusion and syncytium formation in multiple cell types. Syncytium formation enhances cell-cell virus transmission and may also induce immunogenic cell death, a form of apoptosis that stimulates immune recognition of tumor cells. These properties suggest that FAST proteins might serve to enhance oncolytic virotherapy. The oncolytic activity of recombinant VSVΔM51 (an interferon-sensitive vesicular stomatitis virus [VSV] mutant encoding the p14 FAST protein (VSV-p14 was compared with a similar construct encoding GFP (VSV-GFP in cell culture and syngeneic BALB/c tumor models. Compared with VSV-GFP, VSV-p14 exhibited increased oncolytic activity against MCF-7 and 4T1 breast cancer spheroids in culture and reduced primary 4T1 breast tumor growth in vivo. VSV-p14 prolonged survival in both primary and metastatic 4T1 breast cancer models, and in a CT26 metastatic colon cancer model. As with VSV-GFP, VSV-p14 preferentially replicated in vivo in tumors and was cleared rapidly from other sites. Furthermore, VSV-p14 increased the numbers of activated splenic CD4, CD8, natural killer (NK, and natural killer T (NKT cells, and increased the number of activated CD4 and CD8 cells in tumors. FAST proteins may therefore provide a multi-pronged approach to improving oncolytic virotherapy via syncytium formation and enhanced immune stimulation.

On reducibility and ergodicity of population projection matrix models

DEFF Research Database (Denmark)

Stott, Iain; Townley, Stuart; Carslake, David

2010-01-01

from all stages to all other stages) and therefore ergodic (whatever initial stage structure is used in the population projection, it will always exhibit the same stable asymptotic growth rate). 2. Evaluation of 652 PPM models for 171 species from the literature suggests that 24·7% of PPM models...... structure used in the population projection). In our sample of published PPMs, 15·6% are non-ergodic. 3. This presents a problem: reducible–ergodic models often defy biological rationale in their description of the life cycle but may or may not prove problematic for analysis as they often behave similarly...... of reducibility in published PPMs, with significant implications for the predictive power of such models in many cases. We suggest that as a general rule, reducibility of PPM models should be avoided. However, we provide a guide to the pertinent analysis of reducible matrix models, largely based upon whether...

Genome-scale modeling of the protein secretory machinery in yeast

DEFF Research Database (Denmark)

Feizi, Amir; Österlund, Tobias; Petranovic, Dina

2013-01-01

The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking....... Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm...

Protein restriction and cancer.

Science.gov (United States)

Yin, Jie; Ren, Wenkai; Huang, Xingguo; Li, Tiejun; Yin, Yulong

2018-03-26

Protein restriction without malnutrition is currently an effective nutritional intervention known to prevent diseases and promote health span from yeast to human. Recently, low protein diets are reported to be associated with lowered cancer incidence and mortality risk of cancers in human. In murine models, protein restriction inhibits tumor growth via mTOR signaling pathway. IGF-1, amino acid metabolic programing, FGF21, and autophagy may also serve as potential mechanisms of protein restriction mediated cancer prevention. Together, dietary intervention aimed at reducing protein intake can be beneficial and has the potential to be widely adopted and effective in preventing and treating cancers. Copyright © 2018 Elsevier B.V. All rights reserved.

Parametric reduced models for the nonlinear Schrödinger equation.

Science.gov (United States)

Harlim, John; Li, Xiantao

2015-05-01

Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

The Phyre2 web portal for protein modeling, prediction and analysis.

Science.gov (United States)

Kelley, Lawrence A; Mezulis, Stefans; Yates, Christopher M; Wass, Mark N; Sternberg, Michael J E

2015-06-01

Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.

Disulfide Linkage Characterization of Disulfide Bond-Containing Proteins and Peptides by Reducing Electrochemistry and Mass Spectrometry

DEFF Research Database (Denmark)

Cramer, Christian N; Haselmann, Kim F; Olsen, Jesper V

2016-01-01

in protein sequencing by tandem MS (MS/MS). Electrochemical (EC) reduction of disulfide bonds has recently been demonstrated to provide efficient reduction efficiencies, significantly enhancing sequence coverages in online coupling with MS characterization. In this study, the potential use of EC disulfide...... link between parent disulfide-linked fragments and free reduced peptides in an LC-EC-MS platform of nonreduced proteolytic protein digestions. Here we report the successful use of EC as a partial reduction approach in mapping of disulfide bonds of intact human insulin (HI) and lysozyme. In addition, we...... established a LC-EC-MS platform advantageous in disulfide characterization of complex and highly disulfide-bonded proteins such as human serum albumin (HSA) by online EC reduction of nonreduced proteolytic digestions....

Prediction of beta-turns in proteins using the first-order Markov models.

Science.gov (United States)

Lin, Thy-Hou; Wang, Ging-Ming; Wang, Yen-Tseng

2002-01-01

We present a method based on the first-order Markov models for predicting simple beta-turns and loops containing multiple turns in proteins. Sequences of 338 proteins in a database are divided using the published turn criteria into the following three regions, namely, the turn, the boundary, and the nonturn ones. A transition probability matrix is constructed for either the turn or the nonturn region using the weighted transition probabilities computed for dipeptides identified from each region. There are two such matrices constructed for the boundary region since the transition probabilities for dipeptides immediately preceding or following a turn are different. The window used for scanning a protein sequence from amino (N-) to carboxyl (C-) terminal is a hexapeptide since the transition probability computed for a turn tetrapeptide is capped at both the N- and C- termini with a boundary transition probability indexed respectively from the two boundary transition matrices. A sum of the averaged product of the transition probabilities of all the hexapeptides involving each residue is computed. This is then weighted with a probability computed from assuming that all the hexapeptides are from the nonturn region to give the final prediction quantity. Both simple beta-turns and loops containing multiple turns in a protein are then identified by the rising of the prediction quantity computed. The performance of the prediction scheme or the percentage (%) of correct prediction is evaluated through computation of Matthews correlation coefficients for each protein predicted. It is found that the prediction method is capable of giving prediction results with better correlation between the percent of correct prediction and the Matthews correlation coefficients for a group of test proteins as compared with those predicted using some secondary structural prediction methods. The prediction accuracy for about 40% of proteins in the database or 50% of proteins in the test set is

On the characterization and software implementation of general protein lattice models.

Directory of Open Access Journals (Sweden)

Alessio Bechini

Full Text Available models of proteins have been widely used as a practical means to computationally investigate general properties of the system. In lattice models any sterically feasible conformation is represented as a self-avoiding walk on a lattice, and residue types are limited in number. So far, only two- or three-dimensional lattices have been used. The inspection of the neighborhood of alpha carbons in the core of real proteins reveals that also lattices with higher coordination numbers, possibly in higher dimensional spaces, can be adopted. In this paper, a new general parametric lattice model for simplified protein conformations is proposed and investigated. It is shown how the supporting software can be consistently designed to let algorithms that operate on protein structures be implemented in a lattice-agnostic way. The necessary theoretical foundations are developed and organically presented, pinpointing the role of the concept of main directions in lattice-agnostic model handling. Subsequently, the model features across dimensions and lattice types are explored in tests performed on benchmark protein sequences, using a Python implementation. Simulations give insights on the use of square and triangular lattices in a range of dimensions. The trend of potential minimum for sequences of different lengths, varying the lattice dimension, is uncovered. Moreover, an extensive quantitative characterization of the usage of the so-called "move types" is reported for the first time. The proposed general framework for the development of lattice models is simple yet complete, and an object-oriented architecture can be proficiently employed for the supporting software, by designing ad-hoc classes. The proposed framework represents a new general viewpoint that potentially subsumes a number of solutions previously studied. The adoption of the described model pushes to look at protein structure issues from a more general and essential perspective, making

Identification of proteins in hyperglycemia and stroke animal models.

Science.gov (United States)

Sung, Jin-Hee; Shah, Fawad-Ali; Gim, Sang-Ah; Koh, Phil-Ok

2016-01-01

Stroke is a major cause of disability and death in adults. Diabetes mellitus is a metabolic disorder that strongly increases the risk of severe vascular diseases. This study compared changes in proteins of the cerebral cortex during ischemic brain injury between nondiabetic and diabetic animals. Adult male rats were injected with streptozotocin (40 mg/kg) via the intraperitoneal route to induce diabetes and underwent surgical middle cerebral artery occlusion (MCAO) 4 wk after streptozotocin treatment. Cerebral cortex tissues were collected 24 h after MCAO and cerebral cortex proteins were analyzed by two-dimensional gel electrophoresis and mass spectrometry. Several proteins were identified as differentially expressed between nondiabetic and diabetic animals. Among the identified proteins, we focused on the following metabolism-related enzymes: isocitrate dehydrogenase, glyceraldehyde-3-phosphate dehydrogenase, adenosylhomocysteinase, pyruvate kinase, and glucose-6-phosphate isomerase (neuroleukin). Expression of these proteins was decreased in animals that underwent MCAO. Moreover, protein expression was reduced to a greater extent in diabetic animals than in nondiabetic animals. Reverse transcription-polymerase chain reaction analysis confirmed that the diabetic condition exacerbates the decrease in expression of metabolism-related proteins after MCAO. These results suggest that the diabetic condition may exacerbate brain damage during focal cerebral ischemia through the downregulation of metabolism-related proteins. Copyright © 2016 Elsevier Inc. All rights reserved.

Automated de novo phasing and model building of coiled-coil proteins.

Science.gov (United States)

Rämisch, Sebastian; Lizatović, Robert; André, Ingemar

2015-03-01

Models generated by de novo structure prediction can be very useful starting points for molecular replacement for systems where suitable structural homologues cannot be readily identified. Protein-protein complexes and de novo-designed proteins are examples of systems that can be challenging to phase. In this study, the potential of de novo models of protein complexes for use as starting points for molecular replacement is investigated. The approach is demonstrated using homomeric coiled-coil proteins, which are excellent model systems for oligomeric systems. Despite the stereotypical fold of coiled coils, initial phase estimation can be difficult and many structures have to be solved with experimental phasing. A method was developed for automatic structure determination of homomeric coiled coils from X-ray diffraction data. In a benchmark set of 24 coiled coils, ranging from dimers to pentamers with resolutions down to 2.5 Å, 22 systems were automatically solved, 11 of which had previously been solved by experimental phasing. The generated models contained 71-103% of the residues present in the deposited structures, had the correct sequence and had free R values that deviated on average by 0.01 from those of the respective reference structures. The electron-density maps were of sufficient quality that only minor manual editing was necessary to produce final structures. The method, named CCsolve, combines methods for de novo structure prediction, initial phase estimation and automated model building into one pipeline. CCsolve is robust against errors in the initial models and can readily be modified to make use of alternative crystallographic software. The results demonstrate the feasibility of de novo phasing of protein-protein complexes, an approach that could also be employed for other small systems beyond coiled coils.

Validation of protein models by a neural network approach

Directory of Open Access Journals (Sweden)

Fantucci Piercarlo

2008-01-01

Full Text Available Abstract Background The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure refinement, which has been recently identified as one of the bottlenecks limiting the quality and usefulness of protein structure prediction. Results In this contribution, we present a computational method (Artificial Intelligence Decoys Evaluator: AIDE which is able to consistently discriminate between correct and incorrect protein models. In particular, the method is based on neural networks that use as input 15 structural parameters, which include energy, solvent accessible surface, hydrophobic contacts and secondary structure content. The results obtained with AIDE on a set of decoy structures were evaluated using statistical indicators such as Pearson correlation coefficients, Znat, fraction enrichment, as well as ROC plots. It turned out that AIDE performances are comparable and often complementary to available state-of-the-art learning-based methods. Conclusion In light of the results obtained with AIDE, as well as its comparison with available learning-based methods, it can be concluded that AIDE can be successfully used to evaluate the quality of protein structures. The use of AIDE in combination with other evaluation tools is expected to further enhance protein refinement efforts.

Generic framework for mining cellular automata models on protein-folding simulations.

Science.gov (United States)

Diaz, N; Tischer, I

2016-05-13

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

DeepQA: improving the estimation of single protein model quality with deep belief networks.

Science.gov (United States)

Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-12-05

Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

GLP-1 analogs reduce hepatocyte steatosis and improve survival by enhancing the unfolded protein response and promoting macroautophagy.

Directory of Open Access Journals (Sweden)

Shvetank Sharma

Full Text Available Nonalcoholic fatty liver disease (NAFLD is a known outcome of hepatosteatosis. Free fatty acids (FFA induce the unfolded protein response (UPR or endoplasmic reticulum (ER stress that may induce apoptosis. Recent data indicate ER stress to be a major player in the progression of fatty liver to more aggressive lesions. Autophagy on the other hand has been demonstrated to be protective against ER stress-induced cell death. We hypothesized that exendin-4 (GLP-1 analog treatment of fat loaded hepatocytes can reduce steatosis by autophagy which leads to reduced ER stress-related hepatocyte apoptosis.Primary human hepatocytes were loaded with saturated, cis- and trans-unsaturated fatty acids (palmitic, oleic and elaidic acid respectively. Steatosis, induced with all three fatty acids, was significantly resolved after exendin-4 treatment. Exendin-4 sustained levels of GRP78 expression in fat-loaded cells when compared to untreated fat-loaded cells alone. In contrast, CHOP (C/EBP homologous protein; the penultimate protein that leads to ER stress-related cell death was significantly decreased by exendin-4 in hepatocytes loaded with fatty acids. Finally, exendin-4 in fat loaded hepatocytes clearly promoted gene products associated with macroautophagy as measured by enhanced production of both Beclin-1 and LC3B-II, markers for autophagy; and visualized by transmission electron microscopy (TEM. Similar observations were made in mouse liver lysates after mice were fed with high fat high fructose diet and treated with a long acting GLP-1 receptor agonist, liraglutide.GLP-1 proteins appear to protect hepatocytes from fatty acid-related death by prohibition of a dysfunctional ER stress response; and reduce fatty acid accumulation, by activation of both macro-and chaperone-mediated autophagy. These findings provide a novel role for GLP-1 proteins in halting the progression of more aggressive lesions from underlying steatosis in humans afflicted with NAFLD.

@TOME-2: a new pipeline for comparative modeling of protein-ligand complexes.

Science.gov (United States)

Pons, Jean-Luc; Labesse, Gilles

2009-07-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein-protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein-ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/

A lock-and-key model for protein–protein interactions

OpenAIRE

Morrison, Julie L.; Breitling, Rainer; Higham, Desmond J.; Gilbert, David R.

2006-01-01

Motivation: Protein–protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism’s proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs,...

Protein buffering in model systems and in whole human saliva.

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Andreas Lamanda

Full Text Available The aim of this study was to quantify the buffer attributes (value, power, range and optimum of two model systems for whole human resting saliva, the purified proteins from whole human resting saliva and single proteins. Two model systems, the first containing amyloglucosidase and lysozyme, and the second containing amyloglucosidase and alpha-amylase, were shown to provide, in combination with hydrogencarbonate and di-hydrogenphosphate, almost identical buffer attributes as whole human resting saliva. It was further demonstrated that changes in the protein concentration as small as 0.1% may change the buffer value of a buffer solution up to 15 times. Additionally, it was shown that there was a protein concentration change in the same range (0.16% between saliva samples collected at the time periods of 13:00 and others collected at 9:00 am and 17:00. The mode of the protein expression changed between these samples corresponded to the change in basic buffer power and the change of the buffer value at pH 6.7. Finally, SDS Page and Ruthenium II tris (bathophenantroline disulfonate staining unveiled a constant protein expression in all samples except for one 50 kDa protein band. As the change in the expression pattern of that 50 kDa protein band corresponded to the change in basic buffer power and the buffer value at pH 6.7, it was reasonable to conclude that this 50 kDa protein band may contain the protein(s belonging to the protein buffer system of human saliva.

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

KAUST Repository

Oliva, Romina; Chermak, Edrisse; Cavallo, Luigi

2015-01-01

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

KAUST Repository

Oliva, Romina

2015-07-01

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

Vortex network community based reduced-order force model

Science.gov (United States)

Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya; Taira, Kunihiko

2017-11-01

We characterize the vortical wake interactions by utilizing network theory and cluster-based approaches, and develop a data-inspired unsteady force model. In the present work, the vortical interaction network is defined by nodes representing vortical elements and the edges quantified by induced velocity measures amongst the vortices. The full vorticity field is reduced to a finite number of vortical clusters based on network community detection algorithm, which serves as a basis for a skeleton network that captures the essence of the wake dynamics. We use this reduced representation of the wake to develop a data-inspired reduced-order force model that can predict unsteady fluid forces on the body. The overall formulation is demonstrated for laminar flows around canonical bluff body wake and stalled flow over an airfoil. We also show the robustness of the present network-based model against noisy data, which motivates applications towards turbulent flows and experimental measurements. Supported by the National Science Foundation (Grant 1632003).

Structural model for the interaction of a designed Ankyrin Repeat Protein with the human epidermal growth factor receptor 2.

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V Chandana Epa

Full Text Available Designed Ankyrin Repeat Proteins are a class of novel binding proteins that can be selected and evolved to bind to targets with high affinity and specificity. We are interested in the DARPin H10-2-G3, which has been evolved to bind with very high affinity to the human epidermal growth factor receptor 2 (HER2. HER2 is found to be over-expressed in 30% of breast cancers, and is the target for the FDA-approved therapeutic monoclonal antibodies trastuzumab and pertuzumab and small molecule tyrosine kinase inhibitors. Here, we use computational macromolecular docking, coupled with several interface metrics such as shape complementarity, interaction energy, and electrostatic complementarity, to model the structure of the complex between the DARPin H10-2-G3 and HER2. We analyzed the interface between the two proteins and then validated the structural model by showing that selected HER2 point mutations at the putative interface with H10-2-G3 reduce the affinity of binding up to 100-fold without affecting the binding of trastuzumab. Comparisons made with a subsequently solved X-ray crystal structure of the complex yielded a backbone atom root mean square deviation of 0.84-1.14 Ångstroms. The study presented here demonstrates the capability of the computational techniques of structural bioinformatics in generating useful structural models of protein-protein interactions.

Mechanical strength of 17,134 model proteins and cysteine slipknots.

Directory of Open Access Journals (Sweden)

Mateusz Sikora

2009-10-01

Full Text Available A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17,134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cysteine slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations.

Anomalous diffusion in neutral evolution of model proteins

Science.gov (United States)

Nelson, Erik D.; Grishin, Nick V.

2015-06-01

Protein evolution is frequently explored using minimalist polymer models, however, little attention has been given to the problem of structural drift, or diffusion. Here, we study neutral evolution of small protein motifs using an off-lattice heteropolymer model in which individual monomers interact as low-resolution amino acids. In contrast to most earlier models, both the length and folded structure of the polymers are permitted to change. To describe structural change, we compute the mean-square distance (MSD) between monomers in homologous folds separated by n neutral mutations. We find that structural change is episodic, and, averaged over lineages (for example, those extending from a single sequence), exhibits a power-law dependence on n . We show that this exponent depends on the alignment method used, and we analyze the distribution of waiting times between neutral mutations. The latter are more disperse than for models required to maintain a specific fold, but exhibit a similar power-law tail.

A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

KAUST Repository

Wong, Ka-Chun; Li, Yue; Peng, Chengbin; Wong, Hau-San

2015-01-01

Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

KAUST Repository

Wong, Ka-Chun

2015-06-11

Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

Conformational sampling in template-free protein loop structure modeling: an overview.

Science.gov (United States)

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a "mini protein folding problem" under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized.

CONFORMATIONAL SAMPLING IN TEMPLATE-FREE PROTEIN LOOP STRUCTURE MODELING: AN OVERVIEW

Directory of Open Access Journals (Sweden)

Yaohang Li

2013-02-01

Full Text Available Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a “mini protein folding problem” under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized.

Exploration of freely available web-interfaces for comparative homology modelling of microbial proteins.

Science.gov (United States)

Nema, Vijay; Pal, Sudhir Kumar

2013-01-01

This study was conducted to find the best suited freely available software for modelling of proteins by taking a few sample proteins. The proteins used were small to big in size with available crystal structures for the purpose of benchmarking. Key players like Phyre2, Swiss-Model, CPHmodels-3.0, Homer, (PS)2, (PS)(2)-V(2), Modweb were used for the comparison and model generation. Benchmarking process was done for four proteins, Icl, InhA, and KatG of Mycobacterium tuberculosis and RpoB of Thermus Thermophilus to get the most suited software. Parameters compared during analysis gave relatively better values for Phyre2 and Swiss-Model. This comparative study gave the information that Phyre2 and Swiss-Model make good models of small and large proteins as compared to other screened software. Other software was also good but is often not very efficient in providing full-length and properly folded structure.

Small heat shock proteins protect against α-synuclein-induced toxicity and aggregation

International Nuclear Information System (INIS)

Outeiro, Tiago Fleming; Klucken, Jochen; Strathearn, Katherine E.; Liu Fang; Nguyen, Paul; Rochet, Jean-Christophe; Hyman, Bradley T.; McLean, Pamela J.

2006-01-01

Protein misfolding and inclusion formation are common events in neurodegenerative diseases, such as Parkinson's disease (PD), Alzheimer's disease (AD) or Huntington's disease (HD). α-Synuclein (aSyn) is the main protein component of inclusions called Lewy bodies (LB) which are pathognomic of PD, Dementia with Lewy bodies (DLB), and other diseases collectively known as LB diseases. Heat shock proteins (HSPs) are one class of the cellular quality control system that mediate protein folding, remodeling, and even disaggregation. Here, we investigated the role of the small heat shock proteins Hsp27 and αB-crystallin, in LB diseases. We demonstrate, via quantitative PCR, that Hsp27 messenger RNA levels are ∼2-3-fold higher in DLB cases compared to control. We also show a corresponding increase in Hsp27 protein levels. Furthermore, we found that Hsp27 reduces aSyn-induced toxicity by ∼80% in a culture model while αB-crystallin reduces toxicity by ∼20%. In addition, intracellular inclusions were immunopositive for endogenous Hsp27, and overexpression of this protein reduced aSyn aggregation in a cell culture model

A reduced covariant string model for the extrinsic string

International Nuclear Information System (INIS)

Botelho, L.C.L.

1989-01-01

It is studied a reduced covariant string model for the extrinsic string by using Polyakov's path integral formalism. On the basis of this reduced model it is suggested that the extrinsic string has its critical dimension given by 13. Additionally, it is calculated in a simple way Poliakov's renormalization group law for the string rigidity coupling constants. (A.C.A.S.) [pt

The evolution of the protein synthesis system. I - A model of a primitive protein synthesis system

Science.gov (United States)

Mizutani, H.; Ponnamperuma, C.

1977-01-01

A model is developed to describe the evolution of the protein synthesis system. The model is comprised of two independent autocatalytic systems, one including one gene (A-gene) and two activated amino acid polymerases (O and A-polymerases), and the other including the addition of another gene (N-gene) and a nucleotide polymerase. Simulation results have suggested that even a small enzymic activity and polymerase specificity could lead the system to the most accurate protein synthesis, as far as permitted by transitions to systems with higher accuracy.

Interpretation of protein quantitation using the Bradford assay: comparison with two calculation models.

Science.gov (United States)

Ku, Hyung-Keun; Lim, Hyuk-Min; Oh, Kyong-Hwa; Yang, Hyo-Jin; Jeong, Ji-Seon; Kim, Sook-Kyung

2013-03-01

The Bradford assay is a simple method for protein quantitation, but variation in the results between proteins is a matter of concern. In this study, we compared and normalized quantitative values from two models for protein quantitation, where the residues in the protein that bind to anionic Coomassie Brilliant Blue G-250 comprise either Arg and Lys (Method 1, M1) or Arg, Lys, and His (Method 2, M2). Use of the M2 model yielded much more consistent quantitation values compared with use of the M1 model, which exhibited marked overestimations against protein standards. Copyright © 2012 Elsevier Inc. All rights reserved.

Reduced order for nuclear reactor model in frequency and time domain

International Nuclear Information System (INIS)

Nugroho, D.H.

1997-01-01

In control system theory, a model can be represented by frequency or time domain. In frequency domain, the model was represented by transfer function. in time domain, the model was represented by state space. for the sake of simplification in computation, it is necessary to reduce the model order. the main aim of this research is to find the best in nuclear reactor model. Model order reduction in frequency domain can be done utilizing pole-zero cancellation method; while in time domain utilizing balanced aggregation method the balanced aggregation method was developed by moore (1981). In this paper, the two kinds of method were applied to reduce a nuclear reactor model which was constructed by neutron dynamics and heat transfer equations. to validate that the model characteristics were not change when model order reduction applied, the response was utilized for full and reduced order. it was shown that the nuclear reactor order model can be reduced from order 8 to 2 order 2 is the best order for nuclear reactor model

Model for Stress-induced Protein Degradation in Lemna minor1

Science.gov (United States)

Cooke, Robert J.; Roberts, Keith; Davies, David D.

1980-01-01

Transfer of Lemna minor fronds to adverse or stress conditions produces a large increase in the rate of protein degradation. Cycloheximide partially inhibits stress-induced protein degradation and also partially inhibits the protein degradation which occurs in the absence of stress. The increased protein degradation does not appear to be due to an increase in activity of soluble proteolytic enzymes. Biochemical evidence indicates that stress, perhaps acting via hormones, affects the permeability of certain membranes, particularly the tonoplast. A general model for stress-induced protein degradation is presented in which changes in membrane properties allow vacuolar proteolytic enzymes increased access to cytoplasmic proteins. PMID:16661588

Tiaolipiwei Acupuncture Reduces Albuminuria by Alleviating Podocyte Lesions in a Rat Model of Diabetic Nephropathy

Directory of Open Access Journals (Sweden)

Zhilong Zhang

2018-01-01

Full Text Available Background. Diabetic nephropathy is a common and serious complication of diabetes and a major cause of end-stage renal disease. Tiaolipiwei acupuncture is a safe treatment approach that may be effective for lowering albuminuria in diabetic nephropathy. Yet, the exact mechanisms of this therapeutic effect are unclear. Methods. A rodent model of type 2 diabetic nephropathy (T2DN was induced by a high-fat diet combined with low-dose streptozotocin. T2DN rats were treated with Tiaolipiwei acupuncture (ACU for 4, 8, or 12 weeks. At the end of treatment, urinary and blood samples were collected for analysis. Transmission electron microscopy was used to observe morphological changes, and protein expression levels of nephrin, CD2AP, podocalyxin, and desmin were quantified in renal tissue. Results. Compared to the T2DN groups, the T2DN + ACU groups showed significant improvements in 24-hour urinary protein, serum urea, cholesterol, and triglycerides at all time points. ACU treatment also improved the density of slit diaphragms. Simultaneously, ACU promoted the renal expression of nephrin, CD2AP, and podocalyxin and decreased the expression of desmin. Conclusion. Our study suggests that Tiaolipiwei acupuncture ameliorates podocyte lesions to reduce albuminuria and prevent the progression of T2DN in a rat model.

Predicting Protein Secondary Structure with Markov Models

DEFF Research Database (Denmark)

Fischer, Paul; Larsen, Simon; Thomsen, Claus

2004-01-01

we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

A KINETIC MODEL FOR MONO-LAYER GLOBULAR PROTEIN ADSORPTION ON SOLID/LIQUID INTERFACES

Directory of Open Access Journals (Sweden)

Kamal I. M. Al-Malah

2012-12-01

Full Text Available A kinetic model was derived for globular protein adsorption. The model takes into account the three possible scenarios of a protein molecule in solution, being exposed to an interface: adsorption step from the solution to the interface; the possible desorption back into the solution; and the surface-induced unfolding or spreading of the protein unto the substrate surface. A globular protein molecule is visualized as a sphere with radius D. In addition to the general case of protein adsorption, which portrays either the surface coverage (Theta or surface concentration (� as a function of the adsorption time, special cases, like equilibrium condition, lowsurface coverage, irreversible, and Langmuirian were also presented and treated in light of the derived model. The general model was simplified for each of the subset cases. The irreversibility versus reversibility of protein adsorption was discussed. The substrate surface energetics or effects are accounted for via the proposition of the percent relative change in D/V ratio for the adsorbing protein, called (D/VPRC parameter. (D/VPRC is calculated with respect to the monolayer surface concentration of protein, where the latter is given by D/Vratio. This can be used as a landmark to protein adsorption isotherms or even kinetics. This is visualized as an indicator for solid substrate effects on the adsorbing proteins. (D/VPRC can be zero (fresh monolayer, negative (aged monolayer, or positive (multi-layer. The reference surface concentration is reported for some selected proteins.

An Efficient Null Model for Conformational Fluctuations in Proteins

DEFF Research Database (Denmark)

Harder, Tim Philipp; Borg, Mikael; Bottaro, Sandro

2012-01-01

Protein dynamics play a crucial role in function, catalytic activity, and pathogenesis. Consequently, there is great interest in computational methods that probe the conformational fluctuations of a protein. However, molecular dynamics simulations are computationally costly and therefore are often...... limited to comparatively short timescales. TYPHON is a probabilistic method to explore the conformational space of proteins under the guidance of a sophisticated probabilistic model of local structure and a given set of restraints that represent nonlocal interactions, such as hydrogen bonds or disulfide...... on conformational fluctuations that is in correspondence with experimental measurements. TYPHON provides a flexible, yet computationally efficient, method to explore possible conformational fluctuations in proteins....

Accelerating transient simulation of linear reduced order models.

Energy Technology Data Exchange (ETDEWEB)

Thornquist, Heidi K.; Mei, Ting; Keiter, Eric Richard; Bond, Brad

2011-10-01

Model order reduction (MOR) techniques have been used to facilitate the analysis of dynamical systems for many years. Although existing model reduction techniques are capable of providing huge speedups in the frequency domain analysis (i.e. AC response) of linear systems, such speedups are often not obtained when performing transient analysis on the systems, particularly when coupled with other circuit components. Reduced system size, which is the ostensible goal of MOR methods, is often insufficient to improve transient simulation speed on realistic circuit problems. It can be shown that making the correct reduced order model (ROM) implementation choices is crucial to the practical application of MOR methods. In this report we investigate methods for accelerating the simulation of circuits containing ROM blocks using the circuit simulator Xyce.

Reducing Spatial Data Complexity for Classification Models

International Nuclear Information System (INIS)

Ruta, Dymitr; Gabrys, Bogdan

2007-01-01

Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the

Reducing Spatial Data Complexity for Classification Models

Science.gov (United States)

Ruta, Dymitr; Gabrys, Bogdan

2007-11-01

Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the

Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins.

Science.gov (United States)

Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens

2016-05-01

Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes. © 2015 Wiley Periodicals, Inc.

Paxillin and embryonic PolyAdenylation Binding Protein (ePABP) engage to regulate androgen-dependent Xenopus laevis oocyte maturation - A model of kinase-dependent regulation of protein expression.

Science.gov (United States)

Miedlich, Susanne U; Taya, Manisha; Young, Melissa Rasar; Hammes, Stephen R

2017-06-15

Steroid-triggered Xenopus laevis oocyte maturation is an elegant physiologic model of nongenomic steroid signaling, as it proceeds completely independent of transcription. We previously demonstrated that androgens are the main physiologic stimulator of oocyte maturation in Xenopus oocytes, and that the adaptor protein paxillin plays a crucial role in mediating this process through a positive feedback loop in which paxillin first enhances Mos protein translation, ensued by Erk2 activation and Erk-dependent phosphorylation of paxillin on serine residues. Phosphoserine-paxillin then further augments Mos protein translation and downstream Erk2 activation, resulting in meiotic progression. We hypothesized that paxillin enhances Mos translation by interacting with embryonic PolyAdenylation Binding Protein (ePABP) on polyadenylated Mos mRNA. Knockdown of ePABP phenocopied paxillin knockdown, with reduced Mos protein expression, Erk2 and Cdk1 activation, as well as oocyte maturation. In both Xenopus oocytes and mammalian cells (HEK-293), paxillin and ePABP constitutively interacted. Testosterone (Xenopus) or EGF (HEK-293) augmented ePABP-paxillin binding, as well as ePABP binding to Mos mRNA (Xenopus), in an Erk-dependent fashion. Thus, ePABP and paxillin work together in an Erk-dependent fashion to enhance Mos protein translation and promote oocyte maturation. Copyright © 2017 Elsevier B.V. All rights reserved.

Bitter taste masking of enzyme-treated soy protein in water and bread.

Science.gov (United States)

Bertelsen, Anne S; Laursen, Anne; Knudsen, Tine A; Møller, Stine; Kidmose, Ulla

2018-08-01

Bioactive protein hydrolysates are often very bitter. To overcome this challenge, xylitol, sucrose, α-cyclodextrin, maltodextrin and combinations of these were tested systematically as bitter-masking agents of an enzyme-treated soy protein in an aqueous model and in a bread model. Sensory descriptive analysis was used to reveal the bitter-masking effect of the taste-masking blends on the enzyme-treated soy protein. In water, xylitol, sucrose and maltodextrin reduced bitterness significantly, whereas α-cyclodextrin did not. No significant difference was observed in bitterness reduction between xylitol and sucrose. Both reduced bitterness significantly more than maltodextrin. No interactions between the taste-masking agents affecting bitterness reduction were found. Clearer bitter-masking effects were seen in the aqueous model compared with the bread model. The bitter-masking effects of α-cyclodextrin and maltodextrin were similar between water and bread. The effect of xylitol and sucrose on bitterness suppression varied between the systems. In water, bitterness was negatively correlated with sweetness. In bread, bitterness was negatively correlated with freshness, and maltodextrin significantly reduced bitterness of the enzyme-treated soy protein and increased freshness. Bitter-masking effects were generally more discernible in the aqueous model compared with the bread model. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Coarse Grained Molecular Dynamics Simulations of Transmembrane Protein-Lipid Systems

Directory of Open Access Journals (Sweden)

Peter Spijker

2010-06-01

Full Text Available Many biological cellular processes occur at the micro- or millisecond time scale. With traditional all-atom molecular modeling techniques it is difficult to investigate the dynamics of long time scales or large systems, such as protein aggregation or activation. Coarse graining (CG can be used to reduce the number of degrees of freedom in such a system, and reduce the computational complexity. In this paper the first version of a coarse grained model for transmembrane proteins is presented. This model differs from other coarse grained protein models due to the introduction of a novel angle potential as well as a hydrogen bonding potential. These new potentials are used to stabilize the backbone. The model has been validated by investigating the adaptation of the hydrophobic mismatch induced by the insertion of WALP-peptides into a lipid membrane, showing that the first step in the adaptation is an increase in the membrane thickness, followed by a tilting of the peptide.

Sensitivity study of reduced models of the activated sludge process ...

African Journals Online (AJOL)

2009-08-07

Aug 7, 2009 ... Sensitivity study of reduced models of the activated sludge process, for the purposes of parameter estimation and process optimisation: Benchmark process with ASM1 and UCT reduced biological models. S du Plessis and R Tzoneva*. Department of Electrical Engineering, Cape Peninsula University of ...

The use of recombinant nAG protein In spinal cord crush injury in a rat model

International Nuclear Information System (INIS)

Al-Qattan, M.M.; Al-Motairi, M.; Ah-Habib, A.

2017-01-01

Objective: To evaluate the therapeutic properties of nAG protein during the recovery following acute spinal cord injuries in the rat. Study Design: An experimental study. Place and Duration of Study: King Saud University, Riyadh, Saudi Arabia, from September 2014 to September 2015. Methodology: Eight rats were studied (4 control rats and 4 experimental rats; and hence 50% were controls and 50% were experimental). All rats were subjected to an acute spinal cord injury using the aneurysmal clip injury model. Immediately after the injury, a single intra-dural injection of either normal saline (in the control group) or the nAG protein (in the experimental group) was done. Assessment of both groups was done over a 6-week period with regard to weight maintenance, motor recovery scores, MRI and histopathology of the injury site. Results: Weight maintenance was seen in the experimental and not in the control rats. Starting at 3 weeks after injury, the motor recovery was significantly (p<0.05) better in the experimental group. MRI assessment at 6 weeks showed better maintenance of cord continuity and less fluid accumulation at the injury site in the nAG-treated group. Just proximal to the injury site, there was less gliosis in the experimental group compared to the control group. At the crush injury site, there was less tissue architecture distortion, less vacuole formation, and less granulation tissue formation in the experimental group. Conclusion: The local injection nAG protein enhances neuro-restoration, reduces gliosis, and reduces vacuole/ granulation tissue formation following acute spinal cord crush injury in the rat aneurysmal clip animal model. (author)

Overexpression of retinal degeneration slow (RDS protein adversely affects rods in the rd7 model of enhanced S-cone syndrome.

Directory of Open Access Journals (Sweden)

Dibyendu Chakraborty

Full Text Available The nuclear receptor NR2E3 promotes expression of rod photoreceptor genes while repressing cone genes. Mice lacking NR2E3 (Nr2e3(rd7/rd7 referred to here as rd7 are a model for enhanced S-cone syndrome, a disease associated with increased sensitivity to blue light and night blindness. Rd7 retinas have reduced levels of the outer segment (OS structural protein retinal degeneration slow (RDS. We test the hypothesis that increasing RDS levels would improve the Rd7 phenotype. Transgenic mice over-expressing normal mouse peripherin/RDS (NMP in rods and cones were crossed onto the rd7 background. Disease phenotypes were assessed in NMP/rd7 eyes and compared to wild-type (WT and rd7 eyes at postnatal day 30. NMP/rd7 retinas expressed total RDS (transgenic and endogenous message at WT levels, and NMP protein was correctly localized to the OS. NMP/rd7 retinas have shorter OSs compared to rd7 and WT and significantly reduced number of rosettes. NMP/rd7 mice also exhibited significant deficits in scotopic ERG amplitudes compared to rd7 while photopic amplitudes remained unaffected. Protein levels of rhodopsin, RDS, and the RDS homologue ROM-1 were significantly reduced in the NMP/rd7 retinas compared to rd7. We show that correcting the levels of RDS gene expression does not improve the phenotype of the rd7 suggesting that RDS deficiency is not responsible for the defect in this model. We suggest that the specific rod defect in the NMP/rd7 is likely associated with ongoing problems in the rd7 that are related to the expression of cone genes in rod cells, a characteristic of the model.

HIV-specific probabilistic models of protein evolution.

Directory of Open Access Journals (Sweden)

David C Nickle

2007-06-01

Full Text Available Comparative sequence analyses, including such fundamental bioinformatics techniques as similarity searching, sequence alignment and phylogenetic inference, have become a mainstay for researchers studying type 1 Human Immunodeficiency Virus (HIV-1 genome structure and evolution. Implicit in comparative analyses is an underlying model of evolution, and the chosen model can significantly affect the results. In general, evolutionary models describe the probabilities of replacing one amino acid character with another over a period of time. Most widely used evolutionary models for protein sequences have been derived from curated alignments of hundreds of proteins, usually based on mammalian genomes. It is unclear to what extent these empirical models are generalizable to a very different organism, such as HIV-1-the most extensively sequenced organism in existence. We developed a maximum likelihood model fitting procedure to a collection of HIV-1 alignments sampled from different viral genes, and inferred two empirical substitution models, suitable for describing between-and within-host evolution. Our procedure pools the information from multiple sequence alignments, and provided software implementation can be run efficiently in parallel on a computer cluster. We describe how the inferred substitution models can be used to generate scoring matrices suitable for alignment and similarity searches. Our models had a consistently superior fit relative to the best existing models and to parameter-rich data-driven models when benchmarked on independent HIV-1 alignments, demonstrating evolutionary biases in amino-acid substitution that are unique to HIV, and that are not captured by the existing models. The scoring matrices derived from the models showed a marked difference from common amino-acid scoring matrices. The use of an appropriate evolutionary model recovered a known viral transmission history, whereas a poorly chosen model introduced phylogenetic

Bed rest reduces metabolic protein content and abolishes exercise-induced mRNA responses in human skeletal muscle

DEFF Research Database (Denmark)

Jørgensen, Stine Ringholm; Biensø, Rasmus S; Kiilerich, Kristian

2011-01-01

Background: The aim was to test the hypothesis that one week of bed rest will reduce mitochondrial number and expression and activity of oxidative proteins in human skeletal muscle, but that exercise-induced intracellular signaling as well as mRNA and microRNA (miR) responses are maintained after......-legged knee extensor exercise performed before and after bed rest. Results: Maximal oxygen uptake decreased 5% and exercise endurance decreased non-significantly 25% by bed rest. Bed rest reduced skeletal muscle mitochondrial DNA/nuclear DNA content 15%, hexokinase II and sirtuin 1 protein content ~45%, 3...... bed rest. Research Design and Methods: Twelve young, healthy, male subjects completed 7 days of bed rest with vastus lateralis muscle biopsies taken before and after bed rest. In addition, muscle biopsies were obtained from 6 of the subjects prior to, immediately after and 3h after 45 min one...

Plant G-Proteins Come of Age: Breaking the Bond with Animal Models.

Science.gov (United States)

Trusov, Yuri; Botella, José R

2016-01-01

G-proteins are universal signal transducers mediating many cellular responses. Plant G-protein signaling has been modeled on the well-established animal paradigm but accumulated experimental evidence indicates that G-protein-dependent signaling in plants has taken a very different evolutionary path. Here we review the differences between plant and animal G-proteins reported over past two decades. Most importantly, while in animal systems the G-protein signaling cycle is activated by seven transmembrane-spanning G-protein coupled receptors, the existence of these type of receptors in plants is highly controversial. Instead plant G-proteins have been proven to be functionally associated with atypical receptors such as the Arabidopsis RGS1 and a number of receptor-like kinases. We propose that, instead of the GTP/GDP cycle used in animals, plant G-proteins are activated/de-activated by phosphorylation/de-phosphorylation. We discuss the need of a fresh new look at these signaling molecules and provide a hypothetical model that departs from the accepted animal paradigm.

A Reduced Wind Power Grid Model for Research and Education

DEFF Research Database (Denmark)

Akhmatov, Vladislav; Lund, Torsten; Hansen, Anca Daniela

2007-01-01

A reduced grid model of a transmission system with a number of central power plants, consumption centers, local wind turbines and a large offshore wind farm is developed and implemented in the simulation tool PowerFactory (DIgSILENT). The reduced grid model is given by Energinet.dk, Transmission...

Reduced order modeling of flashing two-phase jets

Energy Technology Data Exchange (ETDEWEB)

Gurecky, William, E-mail: william.gurecky@utexas.edu; Schneider, Erich, E-mail: eschneider@mail.utexas.edu; Ballew, Davis, E-mail: davisballew@utexas.edu

2015-12-01

Highlights: • Accident simulation requires ability to quickly predict two-phase flashing jet's damage potential. • A reduced order modeling methodology informed by experimental or computational data is described. • Zone of influence volumes are calculated for jets of various upstream thermodynamic conditions. - Abstract: In the event of a Loss of Coolant Accident (LOCA) in a pressurized water reactor, the escaping coolant produces a highly energetic flashing jet with the potential to damage surrounding structures. In LOCA analysis, the goal is often to evaluate many break scenarios in a Monte Carlo style simulation to evaluate the resilience of a reactor design. Therefore, in order to quickly predict the damage potential of flashing jets, it is of interest to develop a reduced order model that relates the damage potential of a jet to the pressure and temperature upstream of the break and the distance from the break to a given object upon which the jet is impinging. This work presents framework for producing a Reduced Order Model (ROM) that may be informed by measured data, Computational Fluid Dynamics (CFD) simulations, or a combination of both. The model is constructed by performing regression analysis on the pressure field data, allowing the impingement pressure to be quickly reconstructed for any given upstream thermodynamic condition within the range of input data. The model is applicable to both free and fully impinging two-phase flashing jets.

Gene ontology based transfer learning for protein subcellular localization

Directory of Open Access Journals (Sweden)

Zhou Shuigeng

2011-02-01

Full Text Available Abstract Background Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology. Results In this paper, we propose a Gene Ontology Based Transfer Learning Model (GO-TLM for large-scale protein subcellular localization. The model transfers the signature-based homologous GO terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false GO terms that are resulted from evolutionary divergence. We derive three GO kernels from the three aspects of gene ontology to measure the GO similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for

Influence of extracellular matrix proteins on human keratinocyte attachment, proliferation and transfer to a dermal wound model.

Science.gov (United States)

Dawson, R A; Goberdhan, N J; Freedlander, E; MacNeil, S

1996-03-01

The aim of this study was to investigate whether prior culture of cells on ECM proteins might positively influence the performance of keratinocytes when cells are transferred to a dermal in vitro wound bed model. Keratinocytes were cultured using a method for producing cultured epithelial autografts for severely burned patients (essentially using Green's medium, a mitogen-rich medium containing fetal calf serum, cholera toxin, EGF, insulin, transferrin and triiodothyronine). Cells were cultured either on irradiated 3T3 fibroblasts (as in the standard Rheinwald and Green technique) or, alternatively, on collagen I, collagen IV, matrigel, RGD, vitronectin or fibronectin. Under these conditions matrigel, collagen I and IV enhanced initial attachment, RGD, vitronectin, fibronectin and irradiated 3T3 fibroblasts did not. Proliferation of cells was positively influenced by matrigel, collagen I and IV and irradiated 3T3 fibroblasts; of these, however, only matrigel and 3T3 fibroblasts had sustained significant effects on keratinocyte proliferation over 4 days. Cells on fibronectin showed significantly reduced proliferation. An acellular non-viable dermis was then used to mimic the homograft allodermis onto which cultured epithelial autograft sheets are grafted clinically and cells cultured on the various ECM proteins for 96 h were transferred to this in vitro wound model. None of the substrates enhanced keratinocyte performance on this model. It was concluded that under these conditions some ECM proteins can significantly affect keratinocyte attachment and, to a lesser extent, proliferation but that the culture of keratinocytes on these ECM proteins does not appear to confer any lasting benefit to the attachment of these keratinocytes to an in vitro wound-bed model.

Inhibition of coagulation and inflammation by activated protein C or antithrombin reduces intestinal ischemia/reperfusion injury in rats

NARCIS (Netherlands)

Schoots, Ivo G.; Levi, Marcel; van Vliet, Arlène K.; Maas, Adrie M.; Roossink, E. H. Paulina; van Gulik, Thomas M.

2004-01-01

Objective: To examine whether administration of activated protein C or antithrombin reduces local splanchnic derangement of coagulation and inflammation and attenuates intestinal dysfunction and injury following intestinal ischemia/reperfusion. Design: Randomized prospective animal study. Setting:

Intrinsically disordered proteins as molecular shields†

Science.gov (United States)

Chakrabortee, Sohini; Tripathi, Rashmi; Watson, Matthew; Kaminski Schierle, Gabriele S.; Kurniawan, Davy P.; Kaminski, Clemens F.; Wise, Michael J.; Tunnacliffe, Alan

2017-01-01

The broad family of LEA proteins are intrinsically disordered proteins (IDPs) with several potential roles in desiccation tolerance, or anhydrobiosis, one of which is to limit desiccation-induced aggregation of cellular proteins. We show here that this activity, termed molecular shield function, is distinct from that of a classical molecular chaperone, such as HSP70 – while HSP70 reduces aggregation of citrate synthase (CS) on heating, two LEA proteins, a nematode group 3 protein, AavLEA1, and a plant group 1 protein, Em, do not; conversely, the LEA proteins reduce CS aggregation on desiccation, while HSP70 lacks this ability. There are also differences in interaction with client proteins – HSP70 can be co-immunoprecipitated with a polyglutamine-containing client, consistent with tight complex formation, whereas the LEA proteins can not, although a loose interaction is observed by Förster resonance energy transfer. In a further exploration of molecular shield function, we demonstrate that synthetic polysaccharides, like LEA proteins, are able to reduce desiccation-induced aggregation of a water-soluble proteome, consistent with a steric interference model of anti-aggregation activity. If molecular shields operate by reducing intermolecular cohesion rates, they should not protect against intramolecular protein damage. This was tested using the monomeric red fluorescent protein, mCherry, which does not undergo aggregation on drying, but the absorbance and emission spectra of its intrinsic fluorophore are dramatically reduced, indicative of intramolecular conformational changes. As expected, these changes are not prevented by AavLEA1, except for a slight protection at high molar ratios, and an AavLEA1-mCherry fusion protein is damaged to the same extent as mCherry alone. A recent hypothesis proposed that proteomes from desiccation-tolerant species contain a higher degree of disorder than intolerant examples, and that this might provide greater intrinsic stability

Intrinsically disordered proteins as molecular shields.

Science.gov (United States)

Chakrabortee, Sohini; Tripathi, Rashmi; Watson, Matthew; Schierle, Gabriele S Kaminski; Kurniawan, Davy P; Kaminski, Clemens F; Wise, Michael J; Tunnacliffe, Alan

2012-01-01

The broad family of LEA proteins are intrinsically disordered proteins (IDPs) with several potential roles in desiccation tolerance, or anhydrobiosis, one of which is to limit desiccation-induced aggregation of cellular proteins. We show here that this activity, termed molecular shield function, is distinct from that of a classical molecular chaperone, such as HSP70 - while HSP70 reduces aggregation of citrate synthase (CS) on heating, two LEA proteins, a nematode group 3 protein, AavLEA1, and a plant group 1 protein, Em, do not; conversely, the LEA proteins reduce CS aggregation on desiccation, while HSP70 lacks this ability. There are also differences in interaction with client proteins - HSP70 can be co-immunoprecipitated with a polyglutamine-containing client, consistent with tight complex formation, whereas the LEA proteins can not, although a loose interaction is observed by Förster resonance energy transfer. In a further exploration of molecular shield function, we demonstrate that synthetic polysaccharides, like LEA proteins, are able to reduce desiccation-induced aggregation of a water-soluble proteome, consistent with a steric interference model of anti-aggregation activity. If molecular shields operate by reducing intermolecular cohesion rates, they should not protect against intramolecular protein damage. This was tested using the monomeric red fluorescent protein, mCherry, which does not undergo aggregation on drying, but the absorbance and emission spectra of its intrinsic fluorophore are dramatically reduced, indicative of intramolecular conformational changes. As expected, these changes are not prevented by AavLEA1, except for a slight protection at high molar ratios, and an AavLEA1-mCherry fusion protein is damaged to the same extent as mCherry alone. A recent hypothesis proposed that proteomes from desiccation-tolerant species contain a higher degree of disorder than intolerant examples, and that this might provide greater intrinsic stability

Mannan-binding protein forms complexes with alpha-2-macroglobulin. A protein model for the interaction

DEFF Research Database (Denmark)

Storgaard, P; Holm Nielsen, E; Skriver, E

1995-01-01

We report that alpha-2-macroglobulin (alpha 2M) can form complexes with a high molecular weight porcine mannan-binding protein (pMBP-28). The alpha 2M/pMBP-28 complexes was isolated by PEG-precipitation and affinity chromatography on mannan-Sepharose, protein A-Sepharose and anti-IgM Sepharose......-PAGE, which reacted with antibodies against alpha 2M and pMBP-28, respectively, in Western blotting. Furthermore, alpha 2M/pMBP-28 complexes were demonstrated by electron microscopy. Fractionation of pMBP-containing D-mannose eluate from mannan-Sepharose on Superose 6 showed two protein peaks which reacted...... with anti-C1 s antibodies in ELISA, one of about 650-800 kDa, which in addition contained pMBP-28 and anti-alpha 2M reactive material, the other with an M(r) of 100-150 kDa. The latter peak revealed rhomboid molecules (7 x 15 nm) in the electron microscope and a 67 kDa band in SDS-PAGE under reducing...

Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes: The Hemoglobin Case

Directory of Open Access Journals (Sweden)

Guang Hu

2017-01-01

Full Text Available The overall topology and interfacial interactions play key roles in understanding structural and functional principles of protein complexes. Elastic Network Model (ENM and Protein Contact Network (PCN are two widely used methods for high throughput investigation of structures and interactions within protein complexes. In this work, the comparative analysis of ENM and PCN relative to hemoglobin (Hb was taken as case study. We examine four types of structural and dynamical paradigms, namely, conformational change between different states of Hbs, modular analysis, allosteric mechanisms studies, and interface characterization of an Hb. The comparative study shows that ENM has an advantage in studying dynamical properties and protein-protein interfaces, while PCN is better for describing protein structures quantitatively both from local and from global levels. We suggest that the integration of ENM and PCN would give a potential but powerful tool in structural systems biology.

Refinement of protein termini in template-based modeling using conformational space annealing.

Science.gov (United States)

Park, Hahnbeom; Ko, Junsu; Joo, Keehyoung; Lee, Julian; Seok, Chaok; Lee, Jooyoung

2011-09-01

The rapid increase in the number of experimentally determined protein structures in recent years enables us to obtain more reliable protein tertiary structure models than ever by template-based modeling. However, refinement of template-based models beyond the limit available from the best templates is still needed for understanding protein function in atomic detail. In this work, we develop a new method for protein terminus modeling that can be applied to refinement of models with unreliable terminus structures. The energy function for terminus modeling consists of both physics-based and knowledge-based potential terms with carefully optimized relative weights. Effective sampling of both the framework and terminus is performed using the conformational space annealing technique. This method has been tested on a set of termini derived from a nonredundant structure database and two sets of termini from the CASP8 targets. The performance of the terminus modeling method is significantly improved over our previous method that does not employ terminus refinement. It is also comparable or superior to the best server methods tested in CASP8. The success of the current approach suggests that similar strategy may be applied to other types of refinement problems such as loop modeling or secondary structure rearrangement. Copyright © 2011 Wiley-Liss, Inc.

Model systems for understanding absorption tuning by opsin proteins

DEFF Research Database (Denmark)

Nielsen, Mogens Brøndsted

2009-01-01

This tutorial review reports on model systems that have been synthesised and investigated for elucidating how opsin proteins tune the absorption of the protonated retinal Schiff base chromophore. In particular, the importance of the counteranion is highlighted. In addition, the review advocates...... is avoided, and it becomes clear that opsin proteins induce blueshifts in the chromophore absorption rather than redshifts....

Nonlinear thermal reduced model for Microwave Circuit Analysis

OpenAIRE

Chang, Christophe; Sommet, Raphael; Quéré, Raymond; Dueme, Ph.

2004-01-01

With the constant increase of transistor power density, electro thermal modeling is becoming a necessity for accurate prediction of device electrical performances. For this reason, this paper deals with a methodology to obtain a precise nonlinear thermal model based on Model Order Reduction of a three dimensional thermal Finite Element (FE) description. This reduced thermal model is based on the Ritz vector approach which ensure the steady state solution in every case. An equi...

Accurate protein structure modeling using sparse NMR data and homologous structure information.

Science.gov (United States)

Thompson, James M; Sgourakis, Nikolaos G; Liu, Gaohua; Rossi, Paolo; Tang, Yuefeng; Mills, Jeffrey L; Szyperski, Thomas; Montelione, Gaetano T; Baker, David

2012-06-19

While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.

Saccharomyces boulardii CNCM I-745 supplementation reduces gastrointestinal dysfunction in an animal model of IBS.

Directory of Open Access Journals (Sweden)

Paola Brun

Full Text Available We evaluated the effect of Saccharomyces boulardii CNCM I-745 on intestinal neuromuscular anomalies in an IBS-type mouse model of gastrointestinal motor dysfunctions elicited by Herpes Simplex Virus type 1 (HSV-1 exposure.Mice were inoculated intranasally with HSV-1 (102 PFU or vehicle at time 0 and 4 weeks later by the intragastric (IG route (108 PFU. Six weeks after IG inoculum, mice were randomly allocated to receive oral gavage with either S. boulardii (107 CFU/day or vehicle. After 4 weeks the following were determined: a intestinal motility using fluorescein-isothiocyanate dextran distribution in the gut, fecal pellet expulsion, stool water content, and distal colonic transit of glass beads; b integrity of the enteric nervous system (ENS by immunohistochemistry on ileal whole-mount preparations and western blot of protein lysates from ileal longitudinal muscle and myenteric plexus; c isometric muscle tension with electric field and pharmacological (carbachol stimulation of ileal segments; and d intestinal inflammation by levels of tumor necrosis factor α, interleukin(IL-1β, IL-10 and IL-4.S. boulardii CNCM I-745 improved HSV-1 induced intestinal dysmotility and alteration of intestinal transit observed ten weeks after IG inoculum of the virus. Also, the probiotic yeast ameliorated the structural alterations of the ENS induced by HSV-1 (i.e., reduced peripherin immunoreactivity and expression, increased glial S100β protein immunoreactivity and neuronal nitric oxide synthase level, reduced substance P-positive fibers. Moreover, S. boulardii CNCM I-745 diminished the production of HSV-1 associated pro-inflammatory cytokines in the myenteric plexus and increased levels of anti-inflammatory interleukins.S. boulardii CNCM I-745 ameliorated gastrointestinal neuromuscular anomalies in a mouse model of gut dysfunctions typically observed with irritable bowel syndrome.

Saccharomyces boulardii CNCM I-745 supplementation reduces gastrointestinal dysfunction in an animal model of IBS.

Science.gov (United States)

Brun, Paola; Scarpa, Melania; Marchiori, Chiara; Sarasin, Gloria; Caputi, Valentina; Porzionato, Andrea; Giron, Maria Cecilia; Palù, Giorgio; Castagliuolo, Ignazio

2017-01-01

We evaluated the effect of Saccharomyces boulardii CNCM I-745 on intestinal neuromuscular anomalies in an IBS-type mouse model of gastrointestinal motor dysfunctions elicited by Herpes Simplex Virus type 1 (HSV-1) exposure. Mice were inoculated intranasally with HSV-1 (102 PFU) or vehicle at time 0 and 4 weeks later by the intragastric (IG) route (108 PFU). Six weeks after IG inoculum, mice were randomly allocated to receive oral gavage with either S. boulardii (107 CFU/day) or vehicle. After 4 weeks the following were determined: a) intestinal motility using fluorescein-isothiocyanate dextran distribution in the gut, fecal pellet expulsion, stool water content, and distal colonic transit of glass beads; b) integrity of the enteric nervous system (ENS) by immunohistochemistry on ileal whole-mount preparations and western blot of protein lysates from ileal longitudinal muscle and myenteric plexus; c) isometric muscle tension with electric field and pharmacological (carbachol) stimulation of ileal segments; and d) intestinal inflammation by levels of tumor necrosis factor α, interleukin(IL)-1β, IL-10 and IL-4. S. boulardii CNCM I-745 improved HSV-1 induced intestinal dysmotility and alteration of intestinal transit observed ten weeks after IG inoculum of the virus. Also, the probiotic yeast ameliorated the structural alterations of the ENS induced by HSV-1 (i.e., reduced peripherin immunoreactivity and expression, increased glial S100β protein immunoreactivity and neuronal nitric oxide synthase level, reduced substance P-positive fibers). Moreover, S. boulardii CNCM I-745 diminished the production of HSV-1 associated pro-inflammatory cytokines in the myenteric plexus and increased levels of anti-inflammatory interleukins. S. boulardii CNCM I-745 ameliorated gastrointestinal neuromuscular anomalies in a mouse model of gut dysfunctions typically observed with irritable bowel syndrome.

Reduced Order Models for Dynamic Behavior of Elastomer Damping Devices

Science.gov (United States)

Morin, B.; Legay, A.; Deü, J.-F.

2016-09-01

In the context of passive damping, various mechanical systems from the space industry use elastomer components (shock absorbers, silent blocks, flexible joints...). The material of these devices has frequency, temperature and amplitude dependent characteristics. The associated numerical models, using viscoelastic and hyperelastic constitutive behaviour, may become computationally too expensive during a design process. The aim of this work is to propose efficient reduced viscoelastic models of rubber devices. The first step is to choose an accurate material model that represent the viscoelasticity. The second step is to reduce the rubber device finite element model to a super-element that keeps the frequency dependence. This reduced model is first built by taking into account the fact that the device's interfaces are much more rigid than the rubber core. To make use of this difference, kinematical constraints enforce the rigid body motion of these interfaces reducing the rubber device model to twelve dofs only on the interfaces (three rotations and three translations per face). Then, the superelement is built by using a component mode synthesis method. As an application, the dynamic behavior of a structure supported by four hourglass shaped rubber devices under harmonic loads is analysed to show the efficiency of the proposed approach.

Construction of a biodynamic model for Cry protein production studies.

Science.gov (United States)

Navarro-Mtz, Ana Karin; Pérez-Guevara, Fermín

2014-12-01

Mathematical models have been used from growth kinetic simulation to gen regulatory networks prediction for B. thuringiensis culture. However, this culture is a time dependent dynamic process where cells physiology suffers several changes depending on the changes in the cell environment. Therefore, through its culture, B. thuringiensis presents three phases related with the predominance of three major metabolic pathways: vegetative growth (Embded-Meyerhof-Parnas pathway), transition (γ-aminobutiric cycle) and sporulation (tricarboxylic acid cycle). There is not available a mathematical model that relates the different stages of cultivation with the metabolic pathway active on each one of them. Therefore, in the present study, and based on published data, a biodynamic model was generated to describe the dynamic of the three different phases based on their major metabolic pathways. The biodynamic model is used to study the interrelation between the different culture phases and their relationship with the Cry protein production. The model consists of three interconnected modules where each module represents one culture phase and its principal metabolic pathway. For model validation four new fermentations were done showing that the model constructed describes reasonably well the dynamic of the three phases. The main results of this model imply that poly-β-hydroxybutyrate is crucial for endospore and Cry protein production. According to the yields of dipicolinic acid and Cry from poly-β-hydroxybutyrate, calculated with the model, the endospore and Cry protein production are not just simultaneous and parallel processes they are also competitive processes.

Skeletal muscle neuronal nitric oxide synthase micro protein is reduced in people with impaired glucose homeostasis and is not normalized by exercise training.

Science.gov (United States)

Bradley, Scott J; Kingwell, Bronwyn A; Canny, Benedict J; McConell, Glenn K

2007-10-01

Skeletal muscle inducible nitric oxide synthase (NOS) protein is greatly elevated in people with type 2 diabetes mellitus, whereas endothelial NOS is at normal levels. Diabetic rat studies suggest that skeletal muscle neuronal NOS (nNOS) micro protein expression may be reduced in human insulin resistance. The aim of this study was to determine whether skeletal muscle nNOSmicro protein expression is reduced in people with impaired glucose homeostasis and whether exercise training increases nNOSmicro protein expression in these individuals because exercise training increases skeletal muscle nNOSmicro protein in rats. Seven people with type 2 diabetes mellitus or prediabetes (impaired fasting glucose and/or impaired glucose tolerance) and 7 matched (sex, age, fitness, body mass index, blood pressure, lipid profile) healthy controls aged 36 to 60 years participated in this study. Vastus lateralis muscle biopsies for nNOSmicro protein determination were obtained, aerobic fitness was measured (peak pulmonary oxygen uptake [Vo(2) peak]), and glucose tolerance and insulin homeostasis were assessed before and after 1 and 4 weeks of cycling exercise training (60% Vo(2) peak, 50 minutes x 5 d wk(-1)). Skeletal muscle nNOSmicro protein was significantly lower (by 32%) in subjects with type 2 diabetes mellitus or prediabetes compared with that in controls before training (17.7 +/- 1.2 vs 26.2 +/- 3.4 arbitrary units, P glucose homeostasis have reduced skeletal muscle nNOSmicro protein content. However, because exercise training improves insulin sensitivity without influencing skeletal muscle nNOSmicro protein expression, it seems that changes in skeletal muscle nNOSmicro protein are not central to the control of insulin sensitivity in humans and therefore may be a consequence rather than a cause of diabetes.

Inhibition of peptidyl-arginine deiminases reverses protein-hypercitrullination and disease in mouse models of multiple sclerosis

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Mario A. Moscarello

2013-03-01

Multiple sclerosis (MS is the most common CNS-demyelinating disease of humans, showing clinical and pathological heterogeneity and a general resistance to therapy. We first discovered that abnormal myelin hypercitrullination, even in normal-appearing white matter, by peptidylarginine deiminases (PADs correlates strongly with disease severity and might have an important role in MS progression. Hypercitrullination is known to promote focal demyelination through reduced myelin compaction. Here we report that 2-chloroacetamidine (2CA, a small-molecule, PAD active-site inhibitor, dramatically attenuates disease at any stage in independent neurodegenerative as well as autoimmune MS mouse models. 2CA reduced PAD activity and protein citrullination to pre-disease status. In the autoimmune models, disease induction uniformly induced spontaneous hypercitrullination with citrulline+ epitopes targeted frequently. 2CA rapidly suppressed T cell autoreactivity, clearing brain and spinal cord infiltrates, through selective removal of newly activated T cells. 2CA essentially prevented disease when administered before disease onset or before autoimmune induction, making hypercitrullination, and specifically PAD enzymes, a therapeutic target in MS models and thus possibly in MS.

Reduced myelin basic protein and actin-related gene expression in visual cortex in schizophrenia.

Science.gov (United States)

Matthews, Paul R; Eastwood, Sharon L; Harrison, Paul J

2012-01-01

Most brain gene expression studies of schizophrenia have been conducted in the frontal cortex or hippocampus. The extent to which alterations occur in other cortical regions is not well established. We investigated primary visual cortex (Brodmann area 17) from the Stanley Neuropathology Consortium collection of tissue from 60 subjects with schizophrenia, bipolar disorder, major depression, or controls. We first carried out a preliminary array screen of pooled RNA, and then used RT-PCR to quantify five mRNAs which the array identified as differentially expressed in schizophrenia (myelin basic protein [MBP], myelin-oligodendrocyte glycoprotein [MOG], β-actin [ACTB], thymosin β-10 [TB10], and superior cervical ganglion-10 [SCG10]). Reduced mRNA levels were confirmed by RT-PCR for MBP, ACTB and TB10. The MBP reduction was limited to transcripts containing exon 2. ACTB and TB10 mRNAs were also decreased in bipolar disorder. None of the transcripts were altered in subjects with major depression. Reduced MBP mRNA in schizophrenia replicates findings in other brain regions and is consistent with oligodendrocyte involvement in the disorder. The decreases in expression of ACTB, and the actin-binding protein gene TB10, suggest changes in cytoskeletal organisation. The findings confirm that the primary visual cortex shows molecular alterations in schizophrenia and extend the evidence for a widespread, rather than focal, cortical pathophysiology.

Spatial cognitive deficits in an animal model of Wernicke-Korsakoff syndrome are related to changes in thalamic VDAC protein concentrations.

Science.gov (United States)

Bueno, K O; de Souza Resende, L; Ribeiro, A F; Dos Santos, D M; Gonçalves, E C; Vigil, F A B; de Oliveira Silva, I F; Ferreira, L F; de Castro Pimenta, A M; Ribeiro, A M

2015-05-21

Proteomic profiles of the thalamus and the correlation between the rats' performance on a spatial learning task and differential protein expression were assessed in the thiamine deficiency (TD) rat model of Wernicke-Korsakoff syndrome. Two-dimensional gel-electrophoresis detected 320 spots and a significant increase or decrease in seven proteins. Four proteins were correlated to rat behavioral performance in the Morris Water Maze. One of the four proteins was identified by mass spectrometry as Voltage-Dependent Anion Channels (VDACs). The association of VDAC is evident in trials in which the rats' performance was worst, in which the VDAC protein was reduced, as confirmed by Western blot. No difference was observed on the mRNA of Vdac genes, indicating that the decreased VDAC expression may be related to a post-transcriptional process. The results show that TD neurodegeneration involves changes in thalamic proteins and suggest that VDAC protein activity might play an important role in an initial stage of the spatial learning process. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

A coevolution analysis for identifying protein-protein interactions by Fourier transform

Science.gov (United States)

Yin, Changchuan; Yau, Stephen S. -T.

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI). PMID:28430779

A coevolution analysis for identifying protein-protein interactions by Fourier transform.

Directory of Open Access Journals (Sweden)

Changchuan Yin

Full Text Available Protein-protein interactions (PPIs play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA; however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40. The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI.

Modeling structure of G protein-coupled receptors in huan genome

KAUST Repository

Zhang, Yang

2016-01-26

G protein-coupled receptors (or GPCRs) are integral transmembrane proteins responsible to various cellular signal transductions. Human GPCR proteins are encoded by 5% of human genes but account for the targets of 40% of the FDA approved drugs. Due to difficulties in crystallization, experimental structure determination remains extremely difficult for human GPCRs, which have been a major barrier in modern structure-based drug discovery. We proposed a new hybrid protocol, GPCR-I-TASSER, to construct GPCR structure models by integrating experimental mutagenesis data with ab initio transmembrane-helix assembly simulations, assisted by the predicted transmembrane-helix interaction networks. The method was tested in recent community-wide GPCRDock experiments and constructed models with a root mean square deviation 1.26 Å for Dopamine-3 and 2.08 Å for Chemokine-4 receptors in the transmembrane domain regions, which were significantly closer to the native than the best templates available in the PDB. GPCR-I-TASSER has been applied to model all 1,026 putative GPCRs in the human genome, where 923 are found to have correct folds based on the confidence score analysis and mutagenesis data comparison. The successfully modeled GPCRs contain many pharmaceutically important families that do not have previously solved structures, including Trace amine, Prostanoids, Releasing hormones, Melanocortins, Vasopressin and Neuropeptide Y receptors. All the human GPCR models have been made publicly available through the GPCR-HGmod database at http://zhanglab.ccmb.med.umich.edu/GPCR-HGmod/ The results demonstrate new progress on genome-wide structure modeling of transmembrane proteins which should bring useful impact on the effort of GPCR-targeted drug discovery.

Electrostatics of cysteine residues in proteins: Parameterization and validation of a simple model

Science.gov (United States)

Salsbury, Freddie R.; Poole, Leslie B.; Fetrow, Jacquelyn S.

2013-01-01

One of the most popular and simple models for the calculation of pKas from a protein structure is the semi-macroscopic electrostatic model MEAD. This model requires empirical parameters for each residue to calculate pKas. Analysis of current, widely used empirical parameters for cysteine residues showed that they did not reproduce expected cysteine pKas; thus, we set out to identify parameters consistent with the CHARMM27 force field that capture both the behavior of typical cysteines in proteins and the behavior of cysteines which have perturbed pKas. The new parameters were validated in three ways: (1) calculation across a large set of typical cysteines in proteins (where the calculations are expected to reproduce expected ensemble behavior); (2) calculation across a set of perturbed cysteines in proteins (where the calculations are expected to reproduce the shifted ensemble behavior); and (3) comparison to experimentally determined pKa values (where the calculation should reproduce the pKa within experimental error). Both the general behavior of cysteines in proteins and the perturbed pKa in some proteins can be predicted reasonably well using the newly determined empirical parameters within the MEAD model for protein electrostatics. This study provides the first general analysis of the electrostatics of cysteines in proteins, with specific attention paid to capturing both the behavior of typical cysteines in a protein and the behavior of cysteines whose pKa should be shifted, and validation of force field parameters for cysteine residues. PMID:22777874

Allopregnanolone promotes regeneration and reduces β-amyloid burden in a preclinical model of Alzheimer's disease.

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Shuhua Chen

Full Text Available Previously, we demonstrated that allopregnanolone (APα promoted proliferation of rodent and human neural progenitor cells in vitro. Further, we demonstrated that APα promoted neurogenesis in the hippocampal subgranular zone (SGZ and reversed learning and memory deficits in the male triple transgenic mouse model of Alzheimer's (3xTgAD. In the current study, we determined the efficacy of APα to promote the survival of newly generated neural cells while simultaneously reducing Alzheimer's disease (AD pathology in the 3xTgAD male mouse model. Comparative analyses between three different APα treatment regimens indicated that APα administered 1/week for 6 months was maximally efficacious for simultaneous promotion of neurogenesis and survival of newly generated cells and reduction of AD pathology. We further investigated the efficacy of APα to impact Aβ burden. Treatment was initiated either prior to or post intraneuronal Aβ accumulation. Results indicated that APα administered 1/week for 6 months significantly increased survival of newly generated neurons and simultaneously reduced Aβ pathology with greatest efficacy in the pre-pathology treatment group. APα significantly reduced Aβ generation in hippocampus, cortex, and amygdala, which was paralleled by decreased expression of Aβ-binding-alcohol-dehydrogenase. In addition, APα significantly reduced microglia activation as indicated by reduced expression of OX42 while increasing CNPase, an oligodendrocyte myelin marker. Mechanistic analyses indicated that pre-pathology treatment with APα increased expression of liver-X-receptor, pregnane-X-receptor, and 3-hydroxy-3-methyl-glutaryl-CoA-reductase (HMG-CoA-R, three proteins that regulate cholesterol homeostasis and clearance from brain. Together these findings provide preclinical evidence for the optimal treatment regimen of APα to achieve efficacy as a disease modifying therapeutic to promote regeneration while simultaneously decreasing

Hidden Markov model approach for identifying the modular framework of the protein backbone.

Science.gov (United States)

Camproux, A C; Tuffery, P; Chevrolat, J P; Boisvieux, J F; Hazout, S

1999-12-01

The hidden Markov model (HMM) was used to identify recurrent short 3D structural building blocks (SBBs) describing protein backbones, independently of any a priori knowledge. Polypeptide chains are decomposed into a series of short segments defined by their inter-alpha-carbon distances. Basically, the model takes into account the sequentiality of the observed segments and assumes that each one corresponds to one of several possible SBBs. Fitting the model to a database of non-redundant proteins allowed us to decode proteins in terms of 12 distinct SBBs with different roles in protein structure. Some SBBs correspond to classical regular secondary structures. Others correspond to a significant subdivision of their bounding regions previously considered to be a single pattern. The major contribution of the HMM is that this model implicitly takes into account the sequential connections between SBBs and thus describes the most probable pathways by which the blocks are connected to form the framework of the protein structures. Validation of the SBBs code was performed by extracting SBB series repeated in recoding proteins and examining their structural similarities. Preliminary results on the sequence specificity of SBBs suggest promising perspectives for the prediction of SBBs or series of SBBs from the protein sequences.

Advanced Fluid Reduced Order Models for Compressible Flow.

Energy Technology Data Exchange (ETDEWEB)

Tezaur, Irina Kalashnikova [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Fike, Jeffrey A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlberg, Kevin Thomas [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Barone, Matthew F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Maddix, Danielle [Stanford Univ., CA (United States); Mussoni, Erin E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Balajewicz, Maciej [Univ. of Illinois, Urbana-Champaign, IL (United States)

2017-09-01

This report summarizes fiscal year (FY) 2017 progress towards developing and implementing within the SPARC in-house finite volume flow solver advanced fluid reduced order models (ROMs) for compressible captive-carriage flow problems of interest to Sandia National Laboratories for the design and qualification of nuclear weapons components. The proposed projection-based model order reduction (MOR) approach, known as the Proper Orthogonal Decomposition (POD)/Least- Squares Petrov-Galerkin (LSPG) method, can substantially reduce the CPU-time requirement for these simulations, thereby enabling advanced analyses such as uncertainty quantification and de- sign optimization. Following a description of the project objectives and FY17 targets, we overview briefly the POD/LSPG approach to model reduction implemented within SPARC . We then study the viability of these ROMs for long-time predictive simulations in the context of a two-dimensional viscous laminar cavity problem, and describe some FY17 enhancements to the proposed model reduction methodology that led to ROMs with improved predictive capabilities. Also described in this report are some FY17 efforts pursued in parallel to the primary objective of determining whether the ROMs in SPARC are viable for the targeted application. These include the implemen- tation and verification of some higher-order finite volume discretization methods within SPARC (towards using the code to study the viability of ROMs on three-dimensional cavity problems) and a novel structure-preserving constrained POD/LSPG formulation that can improve the accuracy of projection-based reduced order models. We conclude the report by summarizing the key takeaways from our FY17 findings, and providing some perspectives for future work.

Text Mining for Protein Docking.

Directory of Open Access Journals (Sweden)

Varsha D Badal

2015-12-01

Full Text Available The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking. Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu. The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound

A Novel Approach for Protein-Named Entity Recognition and Protein-Protein Interaction Extraction

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Meijing Li

2015-01-01

Full Text Available Many researchers focus on developing protein-named entity recognition (Protein-NER or PPI extraction systems. However, the studies about these two topics cannot be merged well; then existing PPI extraction systems’ Protein-NER still needs to improve. In this paper, we developed the protein-protein interaction extraction system named PPIMiner based on Support Vector Machine (SVM and parsing tree. PPIMiner consists of three main models: natural language processing (NLP model, Protein-NER model, and PPI discovery model. The Protein-NER model, which is named ProNER, identifies the protein names based on two methods: dictionary-based method and machine learning-based method. ProNER is capable of identifying more proteins than dictionary-based Protein-NER model in other existing systems. The final discovered PPIs extracted via PPI discovery model are represented in detail because we showed the protein interaction types and the occurrence frequency through two different methods. In the experiments, the result shows that the performances achieved by our ProNER and PPI discovery model are better than other existing tools. PPIMiner applied this protein-named entity recognition approach and parsing tree based PPI extraction method to improve the performance of PPI extraction. We also provide an easy-to-use interface to access PPIs database and an online system for PPIs extraction and Protein-NER.

Predicting turns in proteins with a unified model.

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Qi Song

Full Text Available MOTIVATION: Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. RESULTS: In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i using newly exploited features of structural evolution information (secondary structure and shape string of protein based on structure homologies, (ii considering all types of turns in a unified model, and (iii practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications.

A reduced fidelity model for the rotary chemical looping combustion reactor

International Nuclear Information System (INIS)

Iloeje, Chukwunwike O.; Zhao, Zhenlong; Ghoniem, Ahmed F.

2017-01-01

Highlights: • Methodology for developing a reduced fidelity rotary CLC reactor model is presented. • The reduced model determines optimal reactor configuration that meets design and operating requirements. • A 4-order of magnitude reduction in computational cost is achieved with good prediction accuracy. • Sensitivity studies demonstrate importance of accurate kinetic parameters for reactor optimization. - Abstract: The rotary chemical looping combustion reactor has great potential for efficient integration with CO_2 capture-enabled energy conversion systems. In earlier studies, we described a one-dimensional rotary reactor model, and used it to demonstrate the feasibility of continuous reactor operation. Though this detailed model provides a high resolution representation of the rotary reactor performance, it is too computationally expensive for studies that require multiple model evaluations. Specifically, it is not ideal for system-level studies where the reactor is a single component in an energy conversion system. In this study, we present a reduced fidelity model (RFM) of the rotary reactor that reduces computational cost and determines an optimal combination of variables that satisfy reactor design requirements. Simulation results for copper, nickel and iron-based oxygen carriers show a four-order of magnitude reduction in simulation time, and reasonable prediction accuracy. Deviations from the detailed reference model predictions range from 3% to 20%, depending on oxygen carrier type and operating conditions. This study also demonstrates how the reduced model can be modified to deal with both optimization and design oriented problems. A parametric study using the reduced model is then applied to analyze the sensitivity of the optimal reactor design to changes in selected operating and kinetic parameters. These studies show that temperature and activation energy have a greater impact on optimal geometry than parameters like pressure or feed fuel

Electronic transport on the spatial structure of the protein: Three-dimensional lattice model

International Nuclear Information System (INIS)

Sarmento, R.G.; Frazão, N.F.; Macedo-Filho, A.

2017-01-01

Highlights: • The electronic transport on the structure of the three-dimensional lattice model of the protein is studied. • The signing of the current–voltage is directly affected by permutations of the weak bonds in the structure. • Semiconductor behave of the proteins suggest a potential application in the development of novel biosensors. - Abstract: We report a numerical analysis of the electronic transport in protein chain consisting of thirty-six standard amino acids. The protein chains studied have three-dimensional structure, which can present itself in three distinct conformations and the difference consist in the presence or absence of thirteen hydrogen-bondings. Our theoretical method uses an electronic tight-binding Hamiltonian model, appropriate to describe the protein segments modeled by the amino acid chain. We note that the presence and the permutations between weak bonds in the structure of proteins are directly related to the signing of the current–voltage. Furthermore, the electronic transport depends on the effect of temperature. In addition, we have found a semiconductor behave in the models investigated and it suggest a potential application in the development of novel biosensors for molecular diagnostics.

Electronic transport on the spatial structure of the protein: Three-dimensional lattice model

Energy Technology Data Exchange (ETDEWEB)

Sarmento, R.G. [Departamento de Ciências Biológicas, Universidade Federal do Piauí, 64800-000 Floriano, PI (Brazil); Frazão, N.F. [Centro de Educação e Saúde, Universidade Federal de Campina Grande, 581750-000 Cuité, PB (Brazil); Macedo-Filho, A., E-mail: amfilho@gmail.com [Campus Prof. Antonio Geovanne Alves de Sousa, Universidade Estadual do Piauí, 64260-000 Piripiri, PI (Brazil)

2017-01-30

Highlights: • The electronic transport on the structure of the three-dimensional lattice model of the protein is studied. • The signing of the current–voltage is directly affected by permutations of the weak bonds in the structure. • Semiconductor behave of the proteins suggest a potential application in the development of novel biosensors. - Abstract: We report a numerical analysis of the electronic transport in protein chain consisting of thirty-six standard amino acids. The protein chains studied have three-dimensional structure, which can present itself in three distinct conformations and the difference consist in the presence or absence of thirteen hydrogen-bondings. Our theoretical method uses an electronic tight-binding Hamiltonian model, appropriate to describe the protein segments modeled by the amino acid chain. We note that the presence and the permutations between weak bonds in the structure of proteins are directly related to the signing of the current–voltage. Furthermore, the electronic transport depends on the effect of temperature. In addition, we have found a semiconductor behave in the models investigated and it suggest a potential application in the development of novel biosensors for molecular diagnostics.

Modelling responses of broiler chickens to dietary balanced protein

NARCIS (Netherlands)

Eits, R.M.

2004-01-01

Protein is an important nutrient for growing broiler chickens, as it affects broiler performance, feed cost as well as nitrogen excretion. The objective of this dissertation was to develop a growth model for broiler chickens that could be easily used by practical nutritionists. The model should

Mathematical Modeling of Protein Misfolding Mechanisms in Neurological Diseases: A Historical Overview.

Science.gov (United States)

Carbonell, Felix; Iturria-Medina, Yasser; Evans, Alan C

2018-01-01

Protein misfolding refers to a process where proteins become structurally abnormal and lose their specific 3-dimensional spatial configuration. The histopathological presence of misfolded protein (MP) aggregates has been associated as the primary evidence of multiple neurological diseases, including Prion diseases, Alzheimer's disease, Parkinson's disease, and Creutzfeldt-Jacob disease. However, the exact mechanisms of MP aggregation and propagation, as well as their impact in the long-term patient's clinical condition are still not well understood. With this aim, a variety of mathematical models has been proposed for a better insight into the kinetic rate laws that govern the microscopic processes of protein aggregation. Complementary, another class of large-scale models rely on modern molecular imaging techniques for describing the phenomenological effects of MP propagation over the whole brain. Unfortunately, those neuroimaging-based studies do not take full advantage of the tremendous capabilities offered by the chemical kinetics modeling approach. Actually, it has been barely acknowledged that the vast majority of large-scale models have foundations on previous mathematical approaches that describe the chemical kinetics of protein replication and propagation. The purpose of the current manuscript is to present a historical review about the development of mathematical models for describing both microscopic processes that occur during the MP aggregation and large-scale events that characterize the progression of neurodegenerative MP-mediated diseases.

Model system-guided protein interaction mapping for virus isolated from phloem tissue

Science.gov (United States)

Potato leafroll virus (PLRV) is an agriculturally important phloem-limited pathogen that causes significant yield loss in potato (Solanum tuberosum) and a model virus in the Luteoviridae. Encoding only a small repertoire of viral proteins, PLRV relies on carefully orchestrated protein-protein intera...

A modeling strategy for G-protein coupled receptors

Directory of Open Access Journals (Sweden)

Anna Kahler

2016-03-01

Full Text Available Cell responses can be triggered via G-protein coupled receptors (GPCRs that interact with small molecules, peptides or proteins and transmit the signal over the membrane via structural changes to activate intracellular pathways. GPCRs are characterized by a rather low sequence similarity and exhibit structural differences even for functionally closely related GPCRs. An accurate structure prediction for GPCRs is therefore not straightforward. We propose a computational approach that relies on the generation of several independent models based on different template structures, which are subsequently refined by molecular dynamics simulations. A comparison of their conformational stability and the agreement with GPCR-typical structural features is then used to select a favorable model. This strategy was applied to predict the structure of the herpesviral chemokine receptor US28 by generating three independent models based on the known structures of the chemokine receptors CXCR1, CXCR4, and CCR5. Model refinement and evaluation suggested that the model based on CCR5 exhibits the most favorable structural properties. In particular, the GPCR-typical structural features, such as a conserved water cluster or conserved non-covalent contacts, are present to a larger extent in the model based on CCR5 compared to the other models. A final model validation based on the recently published US28 crystal structure confirms that the CCR5-based model is the most accurate and exhibits 80.8% correctly modeled residues within the transmembrane helices. The structural agreement between the selected model and the crystal structure suggests that our modeling strategy may also be more generally applicable to other GPCRs of unknown structure.

Markov state models of protein misfolding

Science.gov (United States)

Sirur, Anshul; De Sancho, David; Best, Robert B.

2016-02-01

Markov state models (MSMs) are an extremely useful tool for understanding the conformational dynamics of macromolecules and for analyzing MD simulations in a quantitative fashion. They have been extensively used for peptide and protein folding, for small molecule binding, and for the study of native ensemble dynamics. Here, we adapt the MSM methodology to gain insight into the dynamics of misfolded states. To overcome possible flaws in root-mean-square deviation (RMSD)-based metrics, we introduce a novel discretization approach, based on coarse-grained contact maps. In addition, we extend the MSM methodology to include "sink" states in order to account for the irreversibility (on simulation time scales) of processes like protein misfolding. We apply this method to analyze the mechanism of misfolding of tandem repeats of titin domains, and how it is influenced by confinement in a chaperonin-like cavity.

BWR stability using a reducing dynamical model

International Nuclear Information System (INIS)

Ballestrin Bolea, J. M.; Blazquez Martinez, J. B.

1990-01-01

BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical structure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations is non-linear. Simple parametric calculation of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author)

Reduced influenza viral neutralizing activity of natural human trimers of surfactant protein D

DEFF Research Database (Denmark)

Hartshorn, Kevan L; White, Mitchell R; Tecle, Tesfaldet

2007-01-01

BACKGROUND: Surfactant protein D (SP-D) plays important roles in innate host defense against influenza A virus (IAV) infection. Common human polymorphisms of SP-D have been found in many human populations and associated with increased risk of certain infections. We recently reported that the Thr...... on the CRD of SP-D were found to have differing effects on antiviral activity. Using an mAb that did not interfere with antiviral activity of SP-D, we confirm that natural SP-D trimers had reduced ability to bind to IAV. In addition, the trimers had reduced ability to neutralize IAV as compared to natural...... indicate that a common human polymorphic form of SP-D may modulate host defense against IAV and give impetus to clinical studies correlating this genotype with risk for IAV infection in susceptible groups. We also show that mAbs directed against different areas on the carbohydrate recognition domain of SP...

Electrostatics of cysteine residues in proteins: parameterization and validation of a simple model.

Science.gov (United States)

Salsbury, Freddie R; Poole, Leslie B; Fetrow, Jacquelyn S

2012-11-01

One of the most popular and simple models for the calculation of pK(a) s from a protein structure is the semi-macroscopic electrostatic model MEAD. This model requires empirical parameters for each residue to calculate pK(a) s. Analysis of current, widely used empirical parameters for cysteine residues showed that they did not reproduce expected cysteine pK(a) s; thus, we set out to identify parameters consistent with the CHARMM27 force field that capture both the behavior of typical cysteines in proteins and the behavior of cysteines which have perturbed pK(a) s. The new parameters were validated in three ways: (1) calculation across a large set of typical cysteines in proteins (where the calculations are expected to reproduce expected ensemble behavior); (2) calculation across a set of perturbed cysteines in proteins (where the calculations are expected to reproduce the shifted ensemble behavior); and (3) comparison to experimentally determined pK(a) values (where the calculation should reproduce the pK(a) within experimental error). Both the general behavior of cysteines in proteins and the perturbed pK(a) in some proteins can be predicted reasonably well using the newly determined empirical parameters within the MEAD model for protein electrostatics. This study provides the first general analysis of the electrostatics of cysteines in proteins, with specific attention paid to capturing both the behavior of typical cysteines in a protein and the behavior of cysteines whose pK(a) should be shifted, and validation of force field parameters for cysteine residues. Copyright © 2012 Wiley Periodicals, Inc.

Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

Science.gov (United States)

Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

2014-11-01

As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of

Residues at a Single Site Differentiate Animal Cryptochromes from Cyclobutane Pyrimidine Dimer Photolyases by Affecting the Proteins' Preferences for Reduced FAD.

Science.gov (United States)

Xu, Lei; Wen, Bin; Wang, Yuan; Tian, Changqing; Wu, Mingcai; Zhu, Guoping

2017-06-19

Cryptochromes (CRYs) and photolyases belong to the cryptochrome/photolyase family (CPF). Reduced FAD is essential for photolyases to photorepair UV-induced cyclobutane pyrimidine dimers (CPDs) or 6-4 photoproducts in DNA. In Drosophila CRY (dCRY, a type I animal CRY), FAD is converted to the anionic radical but not to the reduced state upon illumination, which might induce a conformational change in the protein to relay the light signal downstream. To explore the foundation of these differences, multiple sequence alignment of 650 CPF protein sequences was performed. We identified a site facing FAD (Ala377 in Escherichia coli CPD photolyase and Val415 in dCRY), hereafter referred to as "site 377", that was distinctly conserved across these sequences: CPD photolyases often had Ala, Ser, or Asn at this site, whereas animal CRYs had Ile, Leu, or Val. The binding affinity for reduced FAD, but not the photorepair activity of E. coli photolyase, was dramatically impaired when replacing Ala377 with any of the three CRY residues. Conversely, in V415S and V415N mutants of dCRY, FAD was photoreduced to its fully reduced state after prolonged illumination, and light-dependent conformational changes of these mutants were severely inhibited. We speculate that the residues at site 377 play a key role in the different preferences of CPF proteins for reduced FAD, which differentiate animal CRYs from CPD photolyases. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mutations in ribosomal protein L3 and 23S ribosomal RNA at the peptidyl transferase centre are associated with reduced susceptibility to tiamulin in Brachyspira spp. isolates.

Science.gov (United States)

Pringle, Märit; Poehlsgaard, Jacob; Vester, Birte; Long, Katherine S

2004-12-01

The pleuromutilin antibiotic tiamulin binds to the ribosomal peptidyl transferase centre. Three groups of Brachyspira spp. isolates with reduced tiamulin susceptibility were analysed to define resistance mechanisms to the drug. Mutations were identified in genes encoding ribosomal protein L3 and 23S rRNA at positions proximal to the peptidyl transferase centre. In two groups of laboratory-selected mutants, mutations were found at nucleotide positions 2032, 2055, 2447, 2499, 2504 and 2572 of 23S rRNA (Escherichia coli numbering) and at amino acid positions 148 and 149 of ribosomal protein L3 (Brachyspira pilosicoli numbering). In a third group of clinical B. hyodysenteriae isolates, only a single mutation at amino acid 148 of ribosomal protein L3 was detected. Chemical footprinting experiments show a reduced binding of tiamulin to ribosomal subunits from mutants with decreased susceptibility to the drug. This reduction in drug binding is likely the resistance mechanism for these strains. Hence, the identified mutations located near the tiamulin binding site are predicted to be responsible for the resistance phenotype. The positions of the mutated residues relative to the bound drug advocate a model where the mutations affect tiamulin binding indirectly through perturbation of nucleotide U2504.

Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium

Directory of Open Access Journals (Sweden)

Pierre Coenraets

1997-01-01

Full Text Available Comparison of computation time between single-trait and multiple-trait evaluations showed that with the use of the canonicat transformation associated with multiple diagonalization of (covariance matrices, multiple-trait analysis for milk, fat and protein yields is not more expensive than three single-trait analyzes. Rank correlations between breeding values for 54,820 cows with records (for their 1,406 sires estimated with the single-trait and multiple-trait models were over .98 (.99 in fat yield and over .99 (.99 in milk and protein yields. The relative gain expressed as reduction in mean prediction error variance was 3% (1% in milk yield, 6% (3% in fat yield, and .4% (.2% in protein yield for cows (for sires. Relative genetic gains were 3% (1%, 6% (2% and .5% (.2% respectively in milk, fat and protein yields for cows (for sires. The use of multiple-trait models bas therefore the advantages of improved precision and reduced selection bics. Multiple-trait analysis could be extended for the analyzes of test-day records. Results show that this or similar multiple-trait animal model could be implemented immediately in Belgium at low computing cost, using the proposed algorithme and could be the first step to new, more advanced evaluation methods.

Simulation study of a rectifying bipolar ion channel: Detailed model versus reduced model

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Z. Ható

2016-02-01

Full Text Available We study a rectifying mutant of the OmpF porin ion channel using both all-atom and reduced models. The mutant was created by Miedema et al. [Nano Lett., 2007, 7, 2886] on the basis of the NP semiconductor diode, in which an NP junction is formed. The mutant contains a pore region with positive amino acids on the left-hand side and negative amino acids on the right-hand side. Experiments show that this mutant rectifies. Although we do not know the structure of this mutant, we can build an all-atom model for it on the basis of the structure of the wild type channel. Interestingly, molecular dynamics simulations for this all-atom model do not produce rectification. A reduced model that contains only the important degrees of freedom (the positive and negative amino acids and free ions in an implicit solvent, on the other hand, exhibits rectification. Our calculations for the reduced model (using the Nernst-Planck equation coupled to Local Equilibrium Monte Carlo simulations reveal a rectification mechanism that is different from that seen for semiconductor diodes. The basic reason is that the ions are different in nature from electrons and holes (they do not recombine. We provide explanations for the failure of the all-atom model including the effect of all the other atoms in the system as a noise that inhibits the response of ions (that would be necessary for rectification to the polarizing external field.

Bayesian Proteoform Modeling Improves Protein Quantification of Global Proteomic Measurements

Energy Technology Data Exchange (ETDEWEB)

Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Datta, Susmita; Payne, Samuel H.; Kang, Jiyun; Bramer, Lisa M.; Nicora, Carrie D.; Shukla, Anil K.; Metz, Thomas O.; Rodland, Karin D.; Smith, Richard D.; Tardiff, Mark F.; McDermott, Jason E.; Pounds, Joel G.; Waters, Katrina M.

2014-12-01

As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally-driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statistical inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab ® and R packages at https://github.com/PNNL-Comp-Mass-Spec/BP-Quant.

Modelling Transcapillary Transport of Fluid and Proteins in Hemodialysis Patients.

Directory of Open Access Journals (Sweden)

Mauro Pietribiasi

Full Text Available The kinetics of protein transport to and from the vascular compartment play a major role in the determination of fluid balance and plasma refilling during hemodialysis (HD sessions. In this study we propose a whole-body mathematical model describing water and protein shifts across the capillary membrane during HD and compare its output to clinical data while evaluating the impact of choosing specific values for selected parameters.The model follows a two-compartment structure (vascular and interstitial space and is based on balance equations of protein mass and water volume in each compartment. The capillary membrane was described according to the three-pore theory. Two transport parameters, the fractional contribution of large pores (αLP and the total hydraulic conductivity (LpS of the capillary membrane, were estimated from patient data. Changes in the intensity and direction of individual fluid and solute flows through each part of the transport system were analyzed in relation to the choice of different values of small pores radius and fractional conductivity, lymphatic sensitivity to hydraulic pressure, and steady-state interstitial-to-plasma protein concentration ratio.The estimated values of LpS and αLP were respectively 10.0 ± 8.4 mL/min/mmHg (mean ± standard deviation and 0.062 ± 0.041. The model was able to predict with good accuracy the profiles of plasma volume and serum total protein concentration in most of the patients (average root-mean-square deviation < 2% of the measured value.The applied model provides a mechanistic interpretation of fluid transport processes induced by ultrafiltration during HD, using a minimum of tuned parameters and assumptions. The simulated values of individual flows through each kind of pore and lymphatic absorption rate yielded by the model may suggest answers to unsolved questions on the relative impact of these not-measurable quantities on total vascular refilling and fluid balance.

Absence of Non-histone Protein Complexes at Natural Chromosomal Pause Sites Results in Reduced Replication Pausing in Aging Yeast Cells

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Marleny Cabral

2016-11-01

Full Text Available There is substantial evidence that genomic instability increases during aging. Replication pausing (and stalling at difficult-to-replicate chromosomal sites may induce genomic instability. Interestingly, in aging yeast cells, we observed reduced replication pausing at various natural replication pause sites (RPSs in ribosomal DNA (rDNA and non-rDNA locations (e.g., silent replication origins and tRNA genes. The reduced pausing occurs independent of the DNA helicase Rrm3p, which facilitates replication past these non-histone protein-complex-bound RPSs, and is independent of the deacetylase Sir2p. Conditions of caloric restriction (CR, which extend life span, also cause reduced replication pausing at the 5S rDNA and at tRNA genes. In aged and CR cells, the RPSs are less occupied by their specific non-histone protein complexes (e.g., the preinitiation complex TFIIIC, likely because members of these complexes have primarily cytosolic localization. These conditions may lead to reduced replication pausing and may lower replication stress at these sites during aging.

Protein modelling of triterpene synthase genes from mangrove plants using Phyre2 and Swiss-model

Science.gov (United States)

Basyuni, M.; Wati, R.; Sulistiyono, N.; Hayati, R.; Sumardi; Oku, H.; Baba, S.; Sagami, H.

2018-03-01

Molecular cloning of five oxidosqualene cyclases (OSC) genes from Bruguiera gymnorrhiza, Kandelia candel, and Rhizophora stylosa had previously been cloned, characterized, and encoded mono and -multi triterpene synthases. The present study analyzed protein modelling of triterpene synthase genes from mangrove using Phyre2 and Swiss-model. The diversity was noted within protein modelling of triterpene synthases using Phyre2 from sequence identity (38-43%) and residue (696-703). RsM2 was distinguishable from others for template structure; it used lanosterol synthase as a template (PDB ID: w6j.1.A). By contrast, other genes used human lanosterol synthase (1w6k.1.A). The predicted bind sites were correlated with the product of triterpene synthase, the product of BgbAS was β-amyrin, while RsM1 contained a significant amount of β-amyrin. Similarly BgLUS and KcMS, both main products was lupeol, on the other hand, RsM2 with the outcome of taraxerol. Homology modelling revealed that 696 residues of BgbAS, BgLUS, RsM1, and RsM2 (91-92% of the amino acid sequence) had been modelled with 100% confidence by the single highest scoring template using Phyre2. This coverage was higher than Swiss-model (85-90%). The present study suggested that molecular cloning of triterpene genes provides useful tools for studying the protein modelling related regulation of isoprenoids biosynthesis in mangrove forests.

A feature-based approach to modeling protein-protein interaction hot spots.

Science.gov (United States)

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-05-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.

Glycation inhibitors extend yeast chronological lifespan by reducing advanced glycation end products and by back regulation of proteins involved in mitochondrial respiration.

Science.gov (United States)

Kazi, Rubina S; Banarjee, Reema M; Deshmukh, Arati B; Patil, Gouri V; Jagadeeshaprasad, Mashanipalya G; Kulkarni, Mahesh J

2017-03-06

Advanced Glycation End products (AGEs) are implicated in aging process. Thus, reducing AGEs by using glycation inhibitors may help in attenuating the aging process. In this study using Saccharomyces cerevisiae yeast system, we show that Aminoguanidine (AMG), a well-known glycation inhibitor, decreases the AGE modification of proteins in non-calorie restriction (NR) (2% glucose) and extends chronological lifespan (CLS) similar to that of calorie restriction (CR) condition (0.5% glucose). Proteomic analysis revealed that AMG back regulates the expression of differentially expressed proteins especially those involved in mitochondrial respiration in NR condition, suggesting that it switches metabolism from fermentation to respiration, mimicking CR. AMG induced back regulation of differentially expressed proteins could be possibly due to its chemical effect or indirectly by glycation inhibition. To delineate this, Metformin (MET), a structural analog of AMG and a mild glycation inhibitor and Hydralazine (HYD), another potent glycation inhibitor but not structural analog of AMG were used. HYD was more effective than MET in mimicking AMG suggesting that glycation inhibition was responsible for restoration of differentially expressed proteins. Thus glycation inhibitors particularly AMG, HYD and MET extend yeast CLS by reducing AGEs, modulating the expression of proteins involved in mitochondrial respiration and possibly by scavenging glucose. This study reports the role of glycation in aging process. In the non-caloric restriction condition, carbohydrates such as glucose promote protein glycation and reduce CLS. While, the inhibitors of glycation such as AMG, HYD, MET mimic the caloric restriction condition by back regulating deregulated proteins involved in mitochondrial respiration which could facilitate shift of metabolism from fermentation to respiration and extend yeast CLS. These findings suggest that glycation inhibitors can be potential molecules that can be used

A Mathematical Model of the Effect of Immunogenicity on Therapeutic Protein Pharmacokinetics

OpenAIRE

Chen, Xiaoying; Hickling, Timothy; Kraynov, Eugenia; Kuang, Bing; Parng, Chuenlei; Vicini, Paolo

2013-01-01

A mathematical pharmacokinetic/anti-drug-antibody (PK/ADA) model was constructed for quantitatively assessing immunogenicity for therapeutic proteins. The model is inspired by traditional pharmacokinetic/pharmacodynamic (PK/PD) models, and is based on the observed impact of ADA on protein drug clearance. The hypothesis for this work is that altered drug PK contains information about the extent and timing of ADA generation. By fitting drug PK profiles while accounting for ADA-mediated drug cle...

High dietary protein intake, reducing or eliciting insulin resistance?

NARCIS (Netherlands)

Rietman, A.; Schwarz, J.; Tome, D.; Kok, F.J.; Mensink, M.R.

2014-01-01

Dietary proteins have an insulinotropic effect and thus promote insulin secretion, which indeed leads to enhanced glucose clearance from the blood. In the long term, however, a high dietary protein intake is associated with an increased risk of type 2 diabetes. Moreover, branched-chain amino acids

Exercise training restores cardiac protein quality control in heart failure.

Directory of Open Access Journals (Sweden)

Juliane C Campos

Full Text Available Exercise training is a well-known coadjuvant in heart failure treatment; however, the molecular mechanisms underlying its beneficial effects remain elusive. Despite the primary cause, heart failure is often preceded by two distinct phenomena: mitochondria dysfunction and cytosolic protein quality control disruption. The objective of the study was to determine the contribution of exercise training in regulating cardiac mitochondria metabolism and cytosolic protein quality control in a post-myocardial infarction-induced heart failure (MI-HF animal model. Our data demonstrated that isolated cardiac mitochondria from MI-HF rats displayed decreased oxygen consumption, reduced maximum calcium uptake and elevated H₂O₂ release. These changes were accompanied by exacerbated cardiac oxidative stress and proteasomal insufficiency. Declined proteasomal activity contributes to cardiac protein quality control disruption in our MI-HF model. Using cultured neonatal cardiomyocytes, we showed that either antimycin A or H₂O₂ resulted in inactivation of proteasomal peptidase activity, accumulation of oxidized proteins and cell death, recapitulating our in vivo model. Of interest, eight weeks of exercise training improved cardiac function, peak oxygen uptake and exercise tolerance in MI-HF rats. Moreover, exercise training restored mitochondrial oxygen consumption, increased Ca²⁺-induced permeability transition and reduced H₂O₂ release in MI-HF rats. These changes were followed by reduced oxidative stress and better cardiac protein quality control. Taken together, our findings uncover the potential contribution of mitochondrial dysfunction and cytosolic protein quality control disruption to heart failure and highlight the positive effects of exercise training in re-establishing cardiac mitochondrial physiology and protein quality control, reinforcing the importance of this intervention as a non-pharmacological tool for heart failure therapy.

Backbone dynamics of oxidized and reduced D. vulgaris flavodoxin in solution

International Nuclear Information System (INIS)

Hrovat, Andrea; Bluemel, Markus; Loehr, Frank; Mayhew, Stephen G.; Rueterjans, Heinz

1997-01-01

Recombinant Desulfovibrio vulgaris flavodoxin was produced in Escherichia coli. A complete backbone NMR assignment for the two-electron reduced protein revealed significant changes of chemical shift values compared to the oxidized protein, in particular for the flavine mononucleotide (FMN)-binding site. A comparison of homo- and heteronuclear NOESY spectra for the two redox states led to the assumption that reduction is not accompanied by significant changes of the global fold of the protein.The backbone dynamics of both the oxidized and reduced forms of D. vulgaris flavodoxin were investigated using two-dimensional 15 N- 1 H correlation NMR spectroscopy.T 1 , T 2 and NOE data are obtained for 95% of the backbone amide groups in both redox states. These values were analysed in terms of the 'model-free' approach introduced by Lipari and Szabo [(1982) J. Am. Chem. Soc., 104, 4546-;4559, 4559-;4570]. A comparison of the two redox states indicates that in the reduced species significantly more flexibility occurs in the two loop regions enclosing FMN.Also, a higher amplitude of local motion could be found for the N(3)H group of FMN bound to the reduced protein compared to the oxidized state

Acetone utilization by sulfate-reducing bacteria: draft genome sequence of Desulfococcus biacutus and a proteomic survey of acetone-inducible proteins.

Science.gov (United States)

Gutiérrez Acosta, Olga B; Schleheck, David; Schink, Bernhard

2014-07-11

The sulfate-reducing bacterium Desulfococcus biacutus is able to utilize acetone for growth by an inducible degradation pathway that involves a novel activation reaction for acetone with CO as a co-substrate. The mechanism, enzyme(s) and gene(s) involved in this acetone activation reaction are of great interest because they represent a novel and yet undefined type of activation reaction under strictly anoxic conditions. In this study, a draft genome sequence of D. biacutus was established. Sequencing, assembly and annotation resulted in 159 contigs with 5,242,029 base pairs and 4773 predicted genes; 4708 were predicted protein-encoding genes, and 3520 of these had a functional prediction. Proteins and genes were identified that are specifically induced during growth with acetone. A thiamine diphosphate-requiring enzyme appeared to be highly induced during growth with acetone and is probably involved in the activation reaction. Moreover, a coenzyme B12- dependent enzyme and proteins that are involved in redox reactions were also induced during growth with acetone. We present for the first time the genome of a sulfate reducer that is able to grow with acetone. The genome information of this organism represents an important tool for the elucidation of a novel reaction mechanism that is employed by a sulfate reducer in acetone activation.

From the Protein's Perspective: The Benefits and Challenges of Protein Structure-Based Pharmacophore Modeling

NARCIS (Netherlands)

Sanders, M.P.A.; McGuire, R; Roumen, L.; de Esch, I.J.P.; de Vlieg, J; Klomp, J.P.G; de Graaf, C.

2011-01-01

A pharmacophore describes the arrangement of molecular features a ligand must contain to efficaciously bind a receptor. Pharmacophore models are developed to improve molecular understanding of ligand-protein interactions, and can be used as a tool to identify novel compounds that fulfil the

Analysing the origin of long-range interactions in proteins using lattice models

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Unger Ron

2009-01-01

Full Text Available Abstract Background Long-range communication is very common in proteins but the physical basis of this phenomenon remains unclear. In order to gain insight into this problem, we decided to explore whether long-range interactions exist in lattice models of proteins. Lattice models of proteins have proven to capture some of the basic properties of real proteins and, thus, can be used for elucidating general principles of protein stability and folding. Results Using a computational version of double-mutant cycle analysis, we show that long-range interactions emerge in lattice models even though they are not an input feature of them. The coupling energy of both short- and long-range pairwise interactions is found to become more positive (destabilizing in a linear fashion with increasing 'contact-frequency', an entropic term that corresponds to the fraction of states in the conformational ensemble of the sequence in which the pair of residues is in contact. A mathematical derivation of the linear dependence of the coupling energy on 'contact-frequency' is provided. Conclusion Our work shows how 'contact-frequency' should be taken into account in attempts to stabilize proteins by introducing (or stabilizing contacts in the native state and/or through 'negative design' of non-native contacts.

MaMR: High-performance MapReduce programming model for material cloud applications

Science.gov (United States)

Jing, Weipeng; Tong, Danyu; Wang, Yangang; Wang, Jingyuan; Liu, Yaqiu; Zhao, Peng

2017-02-01

With the increasing data size in materials science, existing programming models no longer satisfy the application requirements. MapReduce is a programming model that enables the easy development of scalable parallel applications to process big data on cloud computing systems. However, this model does not directly support the processing of multiple related data, and the processing performance does not reflect the advantages of cloud computing. To enhance the capability of workflow applications in material data processing, we defined a programming model for material cloud applications that supports multiple different Map and Reduce functions running concurrently based on hybrid share-memory BSP called MaMR. An optimized data sharing strategy to supply the shared data to the different Map and Reduce stages was also designed. We added a new merge phase to MapReduce that can efficiently merge data from the map and reduce modules. Experiments showed that the model and framework present effective performance improvements compared to previous work.

Reduced Order Modeling in General Relativity

Science.gov (United States)

Tiglio, Manuel

2014-03-01

Reduced Order Modeling is an emerging yet fast developing filed in gravitational wave physics. The main goals are to enable fast modeling and parameter estimation of any detected signal, along with rapid matched filtering detecting. I will focus on the first two. Some accomplishments include being able to replace, with essentially no lost of physical accuracy, the original models with surrogate ones (which are not effective ones, that is, they do not simplify the physics but go on a very different track, exploiting the particulars of the waveform family under consideration and state of the art dimensional reduction techniques) which are very fast to evaluate. For example, for EOB models they are at least around 3 orders of magnitude faster than solving the original equations, with physically equivalent results. For numerical simulations the speedup is at least 11 orders of magnitude. For parameter estimation our current numbers are about bringing ~100 days for a single SPA inspiral binary neutron star Bayesian parameter estimation analysis to under a day. More recently, it has been shown that the full precessing problem for, say, 200 cycles, can be represented, through some new ideas, by a remarkably compact set of carefully chosen reduced basis waveforms (~10-100, depending on the accuracy requirements). I will highlight what I personally believe are the challenges to face next in this subarea of GW physics and where efforts should be directed. This talk will summarize work in collaboration with: Harbir Antil (GMU), Jonathan Blackman (Caltech), Priscila Canizares (IoA, Cambridge, UK), Sarah Caudill (UWM), Jonathan Gair (IoA. Cambridge. UK), Scott Field (UMD), Chad R. Galley (Caltech), Frank Herrmann (Germany), Han Hestahven (EPFL, Switzerland), Jason Kaye (Brown, Stanford & Courant). Evan Ochsner (UWM), Ricardo Nochetto (UMD), Vivien Raymond (LIGO, Caltech), Rory Smith (LIGO, Caltech) Bela Ssilagyi (Caltech) and MT (UMD & Caltech).

Protein model discrimination using mutational sensitivity derived from deep sequencing.

Science.gov (United States)

Adkar, Bharat V; Tripathi, Arti; Sahoo, Anusmita; Bajaj, Kanika; Goswami, Devrishi; Chakrabarti, Purbani; Swarnkar, Mohit K; Gokhale, Rajesh S; Varadarajan, Raghavan

2012-02-08

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. Copyright © 2012 Elsevier Ltd. All rights reserved.

Masseter muscle myofibrillar protein synthesis and degradation in an experimental critical illness myopathy model.

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Hazem Akkad

Full Text Available Critical illness myopathy (CIM is a debilitating common consequence of modern intensive care, characterized by severe muscle wasting, weakness and a decreased myosin/actin (M/A ratio. Limb/trunk muscles are primarily affected by this myopathy while cranial nerve innervated muscles are spared or less affected, but the mechanisms underlying these muscle-specific differences remain unknown. In this time-resolved study, the cranial nerve innervated masseter muscle was studied in a unique experimental rat intensive care unit (ICU model, where animals were exposed to sedation, neuromuscular blockade (NMB, mechanical ventilation, and immobilization for durations varying between 6 h and 14d. Gel electrophoresis, immunoblotting, RT-PCR and morphological staining techniques were used to analyze M/A ratios, myofiber size, synthesis and degradation of myofibrillar proteins, and levels of heat shock proteins (HSPs. Results obtained in the masseter muscle were compared with previous observations in experimental and clinical studies of limb muscles. Significant muscle-specific differences were observed, i.e., in the masseter, the decline in M/A ratio and muscle fiber size was small and delayed. Furthermore, transcriptional regulation of myosin and actin synthesis was maintained, and Akt phosphorylation was only briefly reduced. In studied degradation pathways, only mRNA, but not protein levels of MuRF1, atrogin-1 and the autophagy marker LC3b were activated by the ICU condition. The matrix metalloproteinase MMP-2 was inhibited and protective HSPs were up-regulated early. These results confirm that the cranial nerve innervated masticatory muscles is less affected by the ICU-stress response than limb muscles, in accordance with clinical observation in ICU patients with CIM, supporting the model' credibility as a valid CIM model.

Approaches for Reduced Order Modeling of Electrically Actuated von Karman Microplates

KAUST Repository

Saghir, Shahid

2016-07-25

This article presents and compares different approaches to develop reduced order models for the nonlinear von Karman rectangular microplates actuated by nonlinear electrostatic forces. The reduced-order models aim to investigate the static and dynamic behavior of the plate under small and large actuation forces. A fully clamped microplate is considered. Different types of basis functions are used in conjunction with the Galerkin method to discretize the governing equations. First we investigate the convergence with the number of modes retained in the model. Then for validation purpose, a comparison of the static results is made with the results calculated by a nonlinear finite element model. The linear eigenvalue problem for the plate under the electrostatic force is solved for a wide range of voltages up to pull-in. Results among the various reduced-order modes are compared and are also validated by comparing to results of the finite-element model. Further, the reduced order models are employed to capture the forced dynamic response of the microplate under small and large vibration amplitudes. Comparison of the different approaches are made for this case. Keywords: electrically actuated microplates, static analysis, dynamics of microplates, diaphragm vibration, large amplitude vibrations, nonlinear dynamics

The Prenylflavonoid Xanthohumol Reduces Alzheimer-Like Changes and Modulates Multiple Pathogenic Molecular Pathways in the Neuro2a/APPswe Cell Model of AD

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Xianfeng Huang

2018-04-01

Full Text Available Alzheimer’s disease (AD is a progressive neurodegenerative disorder that has proved refractory to drug treatment. Given evidence of neuroprotection in animal models of ischemic stroke, we assessed the prenylflavonoid xanthohumol from the Common Hop (Humulus lupulus L. for therapeutic potential in murine neuroblastoma N2a cells stably expressing human Swedish mutant amyloid precursor protein (N2a/APP, a well-characterized cellular model of AD. The ELISA and Western-blot analysis revealed that xanthohumol (Xn inhibited Aβ accumulation and APP processing, and that Xn ameliorated tau hyperphosphorylation via PP2A, GSK3β pathways in N2a/APP cells. The amelioration of tau hyperphosphorylation by Xn was also validated on HEK293/Tau cells, another cell line with tau hyperphosphorylation. Proteomic analysis (2D-DIGE-coupled MS revealed a total of 30 differentially expressed lysate proteins in N2a/APP vs. wild-type (WT N2a cells (N2a/WT, and a total of 21 differentially expressed proteins in lysates of N2a/APP cells in the presence or absence of Xn. Generally, these 51 differential proteins could be classified into seven main categories according to their functions, including: endoplasmic reticulum (ER stress-associated proteins; oxidative stress-associated proteins; proteasome-associated proteins; ATPase and metabolism-associated proteins; cytoskeleton-associated proteins; molecular chaperones-associated proteins, and others. We used Western-blot analysis to validate Xn-associated changes of some key proteins in several biological/pathogenic processes. Taken together, we show that Xn reduces AD-related changes in stably transfected N2a/APP cells. The underlying mechanisms involve modulation of multiple pathogenic pathways, including those involved in ER stress, oxidative stress, proteasome molecular systems, and the neuronal cytoskeleton. These results suggest Xn may have potential for the treatment of AD and/or neuropathologically related

Reduced Complexity Volterra Models for Nonlinear System Identification

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Hacıoğlu Rıfat

2001-01-01

Full Text Available A broad class of nonlinear systems and filters can be modeled by the Volterra series representation. However, its practical use in nonlinear system identification is sometimes limited due to the large number of parameters associated with the Volterra filter′s structure. The parametric complexity also complicates design procedures based upon such a model. This limitation for system identification is addressed in this paper using a Fixed Pole Expansion Technique (FPET within the Volterra model structure. The FPET approach employs orthonormal basis functions derived from fixed (real or complex pole locations to expand the Volterra kernels and reduce the number of estimated parameters. That the performance of FPET can considerably reduce the number of estimated parameters is demonstrated by a digital satellite channel example in which we use the proposed method to identify the channel dynamics. Furthermore, a gradient-descent procedure that adaptively selects the pole locations in the FPET structure is developed in the paper.

Review: Optimizing ruminant conversion of feed protein to human food protein.

Science.gov (United States)

Broderick, G A

2017-11-20

Ruminant livestock have the ability to produce high-quality human food from feedstuffs of little or no value for humans. Balanced essential amino acid composition of meat and milk from ruminants makes those protein sources valuable adjuncts to human diets. It is anticipated that there will be increasing demand for ruminant proteins in the future. Increasing productivity per animal dilutes out the nutritional and environmental costs of maintenance and rearing dairy animals up to production. A number of nutritional strategies improve production per animal such as ration balancing in smallholder operations and small grain supplements to ruminants fed high-forage diets. Greenhouse gas emission intensity is reduced by increased productivity per animal; recent research has developed at least one effective inhibitor of methane production in the rumen. There is widespread over-feeding of protein to dairy cattle; milk and component yields can be maintained, and sometimes even increased, at lower protein intake. Group feeding dairy cows according to production and feeding diets higher in rumen-undegraded protein can improve milk and protein yield. Supplementing rumen-protected essential amino acids will also improve N efficiency in some cases. Better N utilization reduces urinary N, which is the most environmentally unstable form of excretory N. Employing nutritional models to more accurately meet animal requirements improves nutrient efficiency. Although smallholder enterprises, which are concentrated in tropical and semi-tropical regions of developing countries, are subject to different economic pressures, nutritional biology is similar at all production levels. Rather than milk volume, nutritional strategies should maximize milk component yield, which is proportional to market value as well as food value when milk nutrients are consumed directly by farmers and their families. Moving away from Holsteins toward smaller breeds such as Jerseys, Holstein-Jersey crosses or

Modelling small-angle scattering data from complex protein-lipid systems

DEFF Research Database (Denmark)

Kynde, Søren Andreas Røssell

This thesis consists of two parts. The rst part is divided into five chapters. Chapter 1 gives a general introduction to the bio-molecular systems that have been studied. These are membrane proteins and their lipid environments in the form of phospholipid nanodiscs. Membrane proteins...... the techniques very well suited for the study of the nanodisc system. Chapter 3 explains two different modelling approaches that can be used in the analysis of small-angle scattering data from lipid-protein complexes. These are the continuous approach where the system of interest is modelled as a few regular...... combine the bene ts of each of the methods and give unique structural information about relevant bio-molecular complexes in solution. Chapter 4 describes the work behind a proposal of a small-angle neutron scattering instrument for the European Spallation Source under construction in Lund. The instrument...

Lessons from Animal Models of Cytoplasmic Intermediate Filament Proteins.

Science.gov (United States)

Bouameur, Jamal-Eddine; Magin, Thomas M

Cytoplasmic intermediate filaments (IFs) represent a major cytoskeletal network contributing to cell shape, adhesion and migration as well as to tissue resilience and renewal in numerous bilaterians, including mammals. The observation that IFs are dispensable in cultured mammalian cells, but cause tissue-specific, life-threatening disorders, has pushed the need to investigate their function in vivo. In keeping with human disease, the deletion or mutation of murine IF genes resulted in highly specific pathologies. Epidermal keratins, together with desmin, are essential to protect corresponding tissues against mechanical force but also participate in stabilizing cell adhesion and in inflammatory signalling. Surprisingly, other IF proteins contribute to tissue integrity to a much lesser extent than anticipated, pointing towards their role in stress situations. In support, the overexpression of small chaperones or the interference with inflammatory signalling in several settings has been shown to rescue severe tissue pathologies that resulted from the expression of mutant IF proteins. It stills remains an open issue whether the wide range of IF disorders share similar pathomechanisms. Moreover, we lack an understanding how IF proteins participate in signalling processes. Now, with a large number of mouse models in hand, the next challenge will be to develop organotypic cell culture models to dissect pathomechanisms at the molecular level, to employ Crispr/Cas-mediated genome engineering to optimize models and, finally, to combine available animal models with medicinal chemistry for the development of molecular therapies.

Dynamical modeling of microRNA action on the protein translation process.

Science.gov (United States)

Zinovyev, Andrei; Morozova, Nadya; Nonne, Nora; Barillot, Emmanuel; Harel-Bellan, Annick; Gorban, Alexander N

2010-02-24

Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc.), the rate of which can be regulated by small non-coding microRNAs through multiple mechanisms. It remains unclear what mechanisms of microRNA action are the most dominant: moreover, many experimental reports deliver controversial messages on what is the concrete mechanism actually observed in the experiment. Nissan and Parker have recently demonstrated that it might be impossible to distinguish alternative biological hypotheses using the steady state data on the rate of protein synthesis. For their analysis they used two simple kinetic models of protein translation. In contrary to the study by Nissan and Parker, we show that dynamical data allow discriminating some of the mechanisms of microRNA action. We demonstrate this using the same models as developed by Nissan and Parker for the sake of comparison but the methods developed (asymptotology of biochemical networks) can be used for other models. We formulate a hypothesis that the effect of microRNA action is measurable and observable only if it affects the dominant system (generalization of the limiting step notion for complex networks) of the protein translation machinery. The dominant system can vary in different experimental conditions that can partially explain the existing controversy of some of the experimental data. Our analysis of the transient protein translation dynamics shows that it gives enough information to verify or reject a hypothesis about a particular molecular mechanism of microRNA action on protein translation. For multiscale systems only that action of microRNA is distinguishable which affects the parameters of dominant system (critical parameters), or changes the dominant system itself. Dominant systems generalize and further develop the old and very popular idea of limiting step. Algorithms for identifying dominant systems in multiscale

Dynamical modeling of microRNA action on the protein translation process

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Barillot Emmanuel

2010-02-01

Full Text Available Abstract Background Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc., the rate of which can be regulated by small non-coding microRNAs through multiple mechanisms. It remains unclear what mechanisms of microRNA action are the most dominant: moreover, many experimental reports deliver controversial messages on what is the concrete mechanism actually observed in the experiment. Nissan and Parker have recently demonstrated that it might be impossible to distinguish alternative biological hypotheses using the steady state data on the rate of protein synthesis. For their analysis they used two simple kinetic models of protein translation. Results In contrary to the study by Nissan and Parker, we show that dynamical data allow discriminating some of the mechanisms of microRNA action. We demonstrate this using the same models as developed by Nissan and Parker for the sake of comparison but the methods developed (asymptotology of biochemical networks can be used for other models. We formulate a hypothesis that the effect of microRNA action is measurable and observable only if it affects the dominant system (generalization of the limiting step notion for complex networks of the protein translation machinery. The dominant system can vary in different experimental conditions that can partially explain the existing controversy of some of the experimental data. Conclusions Our analysis of the transient protein translation dynamics shows that it gives enough information to verify or reject a hypothesis about a particular molecular mechanism of microRNA action on protein translation. For multiscale systems only that action of microRNA is distinguishable which affects the parameters of dominant system (critical parameters, or changes the dominant system itself. Dominant systems generalize and further develop the old and very popular idea of limiting step

Dietary management of chronic kidney disease: protein restriction and beyond.

Science.gov (United States)

Goraya, Nimrit; Wesson, Donald E

2012-11-01

More kidney protective strategies are needed to reduce the burden of complete kidney failure from chronic kidney disease (CKD). Clinicians sometimes use protein restriction as kidney protection despite its demonstrated lack of effectiveness in the only large-scale study. Small-scale studies support that dietary acid reduction is kidney-protective, including when done with base-inducing foods like fruits and vegetables. We review these studies in light of current kidney-protective recommendations. Animal models of CKD show that acid-inducing dietary protein exacerbates and base-inducing protein ameliorates nephropathy progression, and that increased intake of acid-inducing but not base-inducing dietary protein exacerbates progression. Clinical studies show that dietary acid reduction with Na-based alkali reduces kidney injury and slows nephropathy progression in patients with CKD and reduced glomerular filtration rate (GFR); base-inducing fruits and vegetables reduce kidney injury in patients with reduced GFR; and base-inducing fruits and vegetables improve metabolic acidosis in CKD. Protein type rather than amount might more importantly affect nephropathy progression. Base-inducing foods might be another way to reduce dietary acid, a strategy shown in small studies to slow nephropathy progression. Further studies will determine if CKD patients should be given base-inducing food as part of their management.

Recognizing protein–protein interfaces with empirical potentials and reduced amino acid alphabets

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Wodak Shoshana

2007-07-01

Full Text Available Abstract Background In structural genomics, an important goal is the detection and classification of protein–protein interactions, given the structures of the interacting partners. We have developed empirical energy functions to identify native structures of protein–protein complexes among sets of decoy structures. To understand the role of amino acid diversity, we parameterized a series of functions, using a hierarchy of amino acid alphabets of increasing complexity, with 2, 3, 4, 6, and 20 amino acid groups. Compared to previous work, we used the simplest possible functional form, with residue–residue interactions and a stepwise distance-dependence. We used increased computational ressources, however, constructing 290,000 decoys for 219 protein–protein complexes, with a realistic docking protocol where the protein partners are flexible and interact through a molecular mechanics energy function. The energy parameters were optimized to correctly assign as many native complexes as possible. To resolve the multiple minimum problem in parameter space, over 64000 starting parameter guesses were tried for each energy function. The optimized functions were tested by cross validation on subsets of our native and decoy structures, by blind tests on series of native and decoy structures available on the Web, and on models for 13 complexes submitted to the CAPRI structure prediction experiment. Results Performance is similar to several other statistical potentials of the same complexity. For example, the CAPRI target structure is correctly ranked ahead of 90% of its decoys in 6 cases out of 13. The hierarchy of amino acid alphabets leads to a coherent hierarchy of energy functions, with qualitatively similar parameters for similar amino acid types at all levels. Most remarkably, the performance with six amino acid classes is equivalent to that of the most detailed, 20-class energy function. Conclusion This suggests that six carefully chosen amino

Global optimization of proteins using a dynamical lattice model: Ground states and energy landscapes

OpenAIRE

Dressel, F.; Kobe, S.

2004-01-01

A simple approach is proposed to investigate the protein structure. Using a low complexity model, a simple pairwise interaction and the concept of global optimization, we are able to calculate ground states of proteins, which are in agreement with experimental data. All possible model structures of small proteins are available below a certain energy threshold. The exact lowenergy landscapes for the trp cage protein (1L2Y) is presented showing the connectivity of all states and energy barriers.

Protein structure modelling and evaluation based on a 4-distance description of side-chain interactions

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Inbar Yuval

2010-07-01

Full Text Available Abstract Background Accurate evaluation and modelling of residue-residue interactions within and between proteins is a key aspect of computational structure prediction including homology modelling, protein-protein docking, refinement of low-resolution structures, and computational protein design. Results Here we introduce a method for accurate protein structure modelling and evaluation based on a novel 4-distance description of residue-residue interaction geometry. Statistical 4-distance preferences were extracted from high-resolution protein structures and were used as a basis for a knowledge-based potential, called Hunter. We demonstrate that 4-distance description of side chain interactions can be used reliably to discriminate the native structure from a set of decoys. Hunter ranked the native structure as the top one in 217 out of 220 high-resolution decoy sets, in 25 out of 28 "Decoys 'R' Us" decoy sets and in 24 out of 27 high-resolution CASP7/8 decoy sets. The same concept was applied to side chain modelling in protein structures. On a set of very high-resolution protein structures the average RMSD was 1.47 Å for all residues and 0.73 Å for buried residues, which is in the range of attainable accuracy for a model. Finally, we show that Hunter performs as good or better than other top methods in homology modelling based on results from the CASP7 experiment. The supporting web site http://bioinfo.weizmann.ac.il/hunter/ was developed to enable the use of Hunter and for visualization and interactive exploration of 4-distance distributions. Conclusions Our results suggest that Hunter can be used as a tool for evaluation and for accurate modelling of residue-residue interactions in protein structures. The same methodology is applicable to other areas involving high-resolution modelling of biomolecules.

Modeling of allergen proteins found in sea food products

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Nataly Galán-Freyle

2012-06-01

Full Text Available Shellfish are a source of food allergens, and their consumption is the cause of severe allergic reactions in humans. Tropomyosins, a family of muscle proteins, have been identified as the major allergens in shellfish and mollusks species. Nevertheless, few experimentally determined three-dimensional structures are available in the Protein Data Base (PDB. In this study, 3D models of several homologous of tropomyosins present in marine shellfish and mollusk species (Chaf 1, Met e1, Hom a1, Per v1, and Pen a1 were constructed, validated, and their immunoglobulin E binding epitopes were identified using bioinformatics tools. All protein models for these allergens consisted of long alpha-helices. Chaf 1, Met e1, and Hom a1 had six conserved regions with sequence similarities to known epitopes, whereas Per v1 and Pen a1 contained only one. Lipophilic potentials of identified epitopes revealed a high propensity of hydrophobic amino acids in the immunoglobulin E binding site. This information could be useful to design tropomyosin-specific immunotherapy for sea food allergies.

Subchronic nandrolone administration reduces cardiac oxidative markers during restraint stress by modulating protein expression patterns.

Science.gov (United States)

Pergolizzi, Barbara; Carriero, Vitina; Abbadessa, Giuliana; Penna, Claudia; Berchialla, Paola; De Francia, Silvia; Bracco, Enrico; Racca, Silvia

2017-10-01

Nandrolone decanoate (ND), an anabolic-androgenic steroid prohibited in collegiate and professional sports, is associated with detrimental cardiovascular effects through redox-dependent mechanisms. We previously observed that high-dose short-term ND administration (15 mg/kg for 2 weeks) did not induce left heart ventricular hypertrophy and, paradoxically, improved postischemic response, whereas chronic ND treatment (5 mg/kg twice a week for 10 weeks) significantly reduced the cardioprotective effect of postconditioning, with an increase in infarct size and a decrease in cardiac performance. We wanted to determine whether short-term ND administration could affect the oxidative redox status in animals exposed to acute restraint stress. Our hypothesis was that, depending on treatment schedule, ND may have a double-edged sword effect. Measurement of malondialdehyde and 4-hydroxynonenal, two oxidative stress markers, in rat plasma and left heart ventricular tissue, revealed that the levels of both markers were increased in animals exposed to restraint stress, whereas no increase in marker levels was noted in animals pretreated with ND, indicating a possible protective action of ND against stress-induced oxidative damage. Furthermore, isolation and identification of proteins extracted from the left heart ventricular tissue samples of rats pretreated or not with ND and exposed to acute stress showed a prevalent expression of enzymes involved in amino acid synthesis and energy metabolism. Among other proteins, peroxiredoxin 6 and alpha B-crystallin, both involved in the oxidative stress response, were predominantly expressed in the left heart ventricular tissues of the ND-pretreated rats. In conclusion, ND seems to reduce oxidative stress by inducing the expression of antioxidant proteins in the hearts of restraint-stressed animals, thus contributing to amelioration of postischemic heart performance.

Model to predict inhomogeneous protein-sugar distribution in powders prepared by spray drying

NARCIS (Netherlands)

Grasmeijer, Niels; Frijlink, Henderik W.; Hinrichs, Wouter L. J.

2016-01-01

A protein can be stabilized by spray drying an aqueous solution of the protein and a sugar, thereby incorporating the protein into a glassy sugar matrix. For optimal stability, the protein should be homogeneously distributed inside the sugar matrix. The aim of this study was to develop a model that

Animal Models of Congenital Cardiomyopathies Associated With Mutations in Z-Line Proteins.

Science.gov (United States)

Bang, Marie-Louise

2017-01-01

The cardiac Z-line at the boundary between sarcomeres is a multiprotein complex connecting the contractile apparatus with the cytoskeleton and the extracellular matrix. The Z-line is important for efficient force generation and transmission as well as the maintenance of structural stability and integrity. Furthermore, it is a nodal point for intracellular signaling, in particular mechanosensing and mechanotransduction. Mutations in various genes encoding Z-line proteins have been associated with different cardiomyopathies, including dilated cardiomyopathy, hypertrophic cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy, restrictive cardiomyopathy, and left ventricular noncompaction, and mutations even within the same gene can cause widely different pathologies. Animal models have contributed to a great advancement in the understanding of the physiological function of Z-line proteins and the pathways leading from mutations in Z-line proteins to cardiomyopathy, although genotype-phenotype prediction remains a great challenge. This review presents an overview of the currently available animal models for Z-line and Z-line associated proteins involved in human cardiomyopathies with special emphasis on knock-in and transgenic mouse models recapitulating the clinical phenotypes of human cardiomyopathy patients carrying mutations in Z-line proteins. Pros and cons of mouse models will be discussed and a future outlook will be given. J. Cell. Physiol. 232: 38-52, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Mixing Energy Models in Genetic Algorithms for On-Lattice Protein Structure Prediction

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Mahmood A. Rashid

2013-01-01

Full Text Available Protein structure prediction (PSP is computationally a very challenging problem. The challenge largely comes from the fact that the energy function that needs to be minimised in order to obtain the native structure of a given protein is not clearly known. A high resolution 20×20 energy model could better capture the behaviour of the actual energy function than a low resolution energy model such as hydrophobic polar. However, the fine grained details of the high resolution interaction energy matrix are often not very informative for guiding the search. In contrast, a low resolution energy model could effectively bias the search towards certain promising directions. In this paper, we develop a genetic algorithm that mainly uses a high resolution energy model for protein structure evaluation but uses a low resolution HP energy model in focussing the search towards exploring structures that have hydrophobic cores. We experimentally show that this mixing of energy models leads to significant lower energy structures compared to the state-of-the-art results.

Altered protein glycosylation predicts Alzheimer's disease and modulates its pathology in disease model Drosophila.