Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

Science.gov (United States)

In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

Concept mapping learning strategy to enhance students' mathematical connection ability

Science.gov (United States)

Hafiz, M.; Kadir, Fatra, Maifalinda

2017-05-01

The concept mapping learning strategy in teaching and learning mathematics has been investigated by numerous researchers. However, there are still less researchers who have scrutinized about the roles of map concept which is connected to the mathematical connection ability. Being well understood on map concept, it may help students to have ability to correlate one concept to other concept in order that the student can solve mathematical problems faced. The objective of this research was to describe the student's mathematical connection ability and to analyze the effect of using concept mapping learning strategy to the students' mathematical connection ability. This research was conducted at senior high school in Jakarta. The method used a quasi-experimental with randomized control group design with the total number was 72 students as the sample. Data obtained through using test in the post-test after giving the treatment. The results of the research are: 1) Students' mathematical connection ability has reached the good enough level category; 2) Students' mathematical connection ability who had taught with concept mapping learning strategy is higher than who had taught with conventional learning strategy. Based on the results above, it can be concluded that concept mapping learning strategycould enhance the students' mathematical connection ability, especially in trigonometry.

Knowledge synthesis with maps of neural connectivity.

Science.gov (United States)

Tallis, Marcelo; Thompson, Richard; Russ, Thomas A; Burns, Gully A P C

2011-01-01

This paper describes software for neuroanatomical knowledge synthesis based on neural connectivity data. This software supports a mature methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus, and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macro connections using the Swanson third edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the data mapping components within a unified web-application. As a step toward developing an accurate sub-regional account of neural connectivity, we provide navigational access between the data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called "Knowledge Engineering from Experimental Design" (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web-application that allows anatomical data sets to be described within a standard experimental context and thus indexed by non-spatial experimental design features.

Determining protein complex connectivity using a probabilistic deletion network derived from quantitative proteomics.

Science.gov (United States)

Sardiu, Mihaela E; Gilmore, Joshua M; Carrozza, Michael J; Li, Bing; Workman, Jerry L; Florens, Laurence; Washburn, Michael P

2009-10-06

Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.

The Ser/Thr Protein Kinase Protein-Protein Interaction Map of M. tuberculosis.

Science.gov (United States)

Wu, Fan-Lin; Liu, Yin; Jiang, He-Wei; Luan, Yi-Zhao; Zhang, Hai-Nan; He, Xiang; Xu, Zhao-Wei; Hou, Jing-Li; Ji, Li-Yun; Xie, Zhi; Czajkowsky, Daniel M; Yan, Wei; Deng, Jiao-Yu; Bi, Li-Jun; Zhang, Xian-En; Tao, Sheng-Ce

2017-08-01

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, the leading cause of death among all infectious diseases. There are 11 eukaryotic-like serine/threonine protein kinases (STPKs) in Mtb, which are thought to play pivotal roles in cell growth, signal transduction and pathogenesis. However, their underlying mechanisms of action remain largely uncharacterized. In this study, using a Mtb proteome microarray, we have globally identified the binding proteins in Mtb for all of the STPKs, and constructed the first STPK protein interaction (KPI) map that includes 492 binding proteins and 1,027 interactions. Bioinformatics analysis showed that the interacting proteins reflect diverse functions, including roles in two-component system, transcription, protein degradation, and cell wall integrity. Functional investigations confirmed that PknG regulates cell wall integrity through key components of peptidoglycan (PG) biosynthesis, e.g. MurC. The global STPK-KPIs network constructed here is expected to serve as a rich resource for understanding the key signaling pathways in Mtb, thus facilitating drug development and effective control of Mtb. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Drug-induced regulation of target expression

DEFF Research Database (Denmark)

Iskar, Murat; Campillos, Monica; Kuhn, Michael

2010-01-01

Drug perturbations of human cells lead to complex responses upon target binding. One of the known mechanisms is a (positive or negative) feedback loop that adjusts the expression level of the respective target protein. To quantify this mechanism systems-wide in an unbiased way, drug......-induced differential expression of drug target mRNA was examined in three cell lines using the Connectivity Map. To overcome various biases in this valuable resource, we have developed a computational normalization and scoring procedure that is applicable to gene expression recording upon heterogeneous drug treatments....... In 1290 drug-target relations, corresponding to 466 drugs acting on 167 drug targets studied, 8% of the targets are subject to regulation at the mRNA level. We confirmed systematically that in particular G-protein coupled receptors, when serving as known targets, are regulated upon drug treatment. We...

Knowledge synthesis with maps of neural connectivity

Directory of Open Access Journals (Sweden)

Marcelo eTallis

2011-11-01

Full Text Available This paper describes software for neuroanatomical knowledge synthesis based on high-quality neural connectivity data. This software supports a mature neuroanatomical methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macroconnections using the Swanson 3rd edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the neuroanatomical data mapping components within a unified web-application. As a step towards developing an accurate sub-regional account of neural connectivity, we provide navigational access between the neuroanatomical data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called ’Knowledge Engineering from Experimental Design’ (KEfED model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web application that allows anatomical data sets to be described within a standard experimental context and thus incorporated with non-spatial data sets.

Residue preference mapping of ligand fragments in the Protein Data Bank.

Science.gov (United States)

Wang, Lirong; Xie, Zhaojun; Wipf, Peter; Xie, Xiang-Qun

2011-04-25

The interaction between small molecules and proteins is one of the major concerns for structure-based drug design because the principles of protein-ligand interactions and molecular recognition are not thoroughly understood. Fortunately, the analysis of protein-ligand complexes in the Protein Data Bank (PDB) enables unprecedented possibilities for new insights. Herein, we applied molecule-fragmentation algorithms to split the ligands extracted from PDB crystal structures into small fragments. Subsequently, we have developed a ligand fragment and residue preference mapping (LigFrag-RPM) algorithm to map the profiles of the interactions between these fragments and the 20 proteinogenic amino acid residues. A total of 4032 fragments were generated from 71 798 PDB ligands by a ring cleavage (RC) algorithm. Among these ligand fragments, 315 unique fragments were characterized with the corresponding fragment-residue interaction profiles by counting residues close to these fragments. The interaction profiles revealed that these fragments have specific preferences for certain types of residues. The applications of these interaction profiles were also explored and evaluated in case studies, showing great potential for the study of protein-ligand interactions and drug design. Our studies demonstrated that the fragment-residue interaction profiles generated from the PDB ligand fragments can be used to detect whether these fragments are in their favorable or unfavorable environments. The algorithm for a ligand fragment and residue preference mapping (LigFrag-RPM) developed here also has the potential to guide lead chemistry modifications as well as binding residues predictions.

Determining protein complex connectivity using a probabilistic deletion network derived from quantitative proteomics.

Directory of Open Access Journals (Sweden)

Mihaela E Sardiu

2009-10-01

Full Text Available Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.

Protein-Based Drug-Delivery Materials

Directory of Open Access Journals (Sweden)

Dave Jao

2017-05-01

Full Text Available There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood circulation to their molecular site of action. Protein-based polymers compared to synthetic polymers have the advantages of good biocompatibility, biodegradability, environmental sustainability, cost effectiveness and availability. This review addresses the sources of protein-based polymers, compares the similarity and differences, and highlights characteristic properties and functionality of these protein materials for sustained and controlled drug release. Targeted drug delivery using highly functional multicomponent protein composites to guide active drugs to the site of interest will also be discussed. A systematical elucidation of drug-delivery efficiency in the case of molecular weight, particle size, shape, morphology, and porosity of materials will then be demonstrated to achieve increased drug absorption. Finally, several important biomedical applications of protein-based materials with drug-delivery function—including bone healing, antibiotic release, wound healing, and corneal regeneration, as well as diabetes, neuroinflammation and cancer treatments—are summarized at the end of this review.

A Global Map of Lipid-Binding Proteins and Their Ligandability in Cells.

Science.gov (United States)

Niphakis, Micah J; Lum, Kenneth M; Cognetta, Armand B; Correia, Bruno E; Ichu, Taka-Aki; Olucha, Jose; Brown, Steven J; Kundu, Soumajit; Piscitelli, Fabiana; Rosen, Hugh; Cravatt, Benjamin F

2015-06-18

Lipids play central roles in physiology and disease, where their structural, metabolic, and signaling functions often arise from interactions with proteins. Here, we describe a set of lipid-based chemical proteomic probes and their global interaction map in mammalian cells. These interactions involve hundreds of proteins from diverse functional classes and frequently occur at sites of drug action. We determine the target profiles for several drugs across the lipid-interaction proteome, revealing that its ligandable content extends far beyond traditionally defined categories of druggable proteins. In further support of this finding, we describe a selective ligand for the lipid-binding protein nucleobindin-1 (NUCB1) and show that this compound perturbs the hydrolytic and oxidative metabolism of endocannabinoids in cells. The described chemical proteomic platform thus provides an integrated path to both discover and pharmacologically characterize a wide range of proteins that participate in lipid pathways in cells. Copyright © 2015 Elsevier Inc. All rights reserved.

Nanostructures for protein drug delivery.

Science.gov (United States)

Pachioni-Vasconcelos, Juliana de Almeida; Lopes, André Moreni; Apolinário, Alexsandra Conceição; Valenzuela-Oses, Johanna Karina; Costa, Juliana Souza Ribeiro; Nascimento, Laura de Oliveira; Pessoa, Adalberto; Barbosa, Leandro Ramos Souza; Rangel-Yagui, Carlota de Oliveira

2016-02-01

Use of nanoscale devices as carriers for drugs and imaging agents has been extensively investigated and successful examples can already be found in therapy. In parallel, recombinant DNA technology together with molecular biology has opened up numerous possibilities for the large-scale production of many proteins of pharmaceutical interest, reflecting in the exponentially growing number of drugs of biotechnological origin. When we consider protein drugs, however, there are specific criteria to take into account to select adequate nanostructured systems as drug carriers. In this review, we highlight the main features, advantages, drawbacks and recent developments of nanostructures for protein encapsulation, such as nanoemulsions, liposomes, polymersomes, single-protein nanocapsules and hydrogel nanoparticles. We also discuss the importance of nanoparticle stabilization, as well as future opportunities and challenges in nanostructures for protein drug delivery.

Protein complex prediction based on k-connected subgraphs in protein interaction network

Directory of Open Access Journals (Sweden)

Habibi Mahnaz

2010-09-01

Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

A posteriori model validation for the temporal order of directed functional connectivity maps.

Science.gov (United States)

Beltz, Adriene M; Molenaar, Peter C M

2015-01-01

A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates) and substantive implications (e.g., higher order lags may be common in resting state data).

A posteriori model validation for the temporal order of directed functional connectivity maps

Directory of Open Access Journals (Sweden)

Adriene M. Beltz

2015-08-01

Full Text Available A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests, and (b to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates and substantive implications (e.g., higher order lags may be common in resting state data.

Genomes2Drugs: identifies target proteins and lead drugs from proteome data.

LENUS (Irish Health Repository)

Toomey, David

2009-01-01

BACKGROUND: Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins\\/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and\\/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. METHODOLOGY\\/PRINCIPAL FINDINGS: To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i) homologous to previously crystallized proteins or (ii) targets of known drugs, but are (iii) not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. CONCLUSIONS\\/SIGNIFICANCE: Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under \\'change-of-application\\' patents.

Genomes2Drugs: identifies target proteins and lead drugs from proteome data.

Directory of Open Access Journals (Sweden)

David Toomey

Full Text Available BACKGROUND: Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. METHODOLOGY/PRINCIPAL FINDINGS: To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i homologous to previously crystallized proteins or (ii targets of known drugs, but are (iii not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. CONCLUSIONS/SIGNIFICANCE: Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under 'change-of-application' patents.

Charting Monosynaptic Connectivity Maps by Two-Color Light-Sheet Fluorescence Microscopy

Directory of Open Access Journals (Sweden)

Christian J. Niedworok

2012-11-01

Full Text Available Cellular resolution three-dimensional (3D visualization of defined, fluorescently labeled long-range neuronal networks in the uncut adult mouse brain has been elusive. Here, a virus-based strategy is described that allowed fluorescent labeling of centrifugally projecting neuronal populations in the ventral forebrain and their directly, monosynaptically connected bulbar interneurons upon a single stereotaxic injection into select neuronal populations. Implementation of improved tissue clearing combined with light-sheet fluorescence microscopy permitted imaging of the resulting connectivity maps in a single whole-brain scan. Subsequent 3D reconstructions revealed the exact distribution of the diverse neuronal ensembles monosynaptically connected with distinct bulbar interneuron populations. Moreover, rehydratation of brains after light-sheet fluorescence imaging enabled the immunohistochemical identification of synaptically connected neurons. Thus, this study describes a method for identifying monosynaptic connectivity maps from distinct, virally labeled neuronal populations that helps in better understanding of information flow in neural systems.

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sánchez Claros, Carmen

2012-06-08

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sá nchez Claros, Carmen; Tramontano, Anna

2012-01-01

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

A mapping of drug space from the viewpoint of small molecule metabolism.

Directory of Open Access Journals (Sweden)

James Corey Adams

2009-08-01

Full Text Available Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the "effect space" comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism.

A mapping of drug space from the viewpoint of small molecule metabolism.

Science.gov (United States)

Adams, James Corey; Keiser, Michael J; Basuino, Li; Chambers, Henry F; Lee, Deok-Sun; Wiest, Olaf G; Babbitt, Patricia C

2009-08-01

Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the "effect space" comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism.

Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis.

Directory of Open Access Journals (Sweden)

Rohit Vashisht

Full Text Available A decade since the availability of Mycobacterium tuberculosis (Mtb genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative 'Connect to Decode' (C2D to generate the first and largest manually curated interactome of Mtb termed 'interactome pathway' (IPW, encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

Science.gov (United States)

Rohira, Harsha; Bhat, Ashwini G.; Passi, Anurag; Mukherjee, Keya; Choudhary, Kumari Sonal; Kumar, Vikas; Arora, Anshula; Munusamy, Prabhakaran; Subramanian, Ahalyaa; Venkatachalam, Aparna; S, Gayathri; Raj, Sweety; Chitra, Vijaya; Verma, Kaveri; Zaheer, Salman; J, Balaganesh; Gurusamy, Malarvizhi; Razeeth, Mohammed; Raja, Ilamathi; Thandapani, Madhumohan; Mevada, Vishal; Soni, Raviraj; Rana, Shruti; Ramanna, Girish Muthagadhalli; Raghavan, Swetha; Subramanya, Sunil N.; Kholia, Trupti; Patel, Rajesh; Bhavnani, Varsha; Chiranjeevi, Lakavath; Sengupta, Soumi; Singh, Pankaj Kumar; Atray, Naresh; Gandhi, Swati; Avasthi, Tiruvayipati Suma; Nisthar, Shefin; Anurag, Meenakshi; Sharma, Pratibha; Hasija, Yasha; Dash, Debasis; Sharma, Arun; Scaria, Vinod; Thomas, Zakir; Chandra, Nagasuma; Brahmachari, Samir K.; Bhardwaj, Anshu

2012-01-01

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative ‘Connect to Decode’ (C2D) to generate the first and largest manually curated interactome of Mtb termed ‘interactome pathway’ (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach. PMID:22808064

EST2Prot: Mapping EST sequences to proteins

Directory of Open Access Journals (Sweden)

Lin David M

2006-03-01

Full Text Available Abstract Background EST libraries are used in various biological studies, from microarray experiments to proteomic and genetic screens. These libraries usually contain many uncharacterized ESTs that are typically ignored since they cannot be mapped to known genes. Consequently, new discoveries are possibly overlooked. Results We describe a system (EST2Prot that uses multiple elements to map EST sequences to their corresponding protein products. EST2Prot uses UniGene clusters, substring analysis, information about protein coding regions in existing DNA sequences and protein database searches to detect protein products related to a query EST sequence. Gene Ontology terms, Swiss-Prot keywords, and protein similarity data are used to map the ESTs to functional descriptors. Conclusion EST2Prot extends and significantly enriches the popular UniGene mapping by utilizing multiple relations between known biological entities. It produces a mapping between ESTs and proteins in real-time through a simple web-interface. The system is part of the Biozon database and is accessible at http://biozon.org/tools/est/.

CellMap visualizes protein-protein interactions and subcellular localization

Science.gov (United States)

Dallago, Christian; Goldberg, Tatyana; Andrade-Navarro, Miguel Angel; Alanis-Lobato, Gregorio; Rost, Burkhard

2018-01-01

Many tools visualize protein-protein interaction (PPI) networks. The tool introduced here, CellMap, adds one crucial novelty by visualizing PPI networks in the context of subcellular localization, i.e. the location in the cell or cellular component in which a PPI happens. Users can upload images of cells and define areas of interest against which PPIs for selected proteins are displayed (by default on a cartoon of a cell). Annotations of localization are provided by the user or through our in-house database. The visualizer and server are written in JavaScript, making CellMap easy to customize and to extend by researchers and developers. PMID:29497493

Mapping cell-specific functional connections in the mouse brain using ChR2-evoked hemodynamics (Conference Presentation)

Science.gov (United States)

Bauer, Adam Q.; Kraft, Andrew; Baxter, Grant A.; Bruchas, Michael; Lee, Jin-Moo; Culver, Joseph P.

2017-02-01

Functional magnetic resonance imaging (fMRI) has transformed our understanding of the brain's functional organization. However, mapping subunits of a functional network using hemoglobin alone presents several disadvantages. Evoked and spontaneous hemodynamic fluctuations reflect ensemble activity from several populations of neurons making it difficult to discern excitatory vs inhibitory network activity. Still, blood-based methods of brain mapping remain powerful because hemoglobin provides endogenous contrast in all mammalian brains. To add greater specificity to hemoglobin assays, we integrated optical intrinsic signal(OIS) imaging with optogenetic stimulation to create an Opto-OIS mapping tool that combines the cell-specificity of optogenetics with label-free, hemoglobin imaging. Before mapping, titrated photostimuli determined which stimulus parameters elicited linear hemodynamic responses in the cortex. Optimized stimuli were then scanned over the left hemisphere to create a set of optogenetically-defined effective connectivity (Opto-EC) maps. For many sites investigated, Opto-EC maps exhibited higher spatial specificity than those determined using spontaneous hemodynamic fluctuations. For example, resting-state functional connectivity (RS-FC) patterns exhibited widespread ipsilateral connectivity while Opto-EC maps contained distinct short- and long-range constellations of ipsilateral connectivity. Further, RS-FC maps were usually symmetric about midline while Opto-EC maps displayed more heterogeneous contralateral homotopic connectivity. Both Opto-EC and RS-FC patterns were compared to mouse connectivity data from the Allen Institute. Unlike RS-FC maps, Thy1-based maps collected in awake, behaving mice closely recapitulated the connectivity structure derived using ex vivo anatomical tracer methods. Opto-OIS mapping could be a powerful tool for understanding cellular and molecular contributions to network dynamics and processing in the mouse brain.

Mapping Protein-Protein Interactions by Quantitative Proteomics

DEFF Research Database (Denmark)

Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy

2010-01-01

spectrometry (MS)-based proteomics in combination with affinity purification protocols has become the method of choice to map and track the dynamic changes in protein-protein interactions, including the ones occurring during cellular signaling events. Different quantitative MS strategies have been used...... to characterize protein interaction networks. In this chapter we describe in detail the use of stable isotope labeling by amino acids in cell culture (SILAC) for the quantitative analysis of stimulus-dependent dynamic protein interactions.......Proteins exert their function inside a cell generally in multiprotein complexes. These complexes are highly dynamic structures changing their composition over time and cell state. The same protein may thereby fulfill different functions depending on its binding partners. Quantitative mass...

Properties of Protein Drug Target Classes

Science.gov (United States)

Bull, Simon C.; Doig, Andrew J.

2015-01-01

Accurate identification of drug targets is a crucial part of any drug development program. We mined the human proteome to discover properties of proteins that may be important in determining their suitability for pharmaceutical modulation. Data was gathered concerning each protein’s sequence, post-translational modifications, secondary structure, germline variants, expression profile and drug target status. The data was then analysed to determine features for which the target and non-target proteins had significantly different values. This analysis was repeated for subsets of the proteome consisting of all G-protein coupled receptors, ion channels, kinases and proteases, as well as proteins that are implicated in cancer. Machine learning was used to quantify the proteins in each dataset in terms of their potential to serve as a drug target. This was accomplished by first inducing a random forest that could distinguish between its targets and non-targets, and then using the random forest to quantify the drug target likeness of the non-targets. The properties that can best differentiate targets from non-targets were primarily those that are directly related to a protein’s sequence (e.g. secondary structure). Germline variants, expression levels and interactions between proteins had minimal discriminative power. Overall, the best indicators of drug target likeness were found to be the proteins’ hydrophobicities, in vivo half-lives, propensity for being membrane bound and the fraction of non-polar amino acids in their sequences. In terms of predicting potential targets, datasets of proteases, ion channels and cancer proteins were able to induce random forests that were highly capable of distinguishing between targets and non-targets. The non-target proteins predicted to be targets by these random forests comprise the set of the most suitable potential future drug targets, and should therefore be prioritised when building a drug development programme. PMID

Protein-Based Drug-Delivery Materials

OpenAIRE

Jao, Dave; Xue, Ye; Medina, Jethro; Hu, Xiao

2017-01-01

There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood circulation to their molecular site of action. Protein-based pol...

Computational brain connectivity mapping: A core health and scientific challenge.

Science.gov (United States)

Deriche, Rachid

2016-10-01

One third of the burden of all the diseases in Europe is due to problems caused by diseases affecting brain. Although exceptional progress have been obtained for exploring the brain during the past decades, it is still terra-incognita and calls for specific efforts in research to better understand its architecture and functioning. To take up this great challenge of modern science and to solve the limited view of the brain provided just by one imaging modality, this article advocates the idea developed in my research group of a global approach involving new generation of models for brain connectivity mapping and strong interactions between structural and functional connectivities. Capitalizing on the strengths of integrated and complementary non invasive imaging modalities such as diffusion Magnetic Resonance Imaging (dMRI) and Electro & Magneto-Encephalography (EEG & MEG) will contribute to achieve new frontiers for identifying and characterizing structural and functional brain connectivities and to provide a detailed mapping of the brain connectivity, both in space and time. Thus leading to an added clinical value for high impact diseases with new perspectives in computational neuro-imaging and cognitive neuroscience. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions.

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Su, Min-Gang; Weng, Julia Tzu-Ya; Hsu, Justin Bo-Kai; Huang, Kai-Yao; Chi, Yu-Hsiang; Lee, Tzong-Yi

2017-12-21

Protein post-translational modification (PTM) plays an essential role in various cellular processes that modulates the physical and chemical properties, folding, conformation, stability and activity of proteins, thereby modifying the functions of proteins. The improved throughput of mass spectrometry (MS) or MS/MS technology has not only brought about a surge in proteome-scale studies, but also contributed to a fruitful list of identified PTMs. However, with the increase in the number of identified PTMs, perhaps the more crucial question is what kind of biological mechanisms these PTMs are involved in. This is particularly important in light of the fact that most protein-based pharmaceuticals deliver their therapeutic effects through some form of PTM. Yet, our understanding is still limited with respect to the local effects and frequency of PTM sites near pharmaceutical binding sites and the interfaces of protein-protein interaction (PPI). Understanding PTM's function is critical to our ability to manipulate the biological mechanisms of protein. In this study, to understand the regulation of protein functions by PTMs, we mapped 25,835 PTM sites to proteins with available three-dimensional (3D) structural information in the Protein Data Bank (PDB), including 1785 modified PTM sites on the 3D structure. Based on the acquired structural PTM sites, we proposed to use five properties for the structural characterization of PTM substrate sites: the spatial composition of amino acids, residues and side-chain orientations surrounding the PTM substrate sites, as well as the secondary structure, division of acidity and alkaline residues, and solvent-accessible surface area. We further mapped the structural PTM sites to the structures of drug binding and PPI sites, identifying a total of 1917 PTM sites that may affect PPI and 3951 PTM sites associated with drug-target binding. An integrated analytical platform (CruxPTM), with a variety of methods and online molecular docking

Peptides, proteins and peptide/protein-polymer conjugates as drug delivery system.

Science.gov (United States)

Mukherjee, Biswajit; Karmakar, Swapna D; Hossain, Chowdhury M; Bhattacharya, Sanchari

2014-01-01

In the last few decades, novel drug delivery strategies have been a big priority to the formulation scientists. Peptides and proteins have drawn a special attention for their wide scope in the area. Serum albumin, transferrin, recom- binant proteins, virus capsids etc. are used as carrier for drug and biomolecules. Conjugates of polymers with proteins have also shown strong potency in the field of drug delivery. Polyethylene glycol is one of the most successful polymers that has been used extensively to develop protein conjugated formulations. Besides, polyvinyl pyrrolidone, polylactic-co- glycolic acid, N-(2-hydroxypropyl) methacrylamide copolymer, polyglutamic acid have also been investigated. In this re- view, we will highlight on the most recent overview of various advantages, limitations and marketed products of proteins, peptides and protein/peptide-polymer conjugates as drug carriers, such products in clinical trials and their various uses in the field of modern drug delivery. Understanding the key features of these materials and the vigorous research in this field will develop new drug formulations that will combat various types of life-threatening diseases.

Chimera states in networks of logistic maps with hierarchical connectivities

Science.gov (United States)

zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

2018-04-01

Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

State space modeling of time-varying contemporaneous and lagged relations in connectivity maps.

Science.gov (United States)

Molenaar, Peter C M; Beltz, Adriene M; Gates, Kathleen M; Wilson, Stephen J

2016-01-15

Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. Published by Elsevier Inc.

The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services

Directory of Open Access Journals (Sweden)

Hanspers Kristina

2010-01-01

Full Text Available Abstract Background Many complementary solutions are available for the identifier mapping problem. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. Results Here we present BridgeDb, a software framework for gene, protein and metabolite identifier mapping. This framework provides a standardized interface layer through which bioinformatics tools can be connected to different identifier mapping services. This approach makes it easier for tool developers to support identifier mapping. Mapping services can be combined or merged to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb provides its own ready-to-go mapping services, both in webservice and local database forms. However, the framework is intended for customization and adaptation to any identifier mapping service. BridgeDb has already been integrated into several bioinformatics applications. Conclusion By uncoupling bioinformatics tools from mapping services, BridgeDb improves capability and flexibility of those tools. All described software is open source and available at http://www.bridgedb.org.

Effects of Field-Map Distortion Correction on Resting State Functional Connectivity MRI

Directory of Open Access Journals (Sweden)

Hiroki Togo

2017-12-01

Full Text Available Magnetic field inhomogeneities cause geometric distortions of echo planar images used for functional magnetic resonance imaging (fMRI. To reduce this problem, distortion correction (DC with field map is widely used for both task and resting-state fMRI (rs-fMRI. Although DC with field map has been reported to improve the quality of task fMRI, little is known about its effects on rs-fMRI. Here, we tested the influence of field-map DC on rs-fMRI results using two rs-fMRI datasets derived from 40 healthy subjects: one with DC (DC+ and the other without correction (DC−. Independent component analysis followed by the dual regression approach was used for evaluation of resting-state functional connectivity networks (RSN. We also obtained the ratio of low-frequency to high-frequency signal power (0.01–0.1 Hz and above 0.1 Hz, respectively; LFHF ratio to assess the quality of rs-fMRI signals. For comparison of RSN between DC+ and DC− datasets, the default mode network showed more robust functional connectivity in the DC+ dataset than the DC− dataset. Basal ganglia RSN showed some decreases in functional connectivity primarily in white matter, indicating imperfect registration/normalization without DC. Supplementary seed-based and simulation analyses supported the utility of DC. Furthermore, we found a higher LFHF ratio after field map correction in the anterior cingulate cortex, posterior cingulate cortex, ventral striatum, and cerebellum. In conclusion, field map DC improved detection of functional connectivity derived from low-frequency rs-fMRI signals. We encourage researchers to include a DC step in the preprocessing pipeline of rs-fMRI analysis.

Clinical relevance of drug binding to plasma proteins

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Ascenzi, Paolo; Fanali, Gabriella; Fasano, Mauro; Pallottini, Valentina; Trezza, Viviana

2014-12-01

Binding to plasma proteins highly influences drug efficacy, distribution, and disposition. Serum albumin, the most abundant protein in plasma, is a monomeric multi-domain macromolecule that displays an extraordinary ligand binding capacity, providing a depot and carrier for many endogenous and exogenous compounds, such as fatty acids and most acidic drugs. α-1-Acid glycoprotein, the second main plasma protein, is a glycoprotein physiologically involved in the acute phase reaction and is the main carrier for basic and neutral drugs. High- and low-density lipoproteins play a limited role in drug binding and are natural drug delivery system only for few lipophilic drugs or lipid-based formulations. Several factors influence drug binding to plasma proteins, such as pathological conditions, concurrent administration of drugs, sex, and age. Any of these factors, in turn, influences drug efficacy and toxicity. Here, biochemical, biomedical, and biotechnological aspects of drug binding to plasma proteins are reviewed.

Protein Innovations Advance Drug Treatments, Skin Care

Science.gov (United States)

2012-01-01

Dan Carter carefully layered the sheets of tracing paper on the light box. On each sheet were renderings of the atomic components of an essential human protein, one whose structure had long been a mystery. With each layer Carter laid down, a never-before-seen image became clearer. Carter joined NASA s Marshall Space Flight Center in 1985 and began exploring processes of protein crystal growth in space. By bouncing intense X-rays off the crystals, researchers can determine the electron densities around the thousands of atoms forming the protein molecules, unveiling their atomic structures. Cultivating crystals of sufficient quality on Earth was problematic; the microgravity conditions of space were far more accommodating. At the time, only a few hundred protein structures had been mapped, and the methods were time consuming and tedious. Carter hoped his work would help reveal the structure of human serum albumin, a major protein in the human circulatory system responsible for ferrying numerous small molecules in the blood. More was at stake than scientific curiosity. Albumin has a high affinity for most of the world s pharmaceuticals, Carter explains, and its interaction with drugs can change their safety and efficacy. When a medication enters the bloodstream a cancer chemotherapy drug, for example a majority of it can bind with albumin, leaving only a small percentage active for treatment. How a drug interacts with albumin can influence considerations like the necessary effective dosage, playing a significant role in the design and application of therapeutic measures. In spite of numerous difficulties, including having no access to microgravity following the 1986 Space Shuttle Challenger disaster, the image Carter had hoped to see was finally clarifying. In 1988, his lab had acquired specialized X-ray and detection equipment a tipping point. Carter and his colleagues began to piece together albumin s portrait, the formation of its electron densities coalescing on

A side-effect free method for identifying cancer drug targets.

Science.gov (United States)

Ashraf, Md Izhar; Ong, Seng-Kai; Mujawar, Shama; Pawar, Shrikant; More, Pallavi; Paul, Somnath; Lahiri, Chandrajit

2018-04-27

Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.

On Attribute Thresholding and Data Mapping Functions in a Supervised Connected Component Segmentation Framework

Directory of Open Access Journals (Sweden)

Christoff Fourie

2015-06-01

Full Text Available Search-centric, sample supervised image segmentation has been demonstrated as a viable general approach applicable within the context of remote sensing image analysis. Such an approach casts the controlling parameters of image processing—generating segments—as a multidimensional search problem resolvable via efficient search methods. In this work, this general approach is analyzed in the context of connected component segmentation. A specific formulation of connected component labeling, based on quasi-flat zones, allows for the addition of arbitrary segment attributes to contribute to the nature of the output. This is in addition to core tunable parameters controlling the basic nature of connected components. Additional tunable constituents may also be introduced into such a framework, allowing flexibility in the definition of connected component connectivity, either directly via defining connectivity differently or via additional processes such as data mapping functions. The relative merits of these two additional constituents, namely the addition of tunable attributes and data mapping functions, are contrasted in a general remote sensing image analysis setting. Interestingly, tunable attributes in such a context, conjectured to be safely useful in general settings, were found detrimental under cross-validated conditions. This is in addition to this constituent’s requiring substantially greater computing time. Casting connectivity definitions as a searchable component, here via the utilization of data mapping functions, proved more beneficial and robust in this context. The results suggest that further investigations into such a general framework could benefit more from focusing on the aspects of data mapping and modifiable connectivity as opposed to the utility of thresholding various geometric and spectral attributes.

A global interaction network maps a wiring diagram of cellular function

Science.gov (United States)

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

2017-01-01

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

Microencapsulation of protein drugs for drug delivery: strategy, preparation, and applications.

Science.gov (United States)

Ma, Guanghui

2014-11-10

Bio-degradable poly(lactide) (PLA)/poly(lactide-glycolide) (PLGA) and chitosan microspheres (or microcapsules) have important applications in Drug Delivery Systems (DDS) of protein/peptide drugs. By encapsulating protein/peptide drugs in the microspheres, the serum drug concentration can be maintained at a higher constant value for a prolonged time, or injection formulation can be changed to orally or mucosally administered formulation. PLA/PLGA and chitosan are most often used in injection formulation and oral formulation. However, in the preparation and applications of PLA/PLGA and chitosan microspheres containing protein/peptide drugs, the problems of broad size distribution and poor reproducibility of microspheres, and deactivation of protein during the preparation, storage and release, are still big challenges. In this article, the techniques for control of the diameter of microspheres and microcapsules will be introduced at first, then the strategies about how to maintain the bioactivity of protein drugs during preparation and drug release will be reviewed and developed in our research group. The membrane emulsification techniques including direct membrane emulsification and rapid membrane emulsification processes were developed to prepare uniform-sized microspheres, the diameter of microspheres can be controlled from submicron to 100μm by these two processes, and the reproducibility of products can be guaranteed. Furthermore, compared with conventional stirring method, the big advantages of membrane emulsification process were that the uniform microspheres with much higher encapsulation efficiency can be obtained, and the release behavior can be adjusted by selecting microsphere size. Mild membrane emulsification condition also can prevent the deactivation of proteins, which frequently occurred under high shear force in mechanical stirring, sonification, and homogenization methods. The strategies for maintaining the bioactivity of protein drug were

Drosophila protein interaction map (DPiM): a paradigm for metazoan protein complex interactions.

Science.gov (United States)

Guruharsha, K G; Obar, Robert A; Mintseris, Julian; Aishwarya, K; Krishnan, R T; Vijayraghavan, K; Artavanis-Tsakonas, Spyros

2012-01-01

Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when, what and where of potential interactions, is therefore crucial to understanding the cellular function of any protein-especially those that have not been well studied by traditional molecular genetic approaches. We generated a large-scale resource of affinity-tagged expression-ready clones and used co-affinity purification combined with tandem mass-spectrometry to identify protein partners of nearly 5,000 Drosophila melanogaster proteins. The resulting protein complex "map" provided a blueprint of metazoan protein complex organization. Here we describe how the map has provided valuable insights into protein function in addition to generating hundreds of testable hypotheses. We also discuss recent technological advancements that will be critical in addressing the next generation of questions arising from the map.

Application of split-green fluorescent protein for topology mapping membrane proteins in Escherichia coli

DEFF Research Database (Denmark)

Toddo, Stephen; Soderstrom, Bill; Palombo, Isolde

2012-01-01

A topology map of a membrane protein defines the location of transmembrane helices and the orientation of soluble domains relative to the membrane. In the absence of a high-resolution structure, a topology map is an essential guide for studying structurefunction relationships. Although these maps....../periplasmic location of the N-terminus of a protein. Here, we show that the bimolecular split-green fluorescent protein complementation system can overcome this limitation and can be used to determine the location of both the N- and C-termini of inner membrane proteins in Escherichia coli....

Hot-spot analysis for drug discovery targeting protein-protein interactions.

Science.gov (United States)

Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

Mapping protein information to disease terminologies

Directory of Open Access Journals (Sweden)

Mottaz Anaïs

2007-12-01

Full Text Available In order to improve the accessibility of genomic and proteomic information to medical researchers, we have developed a procedure to link biological information on proteins involved in diseases to the MeSH and ICD-10 disease terminologies. For this purpose, we took advantage of the manually curated disease annotations in more than 2,000 human protein entries of the UniProt KnowledgeBase. We mapped disease names extracted from the entry comment lines or from the corresponding OMIM entry to the MeSH. The method was assessed on a benchmark set of 200 manually mapped disease comment lines. We obtained a recall of 54% for 91% precision. The same procedure was used to map the more than 3,000 diseases in Swiss-Prot to MeSH with comparable efficiency. Tested on ICD-10, the coverage of the mapped terms was lower, which could be explained by the coarse-grained structure of this terminology for hereditary disease description. The mapping is provided as supplementary material at http://research.isbsib.ch/unimed.

Highlighting landslides and other geomorphological features using sediment connectivity maps

Science.gov (United States)

Bossi, Giulia; Crema, Stefano; Cavalli, Marco; Marcato, Gianluca; Pasuto, Alessandro

2016-04-01

Landslide identification is usually made through interpreting geomorphological features in the field or with remote sensing imagery. In recent years, airborne laser scanning (LiDAR) has enhanced the potentiality of geomorphological investigations by providing a detailed and diffuse representation of the land surface. The development of algorithms for geomorphological analysis based on LiDAR derived high-resolution Digital Terrain Models (DTMs) is increasing. Among them, the sediment connectivity index (IC) has been used to quantify sediment dynamics in alpine catchments. In this work, maps of the sediment connectivity index are used for detecting geomorphological features and processes not exclusively related to water-laden processes or debris flows. The test area is located in the upper Passer Valley in South Tyrol (Italy). Here a 4 km2 Deep-seated Gravitational Slope Deformation (DGSD) with several secondary phenomena has been studied for years. The connectivity index was applied to a well-known study area in order to evaluate its effectiveness as an interpretative layer to assist geomorphological analysis. Results were cross checked with evidence previously identified by means of in situ investigations, photointerpretation and monitoring data. IC was applied to a 2.5 m LiDAR derived DTM using two different scenarios in order to test their effectiveness: i) IC derived on the hydrologically correct DTM; ii) IC derived on the original DTM. In the resulting maps a cluster of low-connectivity areas appears as the deformation of the DGSD induce a convexity in the central part of the phenomenon. The double crests, product of the sagging of the landslide, are extremely evident since in those areas the flow directions diverge from the general drainage pattern, which is directed towards the valley river. In the crown area a rock-slab that shows clear evidence of incumbent detachment is clearly highlighted since the maps emphasize the presence of traction trenches and

The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development.

Science.gov (United States)

Kunz, Meik; Liang, Chunguang; Nilla, Santosh; Cecil, Alexander; Dandekar, Thomas

2016-01-01

The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure-activity relationships.Database URL:http://drumpid.bioapps.biozentrum.uni-wuerzburg.de. © The Author(s) 2016. Published by Oxford University Press.

Peptide and protein delivery using new drug delivery systems.

Science.gov (United States)

Jain, Ashish; Jain, Aviral; Gulbake, Arvind; Shilpi, Satish; Hurkat, Pooja; Jain, Sanjay K

2013-01-01

Pharmaceutical and biotechnological research sorts protein drug delivery systems by importance based on their various therapeutic applications. The effective and potent action of the proteins/peptides makes them the drugs of choice for the treatment of numerous diseases. Major research issues in protein delivery include the stabilization of proteins in delivery devices and the design of appropriate target-specific protein carriers. Many efforts have been made for effective delivery of proteins/peptidal drugs through various routes of administrations for successful therapeutic effects. Nanoparticles made of biodegradable polymers such as poly lactic acid, polycaprolactone, poly(lactic-co-glycolic acid), the poly(fumaric-co-sebacic) anhydride chitosan, and modified chitosan, as well as solid lipids, have shown great potential in the delivery of proteins/peptidal drugs. Moreover, scientists also have used liposomes, PEGylated liposomes, niosomes, and aquasomes, among others, for peptidal drug delivery. They also have developed hydrogels and transdermal drug delivery systems for peptidal drug delivery. A receptor-mediated delivery system is another attractive strategy to overcome the limitation in drug absorption that enables the transcytosis of the protein across the epithelial barrier. Modification such as PEGnology is applied to various proteins and peptides of the desired protein and peptides also increases the circulating life, solubility and stability, pharmacokinetic properties, and antigenicity of protein. This review focuses on various approaches for effective protein/peptidal drug delivery, with special emphasis on insulin delivery.

Smarter Drugs: How Protein Crystallography Revolutionizes Drug Design

International Nuclear Information System (INIS)

Smith, Clyde

2005-01-01

According to Smith, protein crystallography allows scientists to design drugs in a much more efficient way than the standard methods traditionally used by large drug companies, which can cost close to a billion dollars and take 10 to 15 years. 'A lot of the work can be compressed down,' Smith said. Protein crystallography enables researchers to learn the structure of molecules involved in disease and health. Seeing the loops, folds and placement of atoms in anything from a virus to a healthy cell membrane gives important information about how these things work - and how to encourage, sidestep or stop their functions. Drug design can be much faster when the relationship between structure and function tells you what area of a molecule to target. Smith will use a timeline to illustrate the traditional methods of drug development and the new ways it can be done now. 'It is very exciting work. There have been some failures, but many successes too.' A new drug to combat the flu was developed in a year or so. Smith will tell us how. He will also highlight drugs developed to combat HIV, Tuberculosis, hypertension and Anthrax.

Characterization of particulate drug delivery systems for oral delivery of Peptide and protein drugs.

Science.gov (United States)

Christophersen, Philip Carsten; Fano, Mathias; Saaby, Lasse; Yang, Mingshi; Nielsen, Hanne Mørck; Mu, Huiling

2015-01-01

Oral drug delivery is a preferred route because of good patient compliance. However, most peptide/ protein drugs are delivered via parenteral routes because of the absorption barriers in the gastrointestinal (GI) tract such as enzymatic degradation by proteases and low permeability acrossthe biological membranes. To overcome these barriers, different formulation strategies for oral delivery of biomacromolecules have been proposed, including lipid based formulations and polymer-based particulate drug delivery systems (DDS). The aim of this review is to summarize the existing knowledge about oral delivery of peptide/protein drugs and to provide an overview of formulationand characterization strategies. For a better understanding of the challenges in oral delivery of peptide/protein drugs, the composition of GI fluids and the digestion processes of different kinds of excipients in the GI tract are summarized. Additionally, the paper provides an overview of recent studies on characterization of solid drug carriers for peptide/protein drugs, drug distribution in particles, drug release and stability in simulated GI fluids, as well as the absorption of peptide/protein drugs in cell-based models. The use of biorelevant media when applicable can increase the knowledge about the quality of DDS for oral protein delivery. Hopefully, the knowledge provided in this review will aid the establishment of improved biorelevant models capable of forecasting the performance of particulate DDS for oral peptide/protein delivery.

A global genetic interaction network maps a wiring diagram of cellular function.

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Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D; Pelechano, Vicent; Styles, Erin B; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F; Li, Sheena C; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; San Luis, Bryan-Joseph; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M; Moore, Claire L; Rosebrock, Adam P; Caudy, Amy A; Myers, Chad L; Andrews, Brenda; Boone, Charles

2016-09-23

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. Copyright © 2016, American Association for the Advancement of Science.

Mapping of Drug-like Chemical Universe with Reduced Complexity Molecular Frameworks.

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Kontijevskis, Aleksejs

2017-04-24

The emergence of the DNA-encoded chemical libraries (DEL) field in the past decade has attracted the attention of the pharmaceutical industry as a powerful mechanism for the discovery of novel drug-like hits for various biological targets. Nuevolution Chemetics technology enables DNA-encoded synthesis of billions of chemically diverse drug-like small molecule compounds, and the efficient screening and optimization of these, facilitating effective identification of drug candidates at an unprecedented speed and scale. Although many approaches have been developed by the cheminformatics community for the analysis and visualization of drug-like chemical space, most of them are restricted to the analysis of a maximum of a few millions of compounds and cannot handle collections of 10 8 -10 12 compounds typical for DELs. To address this big chemical data challenge, we developed the Reduced Complexity Molecular Frameworks (RCMF) methodology as an abstract and very general way of representing chemical structures. By further introducing RCMF descriptors, we constructed a global framework map of drug-like chemical space and demonstrated how chemical space occupied by multi-million-member drug-like Chemetics DNA-encoded libraries and virtual combinatorial libraries with >10 12 members could be analyzed and mapped without a need for library enumeration. We further validate the approach by performing RCMF-based searches in a drug-like chemical universe and mapping Chemetics library selection outputs for LSD1 targets on a global framework chemical space map.

Metabolic connectivity mapping reveals effective connectivity in the resting human brain.

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Riedl, Valentin; Utz, Lukas; Castrillón, Gabriel; Grimmer, Timo; Rauschecker, Josef P; Ploner, Markus; Friston, Karl J; Drzezga, Alexander; Sorg, Christian

2016-01-12

Directionality of signaling among brain regions provides essential information about human cognition and disease states. Assessing such effective connectivity (EC) across brain states using functional magnetic resonance imaging (fMRI) alone has proven difficult, however. We propose a novel measure of EC, termed metabolic connectivity mapping (MCM), that integrates undirected functional connectivity (FC) with local energy metabolism from fMRI and positron emission tomography (PET) data acquired simultaneously. This method is based on the concept that most energy required for neuronal communication is consumed postsynaptically, i.e., at the target neurons. We investigated MCM and possible changes in EC within the physiological range using "eyes open" versus "eyes closed" conditions in healthy subjects. Independent of condition, MCM reliably detected stable and bidirectional communication between early and higher visual regions. Moreover, we found stable top-down signaling from a frontoparietal network including frontal eye fields. In contrast, we found additional top-down signaling from all major clusters of the salience network to early visual cortex only in the eyes open condition. MCM revealed consistent bidirectional and unidirectional signaling across the entire cortex, along with prominent changes in network interactions across two simple brain states. We propose MCM as a novel approach for inferring EC from neuronal energy metabolism that is ideally suited to study signaling hierarchies in the brain and their defects in brain disorders.

High-Performance Signal Detection for Adverse Drug Events using MapReduce Paradigm.

Science.gov (United States)

Fan, Kai; Sun, Xingzhi; Tao, Ying; Xu, Linhao; Wang, Chen; Mao, Xianling; Peng, Bo; Pan, Yue

2010-11-13

Post-marketing pharmacovigilance is important for public health, as many Adverse Drug Events (ADEs) are unknown when those drugs were approved for marketing. However, due to the large number of reported drugs and drug combinations, detecting ADE signals by mining these reports is becoming a challenging task in terms of computational complexity. Recently, a parallel programming model, MapReduce has been introduced by Google to support large-scale data intensive applications. In this study, we proposed a MapReduce-based algorithm, for common ADE detection approach, Proportional Reporting Ratio (PRR), and tested it in mining spontaneous ADE reports from FDA. The purpose is to investigate the possibility of using MapReduce principle to speed up biomedical data mining tasks using this pharmacovigilance case as one specific example. The results demonstrated that MapReduce programming model could improve the performance of common signal detection algorithm for pharmacovigilance in a distributed computation environment at approximately liner speedup rates.

GenProBiS: web server for mapping of sequence variants to protein binding sites.

Science.gov (United States)

Konc, Janez; Skrlj, Blaz; Erzen, Nika; Kunej, Tanja; Janezic, Dusanka

2017-07-03

Discovery of potentially deleterious sequence variants is important and has wide implications for research and generation of new hypotheses in human and veterinary medicine, and drug discovery. The GenProBiS web server maps sequence variants to protein structures from the Protein Data Bank (PDB), and further to protein-protein, protein-nucleic acid, protein-compound, and protein-metal ion binding sites. The concept of a protein-compound binding site is understood in the broadest sense, which includes glycosylation and other post-translational modification sites. Binding sites were defined by local structural comparisons of whole protein structures using the Protein Binding Sites (ProBiS) algorithm and transposition of ligands from the similar binding sites found to the query protein using the ProBiS-ligands approach with new improvements introduced in GenProBiS. Binding site surfaces were generated as three-dimensional grids encompassing the space occupied by predicted ligands. The server allows intuitive visual exploration of comprehensively mapped variants, such as human somatic mis-sense mutations related to cancer and non-synonymous single nucleotide polymorphisms from 21 species, within the predicted binding sites regions for about 80 000 PDB protein structures using fast WebGL graphics. The GenProBiS web server is open and free to all users at http://genprobis.insilab.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Characterization of known protein complexes using k-connectivity and other topological measures

Science.gov (United States)

Gallagher, Suzanne R; Goldberg, Debra S

2015-01-01

Many protein complexes are densely packed, so proteins within complexes often interact with several other proteins in the complex. Steric constraints prevent most proteins from simultaneously binding more than a handful of other proteins, regardless of the number of proteins in the complex. Because of this, as complex size increases, several measures of the complex decrease within protein-protein interaction networks. However, k-connectivity, the number of vertices or edges that need to be removed in order to disconnect a graph, may be consistently high for protein complexes. The property of k-connectivity has been little used previously in the investigation of protein-protein interactions. To understand the discriminative power of k-connectivity and other topological measures for identifying unknown protein complexes, we characterized these properties in known Saccharomyces cerevisiae protein complexes in networks generated both from highly accurate X-ray crystallography experiments which give an accurate model of each complex, and also as the complexes appear in high-throughput yeast 2-hybrid studies in which new complexes may be discovered. We also computed these properties for appropriate random subgraphs.We found that clustering coefficient, mutual clustering coefficient, and k-connectivity are better indicators of known protein complexes than edge density, degree, or betweenness. This suggests new directions for future protein complex-finding algorithms. PMID:26913183

A rice kinase-protein interaction map.

Science.gov (United States)

Ding, Xiaodong; Richter, Todd; Chen, Mei; Fujii, Hiroaki; Seo, Young Su; Xie, Mingtang; Zheng, Xianwu; Kanrar, Siddhartha; Stevenson, Rebecca A; Dardick, Christopher; Li, Ying; Jiang, Hao; Zhang, Yan; Yu, Fahong; Bartley, Laura E; Chern, Mawsheng; Bart, Rebecca; Chen, Xiuhua; Zhu, Lihuang; Farmerie, William G; Gribskov, Michael; Zhu, Jian-Kang; Fromm, Michael E; Ronald, Pamela C; Song, Wen-Yuan

2009-03-01

Plants uniquely contain large numbers of protein kinases, and for the vast majority of the 1,429 kinases predicted in the rice (Oryza sativa) genome, little is known of their functions. Genetic approaches often fail to produce observable phenotypes; thus, new strategies are needed to delineate kinase function. We previously developed a cost-effective high-throughput yeast two-hybrid system. Using this system, we have generated a protein interaction map of 116 representative rice kinases and 254 of their interacting proteins. Overall, the resulting interaction map supports a large number of known or predicted kinase-protein interactions from both plants and animals and reveals many new functional insights. Notably, we found a potential widespread role for E3 ubiquitin ligases in pathogen defense signaling mediated by receptor-like kinases, particularly by the kinases that may have evolved from recently expanded kinase subfamilies in rice. We anticipate that the data provided here will serve as a foundation for targeted functional studies in rice and other plants. The application of yeast two-hybrid and TAPtag analyses for large-scale plant protein interaction studies is also discussed.

Symposium 20 - PABMB: Teaching biochemistry in a connected world: How Apps-Embedded Assessment can contribute to learning outcomes mapping

Directory of Open Access Journals (Sweden)

Eduardo Galembeck

2015-08-01

Full Text Available Symposium 20 - PABMB: Teaching biochemistry in a connected world Chair: Miguel Castanho, Universidade de Lisboa, PortugalAbstract:Apps can be designed to provide usage data, and most of them do. These usage data are usually used to map users interests and to deliver more effective ads that are more likely to result in clicks, and sales. We have applied some of these metrics to understand how it can be used to map students’ behavior using educational software. We tested both Google Analytics, and a system we have developed to map learning outcomes and students engagement. Embedded assessment were implemented in app used to teach: 1 Metabolic Pathways; 2 Protein Synthesis, 3 Cell Structure, and 4 Concepts from techniques used in a Biochemistry Lab course. Our preliminary results show that this approach provides valuable information about class outcomes that can be used for both summative and formative assessments.

IIS--Integrated Interactome System: a web-based platform for the annotation, analysis and visualization of protein-metabolite-gene-drug interactions by integrating a variety of data sources and tools.

Science.gov (United States)

Carazzolle, Marcelo Falsarella; de Carvalho, Lucas Miguel; Slepicka, Hugo Henrique; Vidal, Ramon Oliveira; Pereira, Gonçalo Amarante Guimarães; Kobarg, Jörg; Meirelles, Gabriela Vaz

2014-01-01

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

Science.gov (United States)

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping.

Science.gov (United States)

Chang, Meiping; Smith, Sarah; Thorpe, Andrew; Barratt, Michael J; Karim, Farzana

2010-09-16

We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model.

Systematic identification of proteins that elicit drug side effects

DEFF Research Database (Denmark)

Kuhn, Michael; Al Banchaabouchi, Mumna; Campillos, Monica

2013-01-01

Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins...... that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug-target relations to identify overrepresented protein-side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause......) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations....

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics.

Science.gov (United States)

O'Reilly, Paul G; Wen, Qing; Bankhead, Peter; Dunne, Philip D; McArt, Darragh G; McPherson, Suzanne; Hamilton, Peter W; Mills, Ken I; Zhang, Shu-Dong

2016-05-04

Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. We describe QUADrATiC ( http://go.qub.ac.uk/QUADrATiC ), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts. QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than

Bioengineered protein-based nanocage for drug delivery.

Science.gov (United States)

Lee, Eun Jung; Lee, Na Kyeong; Kim, In-San

2016-11-15

Nature, in its wonders, presents and assembles the most intricate and delicate protein structures and this remarkable phenomenon occurs in all kingdom and phyla of life. Of these proteins, cage-like multimeric proteins provide spatial control to biological processes and also compartmentalizes compounds that may be toxic or unstable and avoids their contact with the environment. Protein-based nanocages are of particular interest because of their potential applicability as drug delivery carriers and their perfect and complex symmetry and ideal physical properties, which have stimulated researchers to engineer, modify or mimic these qualities. This article reviews various existing types of protein-based nanocages that are used for therapeutic purposes, and outlines their drug-loading mechanisms and bioengineering strategies via genetic and chemical functionalization. Through a critical evaluation of recent advances in protein nanocage-based drug delivery in vitro and in vivo, an outlook for de novo and in silico nanocage design, and also protein-based nanocage preclinical and future clinical applications will be presented. Copyright © 2016 Elsevier B.V. All rights reserved.

InterMap3D: predicting and visualizing co-evolving protein residues

DEFF Research Database (Denmark)

Oliveira, Rodrigo Gouveia; Roque, francisco jose sousa simôes almeida; Wernersson, Rasmus

2009-01-01

InterMap3D predicts co-evolving protein residues and plots them on the 3D protein structure. Starting with a single protein sequence, InterMap3D automatically finds a set of homologous sequences, generates an alignment and fetches the most similar 3D structure from the Protein Data Bank (PDB......). It can also accept a user-generated alignment. Based on the alignment, co-evolving residues are then predicted using three different methods: Row and Column Weighing of Mutual Information, Mutual Information/Entropy and Dependency. Finally, InterMap3D generates high-quality images of the protein...

Protein Complex Production from the Drug Discovery Standpoint.

Science.gov (United States)

Moarefi, Ismail

2016-01-01

Small molecule drug discovery critically depends on the availability of meaningful in vitro assays to guide medicinal chemistry programs that are aimed at optimizing drug potency and selectivity. As it becomes increasingly evident, most disease relevant drug targets do not act as a single protein. In the body, they are instead generally found in complex with protein cofactors that are highly relevant for their correct function and regulation. This review highlights selected examples of the increasing trend to use biologically relevant protein complexes for rational drug discovery to reduce costly late phase attritions due to lack of efficacy or toxicity.

Targeted Delivery of Protein Drugs by Nanocarriers

Directory of Open Access Journals (Sweden)

Antonella Battisti

2010-03-01

Full Text Available Recent advances in biotechnology demonstrate that peptides and proteins are the basis of a new generation of drugs. However, the transportation of protein drugs in the body is limited by their high molecular weight, which prevents the crossing of tissue barriers, and by their short lifetime due to immuno response and enzymatic degradation. Moreover, the ability to selectively deliver drugs to target organs, tissues or cells is a major challenge in the treatment of several human diseases, including cancer. Indeed, targeted delivery can be much more efficient than systemic application, while improving bioavailability and limiting undesirable side effects. This review describes how the use of targeted nanocarriers such as nanoparticles and liposomes can improve the pharmacokinetic properties of protein drugs, thus increasing their safety and maximizing the therapeutic effect.

Large-scale prediction of drug-target interactions using protein sequences and drug topological structures

Energy Technology Data Exchange (ETDEWEB)

Cao Dongsheng [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China); Liu Shao [Xiangya Hospital, Central South University, Changsha 410008 (China); Xu Qingsong [School of Mathematical Sciences and Computing Technology, Central South University, Changsha 410083 (China); Lu Hongmei; Huang Jianhua [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China); Hu Qiannan [Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, and Wuhan University School of Pharmaceutical Sciences, Wuhan 430071 (China); Liang Yizeng, E-mail: yizeng_liang@263.net [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China)

2012-11-08

Highlights: Black-Right-Pointing-Pointer Drug-target interactions are predicted using an extended SAR methodology. Black-Right-Pointing-Pointer A drug-target interaction is regarded as an event triggered by many factors. Black-Right-Pointing-Pointer Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. Black-Right-Pointing-Pointer Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug-target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug-target interactions in a timely manner. In this article, we aim at extending current structure-activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug-target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug-target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug

Functionalization of protein-based nanocages for drug delivery applications.

Science.gov (United States)

Schoonen, Lise; van Hest, Jan C M

2014-07-07

Traditional drug delivery strategies involve drugs which are not targeted towards the desired tissue. This can lead to undesired side effects, as normal cells are affected by the drugs as well. Therefore, new systems are now being developed which combine targeting functionalities with encapsulation of drug cargo. Protein nanocages are highly promising drug delivery platforms due to their perfectly defined structures, biocompatibility, biodegradability and low toxicity. A variety of protein nanocages have been modified and functionalized for these types of applications. In this review, we aim to give an overview of different types of modifications of protein-based nanocontainers for drug delivery applications.

Brain functional connectivity in stimulant drug dependence and obsessive-compulsive disorder.

Science.gov (United States)

Meunier, David; Ersche, Karen D; Craig, Kevin J; Fornito, Alex; Merlo-Pich, Emilio; Fineberg, Naomi A; Shabbir, Shaila S; Robbins, Trevor W; Bullmore, Edward T

2012-01-16

There are reasons for thinking that obsessive-compulsive disorder (OCD) and drug dependence, although conventionally distinct diagnostic categories, might share important cognitive and neurobiological substrates. We tested this hypothesis directly by comparing brain functional connectivity measures between patients with OCD, stimulant dependent individuals (SDIs; many of whom were non-dependent users of other recreational drugs) and healthy volunteers. We measured functional connectivity between each possible pair of 506 brain regional functional MRI time series representing low frequency (0.03-0.06 Hz) spontaneous brain hemodynamics in healthy volunteers (N=18), patients with OCD (N=18) and SDIs (N=18). We used permutation tests to identify i) brain regions where strength of connectivity was significantly different in both patient groups compared to healthy volunteers; and ii) brain regions and connections which had significantly different functional connectivity between patient groups. We found that functional connectivity of right inferior and superior orbitofrontal cortex (OFC) was abnormally reduced in both disorders. Whether diagnosed as OCD or SDI, patients with higher scores on measures of compulsive symptom severity showed greater reductions of right orbitofrontal connectivity. Functional connections specifically between OFC and dorsal medial pre-motor and cingulate cortex were attenuated in both patient groups. However, patients with OCD demonstrated more severe and extensive reductions of functional connectivity compared to SDIs. OCD and stimulant dependence are not identical at the level of brain functional systems but they have some important abnormalities in common compared with healthy volunteers. Orbitofrontal connectivity may serve as a human brain systems biomarker for compulsivity across diagnostic categories. Copyright © 2011 Elsevier Inc. All rights reserved.

Protein Nanoparticles as Drug Delivery Carriers for Cancer Therapy

Directory of Open Access Journals (Sweden)

Warangkana Lohcharoenkal

2014-01-01

Full Text Available Nanoparticles have increasingly been used for a variety of applications, most notably for the delivery of therapeutic and diagnostic agents. A large number of nanoparticle drug delivery systems have been developed for cancer treatment and various materials have been explored as drug delivery agents to improve the therapeutic efficacy and safety of anticancer drugs. Natural biomolecules such as proteins are an attractive alternative to synthetic polymers which are commonly used in drug formulations because of their safety. In general, protein nanoparticles offer a number of advantages including biocompatibility and biodegradability. They can be prepared under mild conditions without the use of toxic chemicals or organic solvents. Moreover, due to their defined primary structure, protein-based nanoparticles offer various possibilities for surface modifications including covalent attachment of drugs and targeting ligands. In this paper, we review the most significant advancements in protein nanoparticle technology and their use in drug delivery arena. We then examine the various sources of protein materials that have been used successfully for the construction of protein nanoparticles as well as their methods of preparation. Finally, we discuss the applications of protein nanoparticles in cancer therapy.

Protein nanoparticles as drug delivery carriers for cancer therapy.

Science.gov (United States)

Lohcharoenkal, Warangkana; Wang, Liying; Chen, Yi Charlie; Rojanasakul, Yon

2014-01-01

Nanoparticles have increasingly been used for a variety of applications, most notably for the delivery of therapeutic and diagnostic agents. A large number of nanoparticle drug delivery systems have been developed for cancer treatment and various materials have been explored as drug delivery agents to improve the therapeutic efficacy and safety of anticancer drugs. Natural biomolecules such as proteins are an attractive alternative to synthetic polymers which are commonly used in drug formulations because of their safety. In general, protein nanoparticles offer a number of advantages including biocompatibility and biodegradability. They can be prepared under mild conditions without the use of toxic chemicals or organic solvents. Moreover, due to their defined primary structure, protein-based nanoparticles offer various possibilities for surface modifications including covalent attachment of drugs and targeting ligands. In this paper, we review the most significant advancements in protein nanoparticle technology and their use in drug delivery arena. We then examine the various sources of protein materials that have been used successfully for the construction of protein nanoparticles as well as their methods of preparation. Finally, we discuss the applications of protein nanoparticles in cancer therapy.

Protein Crystallography: A 'Must' Technology for Drug Design

International Nuclear Information System (INIS)

Matsuzaki, Takao

2004-01-01

The history of drug-related protein crystallography and drug design is reviewed to show that 'Lead Generation' is high-lighted in the pharmaceutical industry nowadays. A new drug design method has been developed. The method gave very high success rate; 10-60 % gave < 100 μM, 90 % gave < 10 mM. The crystal structures of drug-protein complexes have become even more important to give solid experimental bases for e.g. 1,000 designed structures and to find the new mechanisms of drug action

NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity.

Science.gov (United States)

Al-Awami, Ali K; Beyer, Johanna; Strobelt, Hendrik; Kasthuri, Narayanan; Lichtman, Jeff W; Pfister, Hanspeter; Hadwiger, Markus

2014-12-01

We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity

KAUST Repository

Al-Awami, Ali K.; Beyer, Johanna; Strobelt, Hendrik; Kasthuri, Narayanan; Lichtman, Jeff W.; Pfister, Hanspeter; Hadwiger, Markus

2014-01-01

We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity

KAUST Repository

Al-Awami, Ali K.

2014-12-31

We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.

Science.gov (United States)

Huang, Liang-Chin; Wu, Xiaogang; Chen, Jake Y

2013-01-01

The prediction of adverse drug reactions (ADRs) has become increasingly important, due to the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the market. We proposed a framework for predicting ADR profiles by integrating protein-protein interaction (PPI) networks with drug structures. We compared ADR prediction performances over 18 ADR categories through four feature groups-only drug targets, drug targets with PPI networks, drug structures, and drug targets with PPI networks plus drug structures. The results showed that the integration of PPI networks and drug structures can significantly improve the ADR prediction performance. The median AUC values for the four groups were 0.59, 0.61, 0.65, and 0.70. We used the protein features in the best two models, "Cardiac disorders" (median-AUC: 0.82) and "Psychiatric disorders" (median-AUC: 0.76), to build ADR-specific PPI networks with literature supports. For validation, we examined 30 drugs withdrawn from the U.S. market to see if our approach can predict their ADR profiles and explain why they were withdrawn. Except for three drugs having ADRs in the categories we did not predict, 25 out of 27 withdrawn drugs (92.6%) having severe ADRs were successfully predicted by our approach. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mapping monomeric threading to protein-protein structure prediction.

Science.gov (United States)

Guerler, Aysam; Govindarajoo, Brandon; Zhang, Yang

2013-03-25

The key step of template-based protein-protein structure prediction is the recognition of complexes from experimental structure libraries that have similar quaternary fold. Maintaining two monomer and dimer structure libraries is however laborious, and inappropriate library construction can degrade template recognition coverage. We propose a novel strategy SPRING to identify complexes by mapping monomeric threading alignments to protein-protein interactions based on the original oligomer entries in the PDB, which does not rely on library construction and increases the efficiency and quality of complex template recognitions. SPRING is tested on 1838 nonhomologous protein complexes which can recognize correct quaternary template structures with a TM score >0.5 in 1115 cases after excluding homologous proteins. The average TM score of the first model is 60% and 17% higher than that by HHsearch and COTH, respectively, while the number of targets with an interface RMSD benchmark proteins. Although the relative performance of SPRING and ZDOCK depends on the level of homology filters, a combination of the two methods can result in a significantly higher model quality than ZDOCK at all homology thresholds. These data demonstrate a new efficient approach to quaternary structure recognition that is ready to use for genome-scale modeling of protein-protein interactions due to the high speed and accuracy.

Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces.

Science.gov (United States)

Xia, Zheng; Wu, Ling-Yun; Zhou, Xiaobo; Wong, Stephen T C

2010-09-13

Predicting drug-protein interactions from heterogeneous biological data sources is a key step for in silico drug discovery. The difficulty of this prediction task lies in the rarity of known drug-protein interactions and myriad unknown interactions to be predicted. To meet this challenge, a manifold regularization semi-supervised learning method is presented to tackle this issue by using labeled and unlabeled information which often generates better results than using the labeled data alone. Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data. Using the proposed method, we predicted certain drug-protein interactions on the enzyme, ion channel, GPCRs, and nuclear receptor data sets. Some of them are confirmed by the latest publicly available drug targets databases such as KEGG. We report encouraging results of using our method for drug-protein interaction network reconstruction which may shed light on the molecular interaction inference and new uses of marketed drugs.

Molecular imaging of drug-modulated protein-protein interactions in living subjects.

Science.gov (United States)

Paulmurugan, Ramasamy; Massoud, Tarik F; Huang, Jing; Gambhir, Sanjiv S

2004-03-15

Networks of protein interactions mediate cellular responses to environmental stimuli and direct the execution of many different cellular functional pathways. Small molecules synthesized within cells or recruited from the external environment mediate many protein interactions. The study of small molecule-mediated interactions of proteins is important to understand abnormal signal transduction pathways in cancer and in drug development and validation. In this study, we used split synthetic renilla luciferase (hRLUC) protein fragment-assisted complementation to evaluate heterodimerization of the human proteins FRB and FKBP12 mediated by the small molecule rapamycin. The concentration of rapamycin required for efficient dimerization and that of its competitive binder ascomycin required for dimerization inhibition were studied in cell lines. The system was dually modulated in cell culture at the transcription level, by controlling nuclear factor kappaB promoter/enhancer elements using tumor necrosis factor alpha, and at the interaction level, by controlling the concentration of the dimerizer rapamycin. The rapamycin-mediated dimerization of FRB and FKBP12 also was studied in living mice by locating, quantifying, and timing the hRLUC complementation-based bioluminescence imaging signal using a cooled charged coupled device camera. This split reporter system can be used to efficiently screen small molecule drugs that modulate protein-protein interactions and also to assess drugs in living animals. Both are essential steps in the preclinical evaluation of candidate pharmaceutical agents targeting protein-protein interactions, including signaling pathways in cancer cells.

[Protein-energy malnutrition in patients with connective tissue dysplasia].

Science.gov (United States)

Lialiukova, E A

2013-01-01

In the conditions of the specialized Center of a dysplasia of a connecting tissue the assessment of an protein--energy malnutrition at 121 patients with signs of a dysplasia of a connecting tissue is carried out. High frequency of an oligotrophy at patients with a dysplasia of a connecting tissue is registered. The I degree of a gipotorofiya is taped at 26.21% of the patients, II degree--at 18.44%, the III degree--at 3.88% of patients.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

Directory of Open Access Journals (Sweden)

Ma'ayan Avi

2007-10-01

Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

S-Glutathionylation and Redox Protein Signaling in Drug Addiction.

Science.gov (United States)

Womersley, Jacqueline S; Uys, Joachim D

2016-01-01

Drug addiction is a chronic relapsing disorder that comes at a high cost to individuals and society. Therefore understanding the mechanisms by which drugs exert their effects is of prime importance. Drugs of abuse increase the production of reactive oxygen and nitrogen species resulting in oxidative stress. This change in redox homeostasis increases the conjugation of glutathione to protein cysteine residues; a process called S-glutathionylation. Although traditionally regarded as a protective mechanism against irreversible protein oxidation, accumulated evidence suggests a more nuanced role for S-glutathionylation, namely as a mediator in redox-sensitive protein signaling. The reversible modification of protein thiols leading to alteration in function under different physiologic/pathologic conditions provides a mechanism whereby change in redox status can be translated into a functional response. As such, S-glutathionylation represents an understudied means of post-translational protein modification that may be important in the mechanisms underlying drug addiction. This review will discuss the evidence for S-glutathionylation as a redox-sensing mechanism and how this may be involved in the response to drug-induced oxidative stress. The function of S-glutathionylated proteins involved in neurotransmission, dendritic spine structure, and drug-induced behavioral outputs will be reviewed with specific reference to alcohol, cocaine, and heroin. Copyright © 2016. Published by Elsevier Inc.

Characterization of particulate drug delivery systems for oral delivery of Peptide and protein drugs

DEFF Research Database (Denmark)

Christophersen, Philip Carsten; Fano, Mathias; Saaby, Lasse

2015-01-01

Oral drug delivery is a preferred route because of good patient compliance. However, most peptide/ protein drugs are delivered via parenteral routes because of the absorption barriers in the gastrointestinal (GI) tract such as enzymatic degradation by proteases and low permeability acrossthe...... delivery of peptide/protein drugs and to provide an overview of formulationand characterization strategies. For a better understanding of the challenges in oral delivery of peptide/protein drugs, the composition of GI fluids and the digestion processes of different kinds of excipients in the GI tract...... biological membranes. To overcome these barriers, different formulation strategies for oral delivery of biomacromolecules have been proposed, including lipid based formulations and polymer-based particulate drug delivery systems (DDS). The aim of this review is to summarize the existing knowledge about oral...

FeatureMap3D - a tool to map protein features and sequence conservation onto homologous structures in the PDB

DEFF Research Database (Denmark)

Wernersson, Rasmus; Rapacki, Krzysztof; Stærfeldt, Hans Henrik

2006-01-01

FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB) f...

Potential use and challenges of functional connectivity mapping in intractable epilepsy

Directory of Open Access Journals (Sweden)

Robert Todd Constable

2013-05-01

Full Text Available This review focuses on the use of resting-state functional magnetic resonance imaging data to assess functional connectivity in the human brain for surgical planning in intractable epilepsy. This approach has the potential to predict outcomes for a given surgical procedure based on the pre-surgical functional organization of the brain. Functional connectivity can also identify cortical regions that are organized differently in epilepsy patients either as a direct function of the disease or through indirect compensatory responses. Functional connectivity mapping can also potentially help identify epileptogenic tissue, whether this is a single focal location or a network of seizure-generating tissues and this information can assist in guiding the implantation of electrodes for invasive monitoring. This review covers the basics of connectivity analysis and discusses particular issues associated with analyzing such data. These issues include how to define nodes, as well as differences between connectivity analyses of individual nodes, groups of nodes, and whole-brain assessment at the voxel level. The need for arbitrary thresholds in some connectivity analyses is discussed and a solution to this problem is reviewed. Overall, functional connectivity analysis is becoming an important tool for assessing functional brain organization in surgical planning in epilepsy.

Making connections for life: an in vivo map of the yeast interactome.

Science.gov (United States)

Kast, Juergen

2008-10-01

Proteins are the true workhorses of any cell. To carry out specific tasks, they frequently bind other molecules in their surroundings. Due to their structural complexity and flexibility, the most diverse array of interactions is seen with other proteins. The different geometries and affinities available for such interactions typically bestow specific functions on proteins. Having available a map of protein-protein interactions is therefore of enormous importance for any researcher interested in gaining insight into biological systems at the level of cells and organisms. In a recent report, a novel approach has been employed that relies on the spontaneous folding of complementary enzyme fragments fused to two different proteins to test whether these interact in their actual cellular context [Tarassov et al., Science 320, 1465-1470 (2008)]. Genome-wide application of this protein-fragment complementation assay has resulted in the first map of the in vivo interactome of Saccharomyces cerevisiae. The current data show striking similarities but also significant differences to those obtained using other large-scale approaches for the same task. This warrants a general discussion of the current state of affairs of protein-protein interaction studies and foreseeable future trends, highlighting their significance for a variety of applications and their potential to revolutionize our understanding of the architecture and dynamics of biological systems.

Mapping small molecule binding data to structural domains.

Science.gov (United States)

Kruger, Felix A; Rostom, Raghd; Overington, John P

2012-01-01

Large-scale bioactivity/SAR Open Data has recently become available, and this has allowed new analyses and approaches to be developed to help address the productivity and translational gaps of current drug discovery. One of the current limitations of these data is the relative sparsity of reported interactions per protein target, and complexities in establishing clear relationships between bioactivity and targets using bioinformatics tools. We detail in this paper the indexing of targets by the structural domains that bind (or are likely to bind) the ligand within a full-length protein. Specifically, we present a simple heuristic to map small molecule binding to Pfam domains. This profiling can be applied to all proteins within a genome to give some indications of the potential pharmacological modulation and regulation of all proteins. In this implementation of our heuristic, ligand binding to protein targets from the ChEMBL database was mapped to structural domains as defined by profiles contained within the Pfam-A database. Our mapping suggests that the majority of assay targets within the current version of the ChEMBL database bind ligands through a small number of highly prevalent domains, and conversely the majority of Pfam domains sampled by our data play no currently established role in ligand binding. Validation studies, carried out firstly against Uniprot entries with expert binding-site annotation and secondly against entries in the wwPDB repository of crystallographic protein structures, demonstrate that our simple heuristic maps ligand binding to the correct domain in about 90 percent of all assessed cases. Using the mappings obtained with our heuristic, we have assembled ligand sets associated with each Pfam domain. Small molecule binding has been mapped to Pfam-A domains of protein targets in the ChEMBL bioactivity database. The result of this mapping is an enriched annotation of small molecule bioactivity data and a grouping of activity classes

Drug disposition in obesity and protein-energy malnutrition.

Science.gov (United States)

Boullata, Joseph I

2010-11-01

Clinical response to medication can differ between patients. Among the known sources of variability is an individual's nutrition status. This review defines some pharmacokinetic terms, provides relevant body size metrics and describes the physiologic influences of protein-energy malnutrition and obesity on drug disposition. Weight-based drug dosing, which presumes a healthy BMI, can be problematic in the protein-energy malnourished or obese patient. The use of total body weight, lean body weight, or an adjusted body weight depends on the drug and how it is differently handled in malnutrition or obesity. Most of the recognized influences are seen in drug distribution and drug elimination as a result of altered body composition and function. Distribution characteristics of each drug are determined by several drug-related factors (e.g. tissue affinity) in combination with body-related factors (e.g. composition). Drug elimination occurs through metabolic and excretory pathways that can also vary with body composition. The current data are limited to select drugs that have been reported in small studies or case reports. In the meantime, a rational approach to evaluate the potential influences of malnutrition and obesity can be used clinically based on available information. Antimicrobials are discussed as a useful example of this approach. Further advancement in this field would require collaboration between experts in body composition and those in drug disposition. Until more data are available, routine monitoring by the clinician of the protein-energy malnourished or obese patient receiving weight-based drug regimens is necessary.

Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map.

Science.gov (United States)

Klambauer, Günter; Wischenbart, Martin; Mahr, Michael; Unterthiner, Thomas; Mayr, Andreas; Hochreiter, Sepp

2015-10-15

We have developed Rchempp, a web service that identifies structurally similar compounds (structural analogs) in large-scale molecule databases. The service allows compounds to be queried in the widely used ChEMBL, DrugBank and the Connectivity Map databases. Rchemcpp utilizes the best performing similarity functions, i.e. molecule kernels, as measures for structural similarity. Molecule kernels have proven superior performance over other similarity measures and are currently excelling at machine learning challenges. To considerably reduce computational time, and thereby make it feasible as a web service, a novel efficient prefiltering strategy has been developed, which maintains the sensitivity of the method. By exploiting information contained in public databases, the web service facilitates many applications crucial for the drug development process, such as prioritizing compounds after screening or reducing adverse side effects during late phases. Rchemcpp was used in the DeepTox pipeline that has won the Tox21 Data Challenge and is frequently used by researchers in pharmaceutical companies. The web service and the R package are freely available via http://shiny.bioinf.jku.at/Analoging/ and via Bioconductor. hochreit@bioinf.jku.at Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A strategy to load balancing for non-connectivity MapReduce job

Science.gov (United States)

Zhou, Huaping; Liu, Guangzong; Gui, Haixia

2017-09-01

MapReduce has been widely used in large scale and complex datasets as a kind of distributed programming model. Original Hash partitioning function in MapReduce often results the problem of data skew when data distribution is uneven. To solve the imbalance of data partitioning, we proposes a strategy to change the remaining partitioning index when data is skewed. In Map phase, we count the amount of data which will be distributed to each reducer, then Job Tracker monitor the global partitioning information and dynamically modify the original partitioning function according to the data skew model, so the Partitioner can change the index of these partitioning which will cause data skew to the other reducer that has less load in the next partitioning process, and can eventually balance the load of each node. Finally, we experimentally compare our method with existing methods on both synthetic and real datasets, the experimental results show our strategy can solve the problem of data skew with better stability and efficiency than Hash method and Sampling method for non-connectivity MapReduce task.

Mapping protein-RNA interactions by RCAP, RNA-cross-linking and peptide fingerprinting.

Science.gov (United States)

Vaughan, Robert C; Kao, C Cheng

2015-01-01

RNA nanotechnology often feature protein RNA complexes. The interaction between proteins and large RNAs are difficult to study using traditional structure-based methods like NMR or X-ray crystallography. RCAP, an approach that uses reversible-cross-linking affinity purification method coupled with mass spectrometry, has been developed to map regions within proteins that contact RNA. This chapter details how RCAP is applied to map protein-RNA contacts within virions.

The constellation of dietary factors in adolescent acne: a semantic connectivity map approach.

Science.gov (United States)

Grossi, E; Cazzaniga, S; Crotti, S; Naldi, L; Di Landro, A; Ingordo, V; Cusano, F; Atzori, L; Tripodi Cutrì, F; Musumeci, M L; Pezzarossa, E; Bettoli, V; Caproni, M; Bonci, A

2016-01-01

Different lifestyle and dietetic factors have been linked with the onset and severity of acne. To assess the complex interconnection between dietetic variables and acne. This was a reanalysis of data from a case-control study by using a semantic connectivity map approach. 563 subjects, aged 10-24 years, involved in a case-control study of acne between March 2009 and February 2010, were considered in this study. The analysis evaluated the link between a moderate to severe acne and anthropometric variables, family history and dietetic factors. Analyses were conducted by relying on an artificial adaptive system, the Auto Semantic Connectivity Map (AutoCM). The AutoCM map showed that moderate-severe acne was closely associated with family history of acne in first degree relatives, obesity (BMI ≥ 30), and high consumption of milk, in particular skim milk, cheese/yogurt, sweets/cakes, chocolate, and a low consumption of fish, and limited intake of fruits/vegetables. Our analyses confirm the link between several dietetic items and acne. When providing care, dermatologists should also be aware of the complex interconnection between dietetic factors and acne. © 2014 European Academy of Dermatology and Venereology.

Cell density signal protein suitable for treatment of connective tissue injuries and defects

Science.gov (United States)

Schwarz, Richard I.

2002-08-13

Identification, isolation and partial sequencing of a cell density protein produced by fibroblastic cells. The cell density signal protein comprising a 14 amino acid peptide or a fragment, variant, mutant or analog thereof, the deduced cDNA sequence from the 14 amino acid peptide, a recombinant protein, protein and peptide-specific antibodies, and the use of the peptide and peptide-specific antibodies as therapeutic agents for regulation of cell differentiation and proliferation. A method for treatment and repair of connective tissue and tendon injuries, collagen deficiency, and connective tissue defects.

Development of novel drug delivery systems using phage display technology for clinical application of protein drugs.

Science.gov (United States)

Nagano, Kazuya; Tsutsumi, Yasuo

2016-01-01

Attempts are being made to develop therapeutic proteins for cancer, hepatitis, and autoimmune conditions, but their clinical applications are limited, except in the cases of drugs based on erythropoietin, granulocyte colony-stimulating factor, interferon-alpha, and antibodies, owing to problems with fundamental technologies for protein drug discovery. It is difficult to identify proteins useful as therapeutic seeds or targets. Another problem in using bioactive proteins is pleiotropic actions through receptors, making it hard to elicit desired effects without side effects. Additionally, bioactive proteins have poor therapeutic effects owing to degradation by proteases and rapid excretion from the circulatory system. Therefore, it is essential to establish a series of novel drug delivery systems (DDS) to overcome these problems. Here, we review original technologies in DDS. First, we introduce antibody proteomics technology for effective selection of proteins useful as therapeutic seeds or targets and identification of various kinds of proteins, such as cancer-specific proteins, cancer metastasis-related proteins, and a cisplatin resistance-related protein. Especially Ephrin receptor A10 is expressed in breast tumor tissues but not in normal tissues and is a promising drug target potentially useful for breast cancer treatment. Moreover, we have developed a system for rapidly creating functional mutant proteins to optimize the seeds for therapeutic applications and used this system to generate various kinds of functional cytokine muteins. Among them, R1antTNF is a TNFR1-selective antagonistic mutant of TNF and is the first mutein converted from agonist to antagonist. We also review a novel polymer-conjugation system to improve the in vivo stability of bioactive proteins. Site-specific PEGylated R1antTNF is uniform at the molecular level, and its bioactivity is similar to that of unmodified R1antTNF. In the future, we hope that many innovative protein drugs will be

Protein and Peptide in Drug Targeting and its Therapeutic Approach

Directory of Open Access Journals (Sweden)

Raj K. Keservani

2015-09-01

Full Text Available Aim: The main aim of this review article is to provide information like advantages of protein and peptides via different routes of drug administration, targeted to a particular site and its implication in drug delivery system. Methods: To that aim, from the web sites of PubMed, HCAplus, Thomson, and Registry were used as the main sources to perform the search for the most significant research articles published on the subject. The information was then carefully analyzed, highlighting the most important results in the development of protein and peptide drug targeting as well as its therapeutic activity. Results: In recent years many researchers use protein and peptide as a target site of drug by a different delivery system. Proteins and peptides are used as specific and effective therapeutic agents, due to instability and side effects their use is complicated. Protein kinases are important regulators of most, if not all, biological processes. Abnormal activity of proteins and peptides has been implicated in many human diseases, such as diabetes, cancer and neurodegenerative disorders. Conclusions: It is concluded that the protein and peptide were used in drug targeting to specific site and also used in different diseased states like cancer, diabetes, immunomodulating, neurodegenerative effects and antimicrobial activity.

Hydroxyapatite nanorod-assembled porous hollow polyhedra as drug/protein carriers.

Science.gov (United States)

Yu, Ya-Dong; Zhu, Ying-Jie; Qi, Chao; Jiang, Ying-Ying; Li, Heng; Wu, Jin

2017-06-15

Hydroxyapatite (HAP) with a porous hollow structure is an ideal biomaterial owing to its excellent biocompatibility and unique architecture. In this study, HAP nanorod-assembled porous hollow polyhedra, consisting of nanorod building blocks, have been successfully prepared at room temperature or under hydrothermal circumstances using a self-sacrificing Ca(OH) 2 template strategy. The hydrothermal treatment (at 180°C for 1h) can promote the HAP nanorods to be arranged with their axial direction normal to the polyhedron surface. The HAP nanorod-assembled porous hollow polyhedra have been explored for the potential application in drug/protein delivery, using ibuprofen (IBU) as a model drug and hemoglobin (Hb) as a model protein. The experimental results indicate that the HAP nanorod-assembled porous hollow polyhedra have a relatively high drug loading capacity and protein adsorption ability, and sustained drug and protein release. The HAP nanorod-assembled porous hollow polyhedra have promising applications in various biomedical fields such as the drug and protein delivery. Copyright © 2017 Elsevier Inc. All rights reserved.

Photoactive assemblies of organic compounds and biomolecules: drug-protein supramolecular systems.

Science.gov (United States)

Vayá, Ignacio; Lhiaubet-Vallet, Virginie; Jiménez, M Consuelo; Miranda, Miguel A

2014-06-21

The properties of singlet and triplet excited states are strongly medium-dependent. Hence, these species constitute valuable tools as reporters to probe compartmentalised microenvironments, including drug@protein supramolecular systems. In the present review, the attention is focused on the photophysical properties of the probe drugs (rather than those of the protein chromophores) using transport proteins (serum albumins and α1-acid glycoproteins) as hosts. Specifically, fluorescence measurements allow investigation of the structural and dynamic properties of biomolecules or their complexes. Thus, the emission quantum yields and the decay kinetics of the drug singlet excited states provide key information to determine important parameters such as the stoichiometry of the complex, the binding constant, the relative degrees of occupancy of the different compartments, etc. Application of the FRET concept allows determination of donor-acceptor interchromophoric distances. In addition, anisotropy measurements can be related to the orientation of the drug within the binding sites, where the degrees of freedom for conformational relaxation are restricted. Transient absorption spectroscopy is also a potentially powerful tool to investigate the binding of drugs to proteins, where formation of encapsulated triplet excited states is favoured over other possible processes leading to ionic species (i.e. radical ions), and their photophysical properties are markedly sensitive to the microenvironment experienced within the protein binding sites. Even under aerobic conditions, the triplet lifetimes of protein-complexed drugs are remarkably long, which provides a broad dynamic range for identification of distinct triplet populations or for chiral discrimination. Specific applications of the laser flash photolysis technique include the determination of drug distribution among the bulk solution and the protein binding sites, competition of two types of proteins to bind a drug

Pig-MAP, porcine acute phase proteins and standardisation of assays in Europe

DEFF Research Database (Denmark)

Alava, M.A.; Gonzalez-Ramon, N.; Heegaard, Peter M. H.

1997-01-01

The pattern of plasma proteins changes greatly following infection, inflammation or tissue injury. The concentration of some proteins referred to as acute phase proteins (APPs) significantly increases within hours or days after the onset of these processes. In contrast, the concentration of other...... during the inflammation. In addition to CRP and Hp, a serum alpha(2)-globulin was observed to be the major acute phase (MAP) protein in pigs. Pig-MAP is a new mammalian plasma protein, which is the pig counterpart of a recently cloned human serum protein denominated PK-120 or MRP. Pig-MAP shows promise...... for the presence of infectious, inflammatory and pathological lesions in animals. The ability to monitor the APP concentration in serum of pigs will improve the quality and safety of the meat produced as well as provide important diagnostic information for animal health and welfare. The serum concentration of APP...

Epitope mapping of the U1 small nuclear ribonucleoprotein particle in patients with systemic lupus erythematosus and mixed connective tissue disease.

Science.gov (United States)

Somarelli, J A; Mesa, A; Rodriguez, R; Avellan, R; Martinez, L; Zang, Y J; Greidinger, E L; Herrera, R J

2011-03-01

Systemic lupus erythematosus (SLE) and mixed connective tissue disease (MCTD) are autoimmune illnesses characterized by the presence of high titers of autoantibodies directed against a wide range of 'self ' antigens. Proteins of the U1 small nuclear ribonucleoprotein particle (U1 snRNP) are among the most immunogenic molecules in patients with SLE and MCTD. The recent release of a crystallized U1 snRNP provides a unique opportunity to evaluate the effects of tertiary and quaternary structures on autoantigenicity within the U1 snRNP. In the present study, an epitope map was created using the U1 snRNP crystal structure. A total of 15 peptides were tested in a cohort of 68 patients with SLE, 29 with MCTD and 26 healthy individuals and mapped onto the U1 snRNP structure. Antigenic sites were detected in a variety of structures and appear to include RNA binding domains, but mostly exclude regions necessary for protein-protein interactions. These data suggest that while some autoantibodies may target U1 snRNP proteins as monomers or apoptosis-induced, protease-digested fragments, others may recognize epitopes on assembled protein subcomplexes of the U1 snRNP. Although nearly all of the peptides are strong predictors of autoimmune illness, none were successful at distinguishing between SLE and MCTD. The antigenicity of some peptides significantly correlated with several clinical symptoms. This investigation implicitly highlights the complexities of autoimmune epitopes, and autoimmune illnesses in general, and demonstrates the variability of antigens in patient populations, all of which contribute to difficult clinical diagnoses.

May disordered protein cause serious drug side effect?

Science.gov (United States)

Tou, Weng Ieong; Chen, Calvin Yu-Chian

2014-04-01

Insomnia is a self-reported disease where patients lose their ability to initiate and maintain sleep, leading to daytime performance impairment. Several drug targets to ameliorate insomnia symptoms have been discovered; however, these drug targets lead to serious side effects. Thus, we characterize the structural properties of these sleep-related receptors and the clock complex and discuss a possible drug design that will reduce side effects. Computational prediction shows that disordered property is shared. Over 30% of the structure of CLOCK, PER1/2/3, BMAL-1, muscarinic acetylcholine receptor-M1, melatonin receptor and casein kinase I are structurally disordered (the remaining proteins represent insomnia drugs might be closely related to the protein architecture. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multidrug and toxin extrusion proteins as transporters of antimicrobial drugs.

Science.gov (United States)

Nies, Anne T; Damme, Katja; Schaeffeler, Elke; Schwab, Matthias

2012-12-01

Antimicrobial drugs are essential in the treatment of infectious diseases. A better understanding of transport processes involved in drug disposition will improve the predictability of drug-drug interactions with consequences for drug response. Multidrug And Toxin Extrusion (MATE; SLC47A) proteins are efflux transporters mediating the excretion of several antimicrobial drugs as well as other organic compounds into bile and urine, thereby contributing to drug disposition. This review summarizes current knowledge of the structural and molecular features of human MATE transporters including their functional role in drug transport with a specific focus on antimicrobial drugs. The PubMed database was searched using the terms "MATE1," "MATE-2K," "MATE2," "SLC47A1," "SLC47A2," and "toxin extrusion protein" (up to June 2012). MATE proteins have been recognized as important transporters mediating the final excretion step of cationic drugs into bile and urine. These include the antiviral drugs acyclovir, amprenavir, and ganciclovir, the antibiotics cephalexin, cephradine and levofloxacin, as well as the antimalarial agents chloroquine and quinine. It is therefore important to enhance our understanding of the role of MATEs in drug extrusion with particular emphasis on the functional consequences of genetic variants on disposition of these antimicrobial drugs.

Construction and characterization of a pure protein hydrogel for drug delivery application.

Science.gov (United States)

Xu, Xu; Xu, ZhaoKang; Yang, XiaoFeng; He, YanHao; Lin, Rong

2017-02-01

Injectable hydrogels have a variety of applications, including regenerative medicine, tissue engineering and controlled drug delivery. In this paper, we reported on a pure protein hydrogel based on tetrameric recombinant proteins for the potential drug delivery application. This protein hydrogel was formed instantly by simply mixing two recombinant proteins (ULD-TIP1 and ULD-GGGWRESAI) through the specific protein-peptide interaction. The protein hydrogel was characterized by rheology and scanning electron microscopy (SEM). In vitro cytotoxicity test indicated that the developed protein hydrogel had no apparent cytotoxicity against L-929 cells and HCEC cells after 48h incubation. The formed protein hydrogels was gradually degraded after incubation in phosphate buffered solution (PBS, pH=7.4) for a period of 144h study, as indicated by in vitro degradation test. Encapsulation of model drug (sodium diclofenac; DIC) were achieved by simple mixing of drugs with hydrogelator and the entrapped drugs was almost completely released from hydrogels within 24h via a diffusion manner. As a conclusion, the simple and mild preparation procedure and good biocompatibility of protein hydrogel would render its good promising candidate for drug delivery applications. Copyright © 2016 Elsevier B.V. All rights reserved.

Fitting multimeric protein complexes into electron microscopy maps using 3D Zernike descriptors.

Science.gov (United States)

Esquivel-Rodríguez, Juan; Kihara, Daisuke

2012-06-14

A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three-dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root-mean-square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases.

Recombinant Amphiphilic Protein Micelles for Drug Delivery

OpenAIRE

Kim, Wookhyun; Xiao, Jiantao; Chaikof, Elliot L.

2011-01-01

Amphiphilic block polypeptides can self-assemble into a range of nanostructures in solution, including micelles and vesicles. Our group has recently described the capacity of recombinant amphiphilic diblock copolypeptides to form highly stable micelles. In this report, we demonstrate the utility of protein nanoparticles to serve as a vehicle for controlled drug delivery. Drug-loaded micelles were produced by encapsulating dipyridamole as a model hydrophobic drug with anti-inflammatory activit...

Molecular mass spectrometry in metallodrug development: A case of mapping transferrin-mediated transformations for a ruthenium(III) anticancer drug

Energy Technology Data Exchange (ETDEWEB)

Jarosz, Maciej [Chair of Analytical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego St. 3, 00-664 Warsaw (Poland); Matczuk, Magdalena, E-mail: mmatczuk@ch.pw.edu.pl [Chair of Analytical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego St. 3, 00-664 Warsaw (Poland); Pawlak, Katarzyna [Chair of Analytical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego St. 3, 00-664 Warsaw (Poland); Timerbaev, Andrei R. [Vernadsky Institute of Geochemistry and Analytical Chemistry, Russian Academy of Sciences, Kosygin St. 19, 119991 Moscow (Russian Federation)

2014-12-03

Highlights: • Extra- and intra-cellular interactions of Ru(III) anticancer drug candidate. • ESI-TOF-MS mapping of the ruthenium species bound to transferring. • ESI-QqQ-MS identification of released Ru species under cytosol simulated conditions. - Abstract: Electrospray ionization mass spectrometry (ESI-MS) techniques have been used to characterize the speciation of a Ru(III) anticancer drug, indazolium trans-[tetrachloridobis(1H-indazole) ruthenate(III)], upon its binding to transferrin and the impact of cellular reducing components on drug–transferrin adducts. Using time-of-flight ESI-MS, the polymorphism of apo- (iron-free) and holo-form (iron-saturated) of the protein was confirmed. While the ruthenium moieties bound to each of five isoforms under simulated extracellular conditions are essentially identical in numbers for apo- and holo-transferrin, distinct differences were found in the composition of Ru(III) species attached to either of the protein forms, which are dominated by differently coordinated aquated complexes. On the other hand, at least one of the Ru-N bonds in metal-organic framework remains intact even after prolonged interaction with the protein. Triple quadrupole tandem ESI-MS measurements demonstrated that the ruthenium species released from drug adducts with holo-transferrin in simulated cancer cytosol are underwent strong ligand exchange (as compared to the protein-bound forms) but most strikingly, they contain the metal center in the reduced Ru(II) state. In vitro probing the extra- and intracellular interactions of promising Ru(III) drug candidate performed by ESI-MS is thought to shed light on the transportation to tumor cells by transferrin and on the activation to more reactive species by the reducing environment of solid tumors.

Numerical conformal mapping methods for exterior and doubly connected regions

Energy Technology Data Exchange (ETDEWEB)

DeLillo, T.K. [Wichita State Univ., KS (United States); Pfaltzgraff, J.A. [Univ. of North Carolina, Chapel Hill, NC (United States)

1996-12-31

Methods are presented and analyzed for approximating the conformal map from the exterior of the disk to the exterior a smooth, simple closed curve and from an annulus to a bounded, doubly connected region with smooth boundaries. The methods are Newton-like methods for computing the boundary correspondences and conformal moduli similar to Fornberg`s method for the interior of the disk. We show that the linear systems are discretizations of the identity plus a compact operator and, hence, that the conjugate gradient method converges superlinearly.

PDTD: a web-accessible protein database for drug target identification

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Gao Zhenting

2008-02-01

Full Text Available Abstract Background Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking http://www.dddc.ac.cn/tarfisdock, which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD, and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation. Description PDTD is a web-accessible protein database for in silico target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores. Conclusion PDTD serves as a comprehensive and

Computational methods for constructing protein structure models from 3D electron microscopy maps.

Science.gov (United States)

Esquivel-Rodríguez, Juan; Kihara, Daisuke

2013-10-01

Protein structure determination by cryo-electron microscopy (EM) has made significant progress in the past decades. Resolutions of EM maps have been improving as evidenced by recently reported structures that are solved at high resolutions close to 3Å. Computational methods play a key role in interpreting EM data. Among many computational procedures applied to an EM map to obtain protein structure information, in this article we focus on reviewing computational methods that model protein three-dimensional (3D) structures from a 3D EM density map that is constructed from two-dimensional (2D) maps. The computational methods we discuss range from de novo methods, which identify structural elements in an EM map, to structure fitting methods, where known high resolution structures are fit into a low-resolution EM map. A list of available computational tools is also provided. Copyright © 2013 Elsevier Inc. All rights reserved.

Mapping Partners Master Drug Dictionary to RxNorm using an NLP-based approach.

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Zhou, Li; Plasek, Joseph M; Mahoney, Lisa M; Chang, Frank Y; DiMaggio, Dana; Rocha, Roberto A

2012-08-01

To develop an automated method based on natural language processing (NLP) to facilitate the creation and maintenance of a mapping between RxNorm and a local medication terminology for interoperability and meaningful use purposes. We mapped 5961 terms from Partners Master Drug Dictionary (MDD) and 99 of the top prescribed medications to RxNorm. The mapping was conducted at both term and concept levels using an NLP tool, called MTERMS, followed by a manual review conducted by domain experts who created a gold standard mapping. The gold standard was used to assess the overall mapping between MDD and RxNorm and evaluate the performance of MTERMS. Overall, 74.7% of MDD terms and 82.8% of the top 99 terms had an exact semantic match to RxNorm. Compared to the gold standard, MTERMS achieved a precision of 99.8% and a recall of 73.9% when mapping all MDD terms, and a precision of 100% and a recall of 72.6% when mapping the top prescribed medications. The challenges and gaps in mapping MDD to RxNorm are mainly due to unique user or application requirements for representing drug concepts and the different modeling approaches inherent in the two terminologies. An automated approach based on NLP followed by human expert review is an efficient and feasible way for conducting dynamic mapping. Copyright © 2011 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.

The Geogenomic Mutational Atlas of Pathogens (GoMAP web system.

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David P Sargeant

Full Text Available We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web system called Geogenomic Mutational Atlas of Pathogens (GoMAP that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ∼ 502,000 sequences for many countries in the world. We also implemented a broadened classification scheme for HIV drug resistance mutations. Several patterns for geographic distributions of resistance mutations were identified by visual mining using this web tool. GoMAP-HIV is an open access web application available at http://www.bio-toolkit.com/GoMap/project/

Exploiting Large-Scale Drug-Protein Interaction Information for Computational Drug Repurposing

Science.gov (United States)

2014-06-20

studies that have reported antimalarial activities of azole compounds [39-43] lend support to our model predictions. The highest-scored non-malarial...Table 4, verapamil and cimetidine, do not have antimal- arial activities themselves but exhibit synergism when used in combination with antimalarial ... activators . Because of their high frequencies among the antimalarial drugs, according to Eq. 3, the drug-protein interactions contributing most to the

Combining ambiguous chemical shift mapping with structure-based backbone and NOE assignment from 15N-NOESY

KAUST Repository

Jang, Richard

2011-01-01

Chemical shift mapping is an important technique in NMRbased drug screening for identifying the atoms of a target protein that potentially bind to a drug molecule upon the molecule\\'s introduction in increasing concentrations. The goal is to obtain a mapping of peaks with known residue assignment from the reference spectrum of the unbound protein to peaks with unknown assignment in the target spectrum of the bound protein. Although a series of perturbed spectra help to trace a path from reference peaks to target peaks, a one-to-one mapping generally is not possible, especially for large proteins, due to errors, such as noise peaks, missing peaks, missing but then reappearing, overlapped, and new peaks not associated with any peaks in the reference. Due to these difficulties, the mapping is typically done manually or semi-automatically. However, automated methods are necessary for high-throughput drug screening. We present PeakWalker, a novel peak walking algorithm for fast-exchange systems that models the errors explicitly and performs many-to-one mapping. On the proteins: hBclXL, UbcH5B, and histone H1, it achieves an average accuracy of over 95% with less than 1.5 residues predicted per target peak. Given these mappings as input, we present PeakAssigner, a novel combined structure-based backbone resonance and NOE assignment algorithm that uses just 15N-NOESY, while avoiding TOCSY experiments and 13C- labeling, to resolve the ambiguities for a one-toone mapping. On the three proteins, it achieves an average accuracy of 94% or better. Copyright © 2011 ACM.

A Biologically-Based Computational Approach to Drug Repurposing for Anthrax Infection

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Jane P. F. Bai

2017-03-01

Full Text Available Developing drugs to treat the toxic effects of lethal toxin (LT and edema toxin (ET produced by B. anthracis is of global interest. We utilized a computational approach to score 474 drugs/compounds for their ability to reverse the toxic effects of anthrax toxins. For each toxin or drug/compound, we constructed an activity network by using its differentially expressed genes, molecular targets, and protein interactions. Gene expression profiles of drugs were obtained from the Connectivity Map and those of anthrax toxins in human alveolar macrophages were obtained from the Gene Expression Omnibus. Drug rankings were based on the ability of a drug/compound’s mode of action in the form of a signaling network to reverse the effects of anthrax toxins; literature reports were used to verify the top 10 and bottom 10 drugs/compounds identified. Simvastatin and bepridil with reported in vitro potency for protecting cells from LT and ET toxicities were computationally ranked fourth and eighth. The other top 10 drugs were fenofibrate, dihydroergotamine, cotinine, amantadine, mephenytoin, sotalol, ifosfamide, and mefloquine; literature mining revealed their potential protective effects from LT and ET toxicities. These drugs are worthy of investigation for their therapeutic benefits and might be used in combination with antibiotics for treating B. anthracis infection.

Seizure-Onset Mapping Based on Time-Variant Multivariate Functional Connectivity Analysis of High-Dimensional Intracranial EEG: A Kalman Filter Approach.

Science.gov (United States)

Lie, Octavian V; van Mierlo, Pieter

2017-01-01

The visual interpretation of intracranial EEG (iEEG) is the standard method used in complex epilepsy surgery cases to map the regions of seizure onset targeted for resection. Still, visual iEEG analysis is labor-intensive and biased due to interpreter dependency. Multivariate parametric functional connectivity measures using adaptive autoregressive (AR) modeling of the iEEG signals based on the Kalman filter algorithm have been used successfully to localize the electrographic seizure onsets. Due to their high computational cost, these methods have been applied to a limited number of iEEG time-series (Kalman filter implementations, a well-known multivariate adaptive AR model (Arnold et al. 1998) and a simplified, computationally efficient derivation of it, for their potential application to connectivity analysis of high-dimensional (up to 192 channels) iEEG data. When used on simulated seizures together with a multivariate connectivity estimator, the partial directed coherence, the two AR models were compared for their ability to reconstitute the designed seizure signal connections from noisy data. Next, focal seizures from iEEG recordings (73-113 channels) in three patients rendered seizure-free after surgery were mapped with the outdegree, a graph-theory index of outward directed connectivity. Simulation results indicated high levels of mapping accuracy for the two models in the presence of low-to-moderate noise cross-correlation. Accordingly, both AR models correctly mapped the real seizure onset to the resection volume. This study supports the possibility of conducting fully data-driven multivariate connectivity estimations on high-dimensional iEEG datasets using the Kalman filter approach.

Recent advances in (therapeutic protein drug development [version 1; referees: 2 approved

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H.A. Daniel Lagassé

2017-02-01

Full Text Available Therapeutic protein drugs are an important class of medicines serving patients most in need of novel therapies. Recently approved recombinant protein therapeutics have been developed to treat a wide variety of clinical indications, including cancers, autoimmunity/inflammation, exposure to infectious agents, and genetic disorders. The latest advances in protein-engineering technologies have allowed drug developers and manufacturers to fine-tune and exploit desirable functional characteristics of proteins of interest while maintaining (and in some cases enhancing product safety or efficacy or both. In this review, we highlight the emerging trends and approaches in protein drug development by using examples of therapeutic proteins approved by the U.S. Food and Drug Administration over the previous five years (2011–2016, namely January 1, 2011, through August 31, 2016.

Recent trends in drug delivery system using protein nanoparticles.

Science.gov (United States)

Sripriyalakshmi, S; Jose, Pinkybel; Ravindran, Aswathy; Anjali, C H

2014-09-01

Engineered nanoparticles that can facilitate drug formulation and passively target tumours have been under extensive research in recent years. These successes have driven a new wave of significant innovation in the generation of advanced particles. The fate and transport of diagnostic nanoparticles would significantly depend on nonselective drug delivery, and hence the use of high drug dosage is implemented. In this perspective, nanocarrier-based drug targeting strategies can be used which improve the selective delivery of drugs to the site of action, i.e. drug targeting. Pharmaceutical industries majorly focus on reducing the toxicity and side effects of drugs but only recently it has been realised that carrier systems themselves may pose risks to the patient. Proteins are compatible with biological systems and they are biodegradable. They offer a multitude of moieties for modifications to tailor drug binding, imaging or targeting entities. Thus, protein nanoparticles provide outstanding contributions as a carrier for drug delivery systems. This review summarises recent progress in particle-based therapeutic delivery and discusses important concepts in particle design and biological barriers for developing the next generation of particles drug delivery systems.

The semantic connectivity map: an adapting self-organising knowledge discovery method in data bases. Experience in gastro-oesophageal reflux disease.

Science.gov (United States)

Buscema, Massimo; Grossi, Enzo

2008-01-01

We describe here a new mapping method able to find out connectivity traces among variables thanks to an artificial adaptive system, the Auto Contractive Map (AutoCM), able to define the strength of the associations of each variable with all the others in a dataset. After the training phase, the weights matrix of the AutoCM represents the map of the main connections between the variables. The example of gastro-oesophageal reflux disease data base is extremely useful to figure out how this new approach can help to re-design the overall structure of factors related to complex and specific diseases description.

MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

Science.gov (United States)

Zhang, Chengxin; Zheng, Wei; Freddolino, Peter L; Zhang, Yang

2018-03-10

Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's homology-based protein-protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with >30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's homology-based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence homology-based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/. Copyright © 2018. Published by Elsevier Ltd.

Striatal activation and frontostriatal connectivity during non-drug reward anticipation in alcohol dependence.

Science.gov (United States)

Becker, Alena; Kirsch, Martina; Gerchen, Martin Fungisai; Kiefer, Falk; Kirsch, Peter

2017-05-01

According to prevailing neurobiological theories of addiction, altered function in neural reward circuitry is a central mechanism of alcohol dependence. Growing evidence postulates that the ventral striatum (VS), as well as areas of the prefrontal cortex, contribute to the increased incentive salience of alcohol-associated cues, diminished motivation to pursue non-drug rewards and weakened strength of inhibitory cognitive control, which are central to addiction. The present study aims to investigate the neural response and functional connectivity underlying monetary, non-drug reward processing in alcohol dependence. We utilized a reward paradigm to investigate the anticipation of monetary reward in 32 alcohol-dependent inpatients and 35 healthy controls. Functional magnetic resonance imaging was used to measure task-related brain activation and connectivity. Alcohol-dependent patients showed increased activation of the VS during anticipation of monetary gain compared with healthy controls. Generalized psychophysiological interaction analyses revealed decreased functional connectivity between the VS and the dorsolateral prefrontal cortex in alcohol dependent patients relative to controls. Increased activation of the VS and reduced frontostriatal connectivity were associated with increased craving. These findings provide evidence that alcohol dependence is rather associated with disrupted integration of striatal and prefrontal processes than with a global reward anticipation deficit. © 2016 Society for the Study of Addiction.

Functional mapping of protein-protein interactions in an enzyme complex by directed evolution.

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Kathrin Roderer

Full Text Available The shikimate pathway enzyme chorismate mutase converts chorismate into prephenate, a precursor of Tyr and Phe. The intracellular chorismate mutase (MtCM of Mycobacterium tuberculosis is poorly active on its own, but becomes >100-fold more efficient upon formation of a complex with the first enzyme of the shikimate pathway, 3-deoxy-d-arabino-heptulosonate-7-phosphate synthase (MtDS. The crystal structure of the enzyme complex revealed involvement of C-terminal MtCM residues with the MtDS interface. Here we employed evolutionary strategies to probe the tolerance to substitution of the C-terminal MtCM residues from positions 84-90. Variants with randomized positions were subjected to stringent selection in vivo requiring productive interactions with MtDS for survival. Sequence patterns identified in active library members coincide with residue conservation in natural chorismate mutases of the AroQδ subclass to which MtCM belongs. An Arg-Gly dyad at positions 85 and 86, invariant in AroQδ sequences, was intolerant to mutation, whereas Leu88 and Gly89 exhibited a preference for small and hydrophobic residues in functional MtCM-MtDS complexes. In the absence of MtDS, selection under relaxed conditions identifies positions 84-86 as MtCM integrity determinants, suggesting that the more C-terminal residues function in the activation by MtDS. Several MtCM variants, purified using a novel plasmid-based T7 RNA polymerase gene expression system, showed that a diminished ability to physically interact with MtDS correlates with reduced activatability and feedback regulatory control by Tyr and Phe. Mapping critical protein-protein interaction sites by evolutionary strategies may pinpoint promising targets for drugs that interfere with the activity of protein complexes.

Functional mapping of protein-protein interactions in an enzyme complex by directed evolution.

Science.gov (United States)

Roderer, Kathrin; Neuenschwander, Martin; Codoni, Giosiana; Sasso, Severin; Gamper, Marianne; Kast, Peter

2014-01-01

The shikimate pathway enzyme chorismate mutase converts chorismate into prephenate, a precursor of Tyr and Phe. The intracellular chorismate mutase (MtCM) of Mycobacterium tuberculosis is poorly active on its own, but becomes >100-fold more efficient upon formation of a complex with the first enzyme of the shikimate pathway, 3-deoxy-d-arabino-heptulosonate-7-phosphate synthase (MtDS). The crystal structure of the enzyme complex revealed involvement of C-terminal MtCM residues with the MtDS interface. Here we employed evolutionary strategies to probe the tolerance to substitution of the C-terminal MtCM residues from positions 84-90. Variants with randomized positions were subjected to stringent selection in vivo requiring productive interactions with MtDS for survival. Sequence patterns identified in active library members coincide with residue conservation in natural chorismate mutases of the AroQδ subclass to which MtCM belongs. An Arg-Gly dyad at positions 85 and 86, invariant in AroQδ sequences, was intolerant to mutation, whereas Leu88 and Gly89 exhibited a preference for small and hydrophobic residues in functional MtCM-MtDS complexes. In the absence of MtDS, selection under relaxed conditions identifies positions 84-86 as MtCM integrity determinants, suggesting that the more C-terminal residues function in the activation by MtDS. Several MtCM variants, purified using a novel plasmid-based T7 RNA polymerase gene expression system, showed that a diminished ability to physically interact with MtDS correlates with reduced activatability and feedback regulatory control by Tyr and Phe. Mapping critical protein-protein interaction sites by evolutionary strategies may pinpoint promising targets for drugs that interfere with the activity of protein complexes.

MapA, an iron-regulated, cytoplasmic membrane protein in the cyanobacterium Synechococcus sp. strain PCC7942.

Science.gov (United States)

Webb, R; Troyan, T; Sherman, D; Sherman, L A

1994-08-01

Growth of Synechococcus sp. strain PCC 7942 in iron-deficient media leads to the accumulation of an approximately 34-kDa protein. The gene encoding this protein, mapA (membrane-associated protein A), has been cloned and sequenced (GenBank accession number, L01621). The mapA transcript is not detectable in normally grown cultures but is stably accumulated by cells grown in iron-deficient media. However, the promoter sequence for this gene does not resemble other bacterial iron-regulated promoters described to date. The carboxyl-terminal region of the derived amino acid sequence of MapA resembles bacterial proteins involved in iron acquisition, whereas the amino-terminal end of MapA has a high degree of amino acid identity with the abundant, chloroplast envelope protein E37. An approach employing improved cellular fractionation techniques as well as electron microscopy and immunocytochemistry was essential in localizing MapA protein to the cytoplasmic membrane of Synechococcus sp. strain PCC 7942. When these cells were grown under iron-deficient conditions, a significant fraction of MapA could also be localized to the thylakoid membranes.

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

Science.gov (United States)

LaBute, Montiago X; Zhang, Xiaohua; Lenderman, Jason; Bennion, Brian J; Wong, Sergio E; Lightstone, Felice C

2014-01-01

Late-stage or post-market identification of adverse drug reactions (ADRs) is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER. We employed a recently parallelized version of AutoDock Vina (VinaLC) to dock 906 small molecule drugs to a virtual panel of 409 DrugBank protein targets. L1-regularized logistic regression models were trained on the resulting docking scores of a 560 compound subset from the initial 906 compounds to predict 85 side effects, grouped into 10 ADR phenotype groups. Only 21% (87 out of 409) of the drug-protein binding features involve known targets of the drug subset, providing a significant probe of off-target effects. As a control, associations of this drug subset with the 555 annotated targets of these compounds, as reported in DrugBank, were used as features to train a separate group of models. The Vina off-target models and the DrugBank on-target models yielded comparable median area-under-the-receiver-operating-characteristic-curves (AUCs) during 10-fold cross-validation (0.60-0.69 and 0.61-0.74, respectively). Evidence was found in the PubMed literature to support several putative ADR-protein associations identified by our analysis. Among them, several associations between neoplasm-related ADRs and known tumor suppressor and tumor invasiveness marker proteins were found. A dual role for interstitial collagenase in both neoplasms and aneurysm formation was also identified. These associations all involve off-target proteins and could not have been found using available drug/on-target interaction data. This study illustrates a path forward to comprehensive ADR virtual screening that can potentially scale with increasing number

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

Directory of Open Access Journals (Sweden)

Montiago X LaBute

Full Text Available Late-stage or post-market identification of adverse drug reactions (ADRs is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER. We employed a recently parallelized version of AutoDock Vina (VinaLC to dock 906 small molecule drugs to a virtual panel of 409 DrugBank protein targets. L1-regularized logistic regression models were trained on the resulting docking scores of a 560 compound subset from the initial 906 compounds to predict 85 side effects, grouped into 10 ADR phenotype groups. Only 21% (87 out of 409 of the drug-protein binding features involve known targets of the drug subset, providing a significant probe of off-target effects. As a control, associations of this drug subset with the 555 annotated targets of these compounds, as reported in DrugBank, were used as features to train a separate group of models. The Vina off-target models and the DrugBank on-target models yielded comparable median area-under-the-receiver-operating-characteristic-curves (AUCs during 10-fold cross-validation (0.60-0.69 and 0.61-0.74, respectively. Evidence was found in the PubMed literature to support several putative ADR-protein associations identified by our analysis. Among them, several associations between neoplasm-related ADRs and known tumor suppressor and tumor invasiveness marker proteins were found. A dual role for interstitial collagenase in both neoplasms and aneurysm formation was also identified. These associations all involve off-target proteins and could not have been found using available drug/on-target interaction data. This study illustrates a path forward to comprehensive ADR virtual screening that can potentially scale with

Influence of multidrug resistance and drug transport proteins on chemotherapy drug metabolism.

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Joyce, Helena; McCann, Andrew; Clynes, Martin; Larkin, Annemarie

2015-05-01

Chemotherapy involving the use of anticancer drugs remains an important strategy in the overall management of patients with metastatic cancer. Acquisition of multidrug resistance remains a major impediment to successful chemotherapy. Drug transporters in cell membranes and intracellular drug metabolizing enzymes contribute to the resistance phenotype and determine the pharmacokinetics of anticancer drugs in the body. ATP-binding cassette (ABC) transporters mediate the transport of endogenous metabolites and xenobiotics including cytotoxic drugs out of cells. Solute carrier (SLC) transporters mediate the influx of cytotoxic drugs into cells. This review focuses on the substrate interaction of these transporters, on their biology and what role they play together with drug metabolizing enzymes in eliminating therapeutic drugs from cells. The majority of anticancer drugs are substrates for the ABC transporter and SLC transporter families. Together, these proteins have the ability to control the influx and the efflux of structurally unrelated chemotherapeutic drugs, thereby modulating the intracellular drug concentration. These interactions have important clinical implications for chemotherapy because ultimately they determine therapeutic efficacy, disease progression/relapse and the success or failure of patient treatment.

Structural Mass Spectrometry of Proteins Using Hydroxyl Radical Based Protein Footprinting

OpenAIRE

Wang, Liwen; Chance, Mark R.

2011-01-01

Structural MS is a rapidly growing field with many applications in basic research and pharmaceutical drug development. In this feature article the overall technology is described and several examples of how hydroxyl radical based footprinting MS can be used to map interfaces, evaluate protein structure, and identify ligand dependent conformational changes in proteins are described.

Connecting protein and mRNA burst distributions for stochastic models of gene expression

International Nuclear Information System (INIS)

Elgart, Vlad; Jia, Tao; Fenley, Andrew T; Kulkarni, Rahul

2011-01-01

The intrinsic stochasticity of gene expression can lead to large variability in protein levels for genetically identical cells. Such variability in protein levels can arise from infrequent synthesis of mRNAs which in turn give rise to bursts of protein expression. Protein expression occurring in bursts has indeed been observed experimentally and recent studies have also found evidence for transcriptional bursting, i.e. production of mRNAs in bursts. Given that there are distinct experimental techniques for quantifying the noise at different stages of gene expression, it is of interest to derive analytical results connecting experimental observations at different levels. In this work, we consider stochastic models of gene expression for which mRNA and protein production occurs in independent bursts. For such models, we derive analytical expressions connecting protein and mRNA burst distributions which show how the functional form of the mRNA burst distribution can be inferred from the protein burst distribution. Additionally, if gene expression is repressed such that observed protein bursts arise only from single mRNAs, we show how observations of protein burst distributions (repressed and unrepressed) can be used to completely determine the mRNA burst distribution. Assuming independent contributions from individual bursts, we derive analytical expressions connecting means and variances for burst and steady-state protein distributions. Finally, we validate our general analytical results by considering a specific reaction scheme involving regulation of protein bursts by small RNAs. For a range of parameters, we derive analytical expressions for regulated protein distributions that are validated using stochastic simulations. The analytical results obtained in this work can thus serve as useful inputs for a broad range of studies focusing on stochasticity in gene expression

Comprehensive Analysis of Homologous Proteins for Specific Drug ...

African Journals Online (AJOL)

... minimize drug failures by predicting drug efficacy and toxicity. One of the most important pathogenic bacterium is Aeromonas species which causes tissue damage, acute gastroenteritis and neonatal septicemia. Bacterial proteins are the ultimate target to inhibit their growth and these are the executors of cellular function.

Discovery and Characterization of Non-ATP Site Inhibitors of the Mitogen Activated Protein (MAP) Kinases

Energy Technology Data Exchange (ETDEWEB)

Comess, Kenneth M.; Sun, Chaohong; Abad-Zapatero, Cele; Goedken, Eric R.; Gum, Rebecca J.; Borhani, David W.; Argiriadi, Maria; Groebe, Duncan R.; Jia, Yong; Clampit, Jill E.; Haasch, Deanna L.; Smith, Harriet T.; Wang, Sanyi; Song, Danying; Coen, Michael L.; Cloutier, Timothy E.; Tang, Hua; Cheng, Xueheng; Quinn, Christopher; Liu, Bo; Xin, Zhili; Liu, Gang; Fry, Elizabeth H.; Stoll, Vincent; Ng, Teresa I.; Banach, David; Marcotte, Doug; Burns, David J.; Calderwood, David J.; Hajduk, Philip J. (Abbott)

2012-03-02

Inhibition of protein kinases has validated therapeutic utility for cancer, with at least seven kinase inhibitor drugs on the market. Protein kinase inhibition also has significant potential for a variety of other diseases, including diabetes, pain, cognition, and chronic inflammatory and immunologic diseases. However, as the vast majority of current approaches to kinase inhibition target the highly conserved ATP-binding site, the use of kinase inhibitors in treating nononcology diseases may require great selectivity for the target kinase. As protein kinases are signal transducers that are involved in binding to a variety of other proteins, targeting alternative, less conserved sites on the protein may provide an avenue for greater selectivity. Here we report an affinity-based, high-throughput screening technique that allows nonbiased interrogation of small molecule libraries for binding to all exposed sites on a protein surface. This approach was used to screen both the c-Jun N-terminal protein kinase Jnk-1 (involved in insulin signaling) and p38{alpha} (involved in the formation of TNF{alpha} and other cytokines). In addition to canonical ATP-site ligands, compounds were identified that bind to novel allosteric sites. The nature, biological relevance, and mode of binding of these ligands were extensively characterized using two-dimensional {sup 1}H/{sup 13}C NMR spectroscopy, protein X-ray crystallography, surface plasmon resonance, and direct enzymatic activity and activation cascade assays. Jnk-1 and p38{alpha} both belong to the MAP kinase family, and the allosteric ligands for both targets bind similarly on a ledge of the protein surface exposed by the MAP insertion present in the CMGC family of protein kinases and distant from the active site. Medicinal chemistry studies resulted in an improved Jnk-1 ligand able to increase adiponectin secretion in human adipocytes and increase insulin-induced protein kinase PKB phosphorylation in human hepatocytes, in

The heparin-binding domain of HB-EGF as an efficient cell-penetrating peptide for drug delivery.

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Luo, Zhao; Cao, Xue-Wei; Li, Chen; Wu, Miao-Dan; Yang, Xu-Zhong; Zhao, Jian; Wang, Fu-Jun

2016-11-01

Cell-penetrating peptides (CPPs) have been shown to be potential drug carriers for cancer therapy. The inherently low immunogenicity and cytotoxicity of human-derived CPPs make them more suitable for intracellular drug delivery compared to other delivery vehicles. In this work, the protein transduction ability of a novel CPP (termed HBP) derived from the heparin-binding domain of HB-EGF was evaluated. Our data shows, for the first time, that HBP possesses similar properties to typical CPPs and is a potent drug delivery vector for improving the antitumor activity of impermeable MAP30. The intrinsic bioactivities of recombinant MAP30-HBP were well preserved compared to those of free MAP30. Furthermore, HBP conjugated to the C-terminus of MAP30 promoted the cellular uptake of recombinant MAP30-HBP. Moreover, the fusion of HBP to MAP30 gave rise to significantly enhanced cytotoxic effects in all of the tumor cell lines tested. In HeLa cells, this cytotoxicity was mainly caused by the induction of cell apoptosis. Further investigation revealed that HBP enhanced MAP30-induced apoptosis through the activation of the mitochondrial- and death receptor-mediated signaling pathways. In addition, the MAP30-HBP fusion protein caused more HeLa cells to become arrested in S phase compared to MAP30 alone. These results highlight the MAP30-HBP fusion protein as a promising drug candidate for cancer therapy and demonstrate HBP, a novel CPP derived from human HB-EGF, as a new potential vector for antitumor drug delivery. Copyright © 2016 European Peptide Society and John Wiley & Sons, Ltd. Copyright © 2016 European Peptide Society and John Wiley & Sons, Ltd.

Photoactive assemblies of organic compounds and biomolecules: drug-protein supramolecular systems

OpenAIRE

Vayá Pérez, Ignacio; Lhiaubet-Vallet, Virginie Lyria; Jiménez Molero, María Consuelo; Miranda Alonso, Miguel Ángel

2014-01-01

[EN] The properties of singlet and triplet excited states are strongly medium-dependent. Hence, these species constitute valuable tools as reporters to probe compartmentalised microenvironments, including drug@protein supramolecular systems. In the present review, the attention is focused on the photophysical properties of the probe drugs (rather than those of the protein chromophores) using transport proteins (serum albumins and 1-acid glycoproteins) as hosts. Specifically, f...

In Silico Identification of Proteins Associated with Drug-induced Liver Injury Based on the Prediction of Drug-target Interactions.

Science.gov (United States)

Ivanov, Sergey; Semin, Maxim; Lagunin, Alexey; Filimonov, Dmitry; Poroikov, Vladimir

2017-07-01

Drug-induced liver injury (DILI) is the leading cause of acute liver failure as well as one of the major reasons for drug withdrawal from clinical trials and the market. Elucidation of molecular interactions associated with DILI may help to detect potentially hazardous pharmacological agents at the early stages of drug development. The purpose of our study is to investigate which interactions with specific human protein targets may cause DILI. Prediction of interactions with 1534 human proteins was performed for the dataset with information about 699 drugs, which were divided into three categories of DILI: severe (178 drugs), moderate (310 drugs) and without DILI (211 drugs). Based on the comparison of drug-target interactions predicted for different drugs' categories and interpretation of those results using clustering, Gene Ontology, pathway and gene expression analysis, we identified 61 protein targets associated with DILI. Most of the revealed proteins were linked with hepatocytes' death caused by disruption of vital cellular processes, as well as the emergence of inflammation in the liver. It was found that interaction of a drug with the identified targets is the essential molecular mechanism of the severe DILI for the most of the considered pharmaceuticals. Thus, pharmaceutical agents interacting with many of the identified targets may be considered as candidates for filtering out at the early stages of drug research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Updates on drug-target network; facilitating polypharmacology and data integration by growth of DrugBank database.

Science.gov (United States)

Barneh, Farnaz; Jafari, Mohieddin; Mirzaie, Mehdi

2016-11-01

Network pharmacology elucidates the relationship between drugs and targets. As the identified targets for each drug increases, the corresponding drug-target network (DTN) evolves from solely reflection of the pharmaceutical industry trend to a portrait of polypharmacology. The aim of this study was to evaluate the potentials of DrugBank database in advancing systems pharmacology. We constructed and analyzed DTN from drugs and targets associations in the DrugBank 4.0 database. Our results showed that in bipartite DTN, increased ratio of identified targets for drugs augmented density and connectivity of drugs and targets and decreased modular structure. To clear up the details in the network structure, the DTNs were projected into two networks namely, drug similarity network (DSN) and target similarity network (TSN). In DSN, various classes of Food and Drug Administration-approved drugs with distinct therapeutic categories were linked together based on shared targets. Projected TSN also showed complexity because of promiscuity of the drugs. By including investigational drugs that are currently being tested in clinical trials, the networks manifested more connectivity and pictured the upcoming pharmacological space in the future years. Diverse biological processes and protein-protein interactions were manipulated by new drugs, which can extend possible target combinations. We conclude that network-based organization of DrugBank 4.0 data not only reveals the potential for repurposing of existing drugs, also allows generating novel predictions about drugs off-targets, drug-drug interactions and their side effects. Our results also encourage further effort for high-throughput identification of targets to build networks that can be integrated into disease networks. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

On optical detection of densely labeled synapses in neuropil and mapping connectivity with combinatorially multiplexed fluorescent synaptic markers.

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Yuriy Mishchenko

Full Text Available We propose a new method for mapping neural connectivity optically, by utilizing Cre/Lox system Brainbow to tag synapses of different neurons with random mixtures of different fluorophores, such as GFP, YFP, etc., and then detecting patterns of fluorophores at different synapses using light microscopy (LM. Such patterns will immediately report the pre- and post-synaptic cells at each synaptic connection, without tracing neural projections from individual synapses to corresponding cell bodies. We simulate fluorescence from a population of densely labeled synapses in a block of hippocampal neuropil, completely reconstructed from electron microscopy data, and show that high-end LM is able to detect such patterns with over 95% accuracy. We conclude, therefore, that with the described approach neural connectivity in macroscopically large neural circuits can be mapped with great accuracy, in scalable manner, using fast optical tools, and straightforward image processing. Relying on an electron microscopy dataset, we also derive and explicitly enumerate the conditions that should be met to allow synaptic connectivity studies with high-resolution optical tools.

C-terminal region of MAP7 domain containing protein 3 (MAP7D3 promotes microtubule polymerization by binding at the C-terminal tail of tubulin.

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Saroj Yadav

Full Text Available MAP7 domain containing protein 3 (MAP7D3, a newly identified microtubule associated protein, has been shown to promote microtubule assembly and stability. Its microtubule binding region has been reported to consist of two coiled coil motifs located at the N-terminus. It possesses a MAP7 domain near the C-terminus and belongs to the microtubule associated protein 7 (MAP7 family. The MAP7 domain of MAP7 protein has been shown to bind to kinesin-1; however, the role of MAP7 domain in MAP7D3 remains unknown. Based on the bioinformatics analysis of MAP7D3, we hypothesized that the MAP7 domain of MAP7D3 may have microtubule binding activity. Indeed, we found that MAP7 domain of MAP7D3 bound to microtubules as well as enhanced the assembly of microtubules in vitro. Interestingly, a longer fragment MDCT that contained the MAP7 domain (MD with the C-terminal tail (CT of the protein promoted microtubule polymerization to a greater extent than MD and CT individually. MDCT stabilized microtubules against dilution induced disassembly. MDCT bound to reconstituted microtubules with an apparent dissociation constant of 3.0 ± 0.5 µM. An immunostaining experiment showed that MDCT localized along the length of the preassembled microtubules. Competition experiments with tau indicated that MDCT shares its binding site on microtubules with tau. Further, we present evidence indicating that MDCT binds to the C-terminal tail of tubulin. In addition, MDCT could bind to tubulin in HeLa cell extract. Here, we report a microtubule binding region in the C-terminal region of MAP7D3 that may have a role in regulating microtubule assembly dynamics.

Photo-synthesis of protein-based nanoparticles and the application in drug delivery

International Nuclear Information System (INIS)

Xie, Jinbing; Wang, Hongyang; Cao, Yi; Qin, Meng; Wang, Wei

2015-01-01

Recently, protein-based nanoparticles as drug delivery systems have attracted great interests due to the excellent behavior of high biocompatibility and biodegradability, and low toxicity. However, the synthesis techniques are generally costly, chemical reagents introduced, and especially present difficulties in producing homogeneous monodispersed nanoparticles. Here, we introduce a novel physical method to synthesize protein nanoparticles which can be accomplished under physiological condition only through ultraviolet (UV) illumination. By accurately adjusting the intensity and illumination time of UV light, disulfide bonds in proteins can be selectively reduced and the subsequent self-assembly process can be well controlled. Importantly, the co-assembly can also be dominated when the proteins mixed with either anti-cancer drugs, siRNA, or active targeting molecules. Both in vitro and in vivo experiments indicate that our synthesized protein–drug nanoparticles (drug-loading content and encapsulation efficiency being ca. 8.2% and 70%, respectively) not only possess the capability of traditional drug delivery systems (DDS), but also have a greater drug delivery efficiency to the tumor sites and a better inhibition of tumor growth (only 35% of volume comparing to the natural growing state), indicating it being a novel drug delivery system in tumor therapy

A New MAP Kinase Protein Involved in Estradiol-Stimulated Reproduction of the Helminth Parasite Taenia crassiceps

Science.gov (United States)

Escobedo, Galileo; Soldevila, Gloria; Ortega-Pierres, Guadalupe; Chávez-Ríos, Jesús Ramsés; Nava, Karen; Fonseca-Liñán, Rocío; López-Griego, Lorena; Hallal-Calleros, Claudia; Ostoa-Saloma, Pedro; Morales-Montor, Jorge

2010-01-01

MAP kinases (MAPK) are involved in the regulation of cellular processes such as reproduction and growth. In parasites, the role of MAPK has been scarcely studied. Here, we describe the participation of an ERK-like protein in estrogen-dependent reproduction of the helminth parasite Taenia crassiceps. Our results show that 17β-estradiol induces a concentration-dependent increase in the bud number of in vitro cultured cysticerci. If parasites are also incubated in presence of an ERK-inhibitor, the stimulatory effect of estrogen is blocked. The expression of ERK-like mRNA and its corresponding protein was detected in the parasite. The ERK-like protein was over-expressed by all treatments. Nevertheless, a strong induction of phosphorylation of this protein was observed only in response to 17β-estradiol. Cross-contamination by host cells was discarded by flow cytometry analysis. Parasite cells expressing the ERK-like protein were exclusively located at the subtegument tissue by confocal microscopy. Finally, the ERK-like protein was separated by bidimensional electrophoresis and then sequenced, showing the conserved TEY activation motif, typical of all known ERK 1/2 proteins. Our results show that an ERK-like protein is involved in the molecular signalling during the interaction between the host and T. crassiceps, and may be considered as target for anti-helminth drugs design. PMID:20145710

Protein Connectivity in Chemotaxis Receptor Complexes.

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Stephan Eismann

2015-12-01

Full Text Available The chemotaxis sensory system allows bacteria such as Escherichia coli to swim towards nutrients and away from repellents. The underlying pathway is remarkably sensitive in detecting chemical gradients over a wide range of ambient concentrations. Interactions among receptors, which are predominantly clustered at the cell poles, are crucial to this sensitivity. Although it has been suggested that the kinase CheA and the adapter protein CheW are integral for receptor connectivity, the exact coupling mechanism remains unclear. Here, we present a statistical-mechanics approach to model the receptor linkage mechanism itself, building on nanodisc and electron cryotomography experiments. Specifically, we investigate how the sensing behavior of mixed receptor clusters is affected by variations in the expression levels of CheA and CheW at a constant receptor density in the membrane. Our model compares favorably with dose-response curves from in vivo Förster resonance energy transfer (FRET measurements, demonstrating that the receptor-methylation level has only minor effects on receptor cooperativity. Importantly, our model provides an explanation for the non-intuitive conclusion that the receptor cooperativity decreases with increasing levels of CheA, a core signaling protein associated with the receptors, whereas the receptor cooperativity increases with increasing levels of CheW, a key adapter protein. Finally, we propose an evolutionary advantage as explanation for the recently suggested CheW-only linker structures.

Protein-Templated Fragment Ligations-From Molecular Recognition to Drug Discovery.

Science.gov (United States)

Jaegle, Mike; Wong, Ee Lin; Tauber, Carolin; Nawrotzky, Eric; Arkona, Christoph; Rademann, Jörg

2017-06-19

Protein-templated fragment ligation is a novel concept to support drug discovery and can help to improve the efficacy of protein ligands. Protein-templated fragment ligations are chemical reactions between small molecules ("fragments") utilizing a protein's surface as a reaction vessel to catalyze the formation of a protein ligand with increased binding affinity. The approach exploits the molecular recognition of reactive small-molecule fragments by proteins both for ligand assembly and for the identification of bioactive fragment combinations. In this way, chemical synthesis and bioassay are integrated in one single step. This Review discusses the biophysical basis of reversible and irreversible fragment ligations and gives an overview of the available methods to detect protein-templated ligation products. The chemical scope and recent applications as well as future potential of the concept in drug discovery are reviewed. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Orally active-targeted drug delivery systems for proteins and peptides.

Science.gov (United States)

Li, Xiuying; Yu, Miaorong; Fan, Weiwei; Gan, Yong; Hovgaard, Lars; Yang, Mingshi

2014-09-01

In the past decade, extensive efforts have been devoted to designing 'active targeted' drug delivery systems (ATDDS) to improve oral absorption of proteins and peptides. Such ATDDS enhance cellular internalization and permeability of proteins and peptides via molecular recognition processes such as ligand-receptor or antigen-antibody interaction, and thus enhance drug absorption. This review focuses on recent advances with orally ATDDS, including ligand-protein conjugates, recombinant ligand-protein fusion proteins and ligand-modified carriers. In addition to traditional intestinal active transport systems of substrates and their corresponding receptors, transporters and carriers, new targets such as intercellular adhesion molecule-1 and β-integrin are also discussed. ATDDS can improve oral absorption of proteins and peptides. However, currently, no clinical studies on ATDDS for proteins and peptides are underway, perhaps due to the complexity and limited knowledge of transport mechanisms. Therefore, more research is warranted to optimize ATDDS efficiency.

Mapping a Careflow Network to assess the connectedness of Connected Health.

Science.gov (United States)

Carroll, Noel; Richardson, Ita

2017-04-01

Connected Health is an emerging and rapidly developing field which has the potential to transform healthcare service systems by increasing its safety, quality and overall efficiency. From a healthcare perspective, process improvement models have mainly focused on the static workflow viewpoint. The objective of this article is to study and model the dynamic nature of healthcare delivery, allowing us to identify where potential issues exist within the service system and to examine how Connected Health technological solutions may support service efficiencies. We explore the application of social network analysis (SNA) as a modelling technique which captures the dynamic nature of a healthcare service. We demonstrate how it can be used to map the 'Careflow Network' and guide Connected Health innovators to examine specific opportunities within the healthcare service. Our results indicate that healthcare technology must be correctly identified and implemented within the Careflow Network to enjoy improvements in service delivery. Oftentimes, prior to making the transformation to Connected Health, researchers use various modelling techniques that fail to identify where Connected Health innovation is best placed in a healthcare service network. Using SNA allows us to develop an understanding of the current operation of healthcare system within which they can effect change. It is important to identify and model the resource exchanges to ensure that the quality and safety of care are enhanced, efficiencies are increased and the overall healthcare service system is improved. We have shown that dynamic models allow us to study the exchange of resources. These are often intertwined within a socio-technical context in an informal manner and not accounted for in static models, yet capture a truer insight on the operations of a Careflow Network.

Injectable nanocomposite cryogels for versatile protein drug delivery.

Science.gov (United States)

Koshy, Sandeep T; Zhang, David K Y; Grolman, Joshua M; Stafford, Alexander G; Mooney, David J

2018-01-01

Sustained, localized protein delivery can enhance the safety and activity of protein drugs in diverse disease settings. While hydrogel systems are widely studied as vehicles for protein delivery, they often suffer from rapid release of encapsulated cargo, leading to a narrow duration of therapy, and protein cargo can be denatured by incompatibility with the hydrogel crosslinking chemistry. In this work, we describe injectable nanocomposite hydrogels that are capable of sustained, bioactive, release of a variety of encapsulated proteins. Injectable and porous cryogels were formed by bio-orthogonal crosslinking of alginate using tetrazine-norbornene coupling. To provide sustained release from these hydrogels, protein cargo was pre-adsorbed to charged Laponite nanoparticles that were incorporated within the walls of the cryogels. The presence of Laponite particles substantially hindered the release of a number of proteins that otherwise showed burst release from these hydrogels. By modifying the Laponite content within the hydrogels, the kinetics of protein release could be precisely tuned. This versatile strategy to control protein release simplifies the design of hydrogel drug delivery systems. Here we present an injectable nanocomposite hydrogel for simple and versatile controlled release of therapeutic proteins. Protein release from hydrogels often requires first entrapping the protein in particles and embedding these particles within the hydrogel to allow controlled protein release. This pre-encapsulation process can be cumbersome, can damage the protein's activity, and must be optimized for each protein of interest. The strategy presented in this work simply premixes the protein with charged nanoparticles that bind strongly with the protein. These protein-laden particles are then placed within a hydrogel and slowly release the protein into the surrounding environment. Using this method, tunable release from an injectable hydrogel can be achieved for a variety of

Targeted proteins for diabetes drug design

Science.gov (United States)

Doan Trang Nguyen, Ngoc; Thi Le, Ly

2012-03-01

Type 2 diabetes mellitus is a common metabolism disorder characterized by high glucose in the bloodstream, especially in the case of insulin resistance and relative insulin deficiency. Nowadays, it is very common in middle-aged people and involves such dangerous symptoms as increasing risk of stroke, obesity and heart failure. In Vietnam, besides the common treatment of insulin injection, some herbal medication is used but no unified optimum remedy for the disease yet exists and there is no production of antidiabetic drugs in the domestic market yet. In the development of nanomedicine at the present time, drug design is considered as an innovative tool for researchers to study the mechanisms of diseases at the molecular level. The aim of this article is to review some common protein targets involved in type 2 diabetes, offering a new idea for designing new drug candidates to produce antidiabetic drugs against type 2 diabetes for Vietnamese people.

Targeted proteins for diabetes drug design

International Nuclear Information System (INIS)

Trang Nguyen, Ngoc Doan; Le, Ly Thi

2012-01-01

Type 2 diabetes mellitus is a common metabolism disorder characterized by high glucose in the bloodstream, especially in the case of insulin resistance and relative insulin deficiency. Nowadays, it is very common in middle-aged people and involves such dangerous symptoms as increasing risk of stroke, obesity and heart failure. In Vietnam, besides the common treatment of insulin injection, some herbal medication is used but no unified optimum remedy for the disease yet exists and there is no production of antidiabetic drugs in the domestic market yet. In the development of nanomedicine at the present time, drug design is considered as an innovative tool for researchers to study the mechanisms of diseases at the molecular level. The aim of this article is to review some common protein targets involved in type 2 diabetes, offering a new idea for designing new drug candidates to produce antidiabetic drugs against type 2 diabetes for Vietnamese people. (review)

Hybrid protein-inorganic nanoparticles: From tumor-targeted drug delivery to cancer imaging.

Science.gov (United States)

Elzoghby, Ahmed O; Hemasa, Ayman L; Freag, May S

2016-12-10

Recently, a great interest has been paid to the development of hybrid protein-inorganic nanoparticles (NPs) for drug delivery and cancer diagnostics in order to combine the merits of both inorganic and protein nanocarriers. This review primarily discusses the most outstanding advances in the applications of the hybrids of naturally-occurring proteins with iron oxide, gadolinium, gold, silica, calcium phosphate NPs, carbon nanotubes, and quantum dots in drug delivery and cancer imaging. Various strategies that have been utilized for the preparation of protein-functionalized inorganic NPs and the mechanisms involved in the drug loading process are discussed. How can the protein functionalization overcome the limitations of colloidal stability, poor dispersibility and toxicity associated with inorganic NPs is also investigated. Moreover, issues relating to the influence of protein hybridization on the cellular uptake, tumor targeting efficiency, systemic circulation, mucosal penetration and skin permeation of inorganic NPs are highlighted. A special emphasis is devoted to the novel approaches utilizing the protein-inorganic nanohybrids in combined cancer therapy, tumor imaging, and theranostic applications as well as stimuli-responsive drug release from the nanohybrids. Copyright © 2016 Elsevier B.V. All rights reserved.

Programmable release of multiple protein drugs from aptamer-functionalized hydrogels via nucleic acid hybridization.

Science.gov (United States)

Battig, Mark R; Soontornworajit, Boonchoy; Wang, Yong

2012-08-01

Polymeric delivery systems have been extensively studied to achieve localized and controlled release of protein drugs. However, it is still challenging to control the release of multiple protein drugs in distinct stages according to the progress of disease or treatment. This study successfully demonstrates that multiple protein drugs can be released from aptamer-functionalized hydrogels with adjustable release rates at predetermined time points using complementary sequences (CSs) as biomolecular triggers. Because both aptamer-protein interactions and aptamer-CS hybridization are sequence-specific, aptamer-functionalized hydrogels constitute a promising polymeric delivery system for the programmable release of multiple protein drugs to treat complex human diseases.

Expression of a Recombinant Anti-HIV and Anti-Tumor Protein, MAP30, in Nicotiana tobacum Hairy Roots: A pH-Stable and Thermophilic Antimicrobial Protein.

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Ali Moghadam

Full Text Available In contrast to conventional antibiotics, which microorganisms can readily evade, it is nearly impossible for a microbial strain that is sensitive to antimicrobial proteins to convert to a resistant strain. Therefore, antimicrobial proteins and peptides that are promising alternative candidates for the control of bacterial infections are under investigation. The MAP30 protein of Momordica charantia is a valuable type I ribosome-inactivating protein (RIP with anti-HIV and anti-tumor activities. Whereas the antimicrobial activity of some type I RIPs has been confirmed, less attention has been paid to the antimicrobial activity of MAP30 produced in a stable, easily handled, and extremely cost-effective protein-expression system. rMAP30-KDEL was expressed in Nicotiana tobacum hairy roots, and its effect on different microorganisms was investigated. Analysis of the extracted total proteins of transgenic hairy roots showed that rMAP30-KDEL was expressed effectively and that this protein exhibited significant antibacterial activity in a dose-dependent manner. rMAP30-KDEL also possessed thermal and pH stability. Bioinformatic analysis of MAP30 and other RIPs regarding their conserved motifs, amino-acid contents, charge, aliphatic index, GRAVY value, and secondary structures demonstrated that these factors accounted for their thermophilicity. Therefore, RIPs such as MAP30 and its derived peptides might have promising applications as food preservatives, and their analysis might provide useful insights into designing clinically applicable antibiotic agents.

A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes.

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Cheng, Feixiong; Zhao, Junfei; Fooksa, Michaela; Zhao, Zhongming

2016-07-01

Development of computational approaches and tools to effectively integrate multidomain data is urgently needed for the development of newly targeted cancer therapeutics. We proposed an integrative network-based infrastructure to identify new druggable targets and anticancer indications for existing drugs through targeting significantly mutated genes (SMGs) discovered in the human cancer genomes. The underlying assumption is that a drug would have a high potential for anticancer indication if its up-/down-regulated genes from the Connectivity Map tended to be SMGs or their neighbors in the human protein interaction network. We assembled and curated 693 SMGs in 29 cancer types and found 121 proteins currently targeted by known anticancer or noncancer (repurposed) drugs. We found that the approved or experimental cancer drugs could potentially target these SMGs in 33.3% of the mutated cancer samples, and this number increased to 68.0% by drug repositioning through surveying exome-sequencing data in approximately 5000 normal-tumor pairs from The Cancer Genome Atlas. Furthermore, we identified 284 potential new indications connecting 28 cancer types and 48 existing drugs (adjusted P < .05), with a 66.7% success rate validated by literature data. Several existing drugs (e.g., niclosamide, valproic acid, captopril, and resveratrol) were predicted to have potential indications for multiple cancer types. Finally, we used integrative analysis to showcase a potential mechanism-of-action for resveratrol in breast and lung cancer treatment whereby it targets several SMGs (ARNTL, ASPM, CTTN, EIF4G1, FOXP1, and STIP1). In summary, we demonstrated that our integrative network-based infrastructure is a promising strategy to identify potential druggable targets and uncover new indications for existing drugs to speed up molecularly targeted cancer therapeutics. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All

RESEARCH PROBLEM DESCRIPTION AND DEFINITION: FROM MENTAL MAP TO CONNECTION CIRCLE

Directory of Open Access Journals (Sweden)

Mildeová, Stanislava

2013-12-01

Full Text Available The paper examines the research problem (question as one of the first methodological steps that has to be accurately and clearly defined. The necessity of modern scientific work is to understand and analyse problems holistically, to see it as a network of interconnected parts. In this sense we show that combination of mental mapping and connection circle may be a way that will be beneficial defining the research problem. There is some evidence from interviews held with PhD students, who were participated in the course Research Methods for Managers at the University of Economics in Prague from 2012-2013.

Determination of contact maps in proteins: A combination of structural and chemical approaches

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Wołek, Karol; Cieplak, Marek, E-mail: mc@ifpan.edu.pl [Institute of Physics, Polish Academy of Science, Al. Lotników 32/46, 02-668 Warsaw (Poland); Gómez-Sicilia, Àngel [Instituto Cajal, Consejo Superior de Investigaciones Cientificas (CSIC), Av. Doctor Arce, 37, 28002 Madrid (Spain); Instituto Madrileño de Estudios Avanzados en Nanociencia (IMDEA-Nanociencia), C/Faraday 9, 28049 Cantoblanco (Madrid) (Spain)

2015-12-28

Contact map selection is a crucial step in structure-based molecular dynamics modelling of proteins. The map can be determined in many different ways. We focus on the methods in which residues are represented as clusters of effective spheres. One contact map, denoted as overlap (OV), is based on the overlap of such spheres. Another contact map, named Contacts of Structural Units (CSU), involves the geometry in a different way and, in addition, brings chemical considerations into account. We develop a variant of the CSU approach in which we also incorporate Coulombic effects such as formation of the ionic bridges and destabilization of possible links through repulsion. In this way, the most essential and well defined contacts are identified. The resulting residue-residue contact map, dubbed repulsive CSU (rCSU), is more sound in its physico-chemical justification than CSU. It also provides a clear prescription for validity of an inter-residual contact: the number of attractive atomic contacts should be larger than the number of repulsive ones — a feature that is not present in CSU. However, both of these maps do not correlate well with the experimental data on protein stretching. Thus, we propose to use rCSU together with the OV map. We find that the combined map, denoted as OV+rCSU, performs better than OV. In most situations, OV and OV+rCSU yield comparable folding properties but for some proteins rCSU provides contacts which improve folding in a substantial way. We discuss the likely residue-specificity of the rCSU contacts. Finally, we make comparisons to the recently proposed shadow contact map, which is derived from different principles.

Towards mapping the brain connectome in depression: functional connectivity by perfusion SPECT.

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Gardner, Ann; Åstrand, Disa; Öberg, Johanna; Jacobsson, Hans; Jonsson, Cathrine; Larsson, Stig; Pagani, Marco

2014-08-30

Several studies have demonstrated altered brain functional connectivity in the resting state in depression. However, no study has investigated interregional networking in patients with persistent depressive disorder (PDD). The aim of this study was to assess differences in brain perfusion distribution and connectivity between large groups of patients and healthy controls. Participants comprised 91 patients with PDD and 65 age- and sex-matched healthy controls. Resting state perfusion was investigated by single photon emission computed tomography, and group differences were assessed by Statistical Parametric Mapping. Brain connectivity was explored through a voxel-wise interregional correlation analysis using as covariate of interest the normalized values of clusters of voxels in which perfusion differences were found in group analysis. Significantly increased regional brain perfusion distribution covering a large part of the cerebellum was observed in patients as compared with controls. Patients showed a significant negative functional connectivity between the cerebellar cluster and caudate, bilaterally. This study demonstrated inverse relative perfusion between the cerebellum and the caudate in PDD. Functional uncoupling may be associated with a dysregulation between the role of the cerebellum in action control and of the caudate in action selection, initiation and decision making in the patients. The potential impact of the resting state condition and the possibility of mitochondrial impairment are discussed. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Detection of First-Line Drug Resistance Mutations and Drug-Protein Interaction Dynamics from Tuberculosis Patients in South India.

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Nachappa, Somanna Ajjamada; Neelambike, Sumana M; Amruthavalli, Chokkanna; Ramachandra, Nallur B

2018-05-01

Diagnosis of drug-resistant tuberculosis predominantly relies on culture-based drug susceptibility testing, which take weeks to produce a result and a more time-efficient alternative method is multiplex allele-specific PCR (MAS-PCR). Also, understanding the role of mutations in causing resistance helps better drug designing. To evaluate the ability of MAS-PCR in the detection of drug resistance and to understand the mechanism of interaction of drugs with mutant proteins in Mycobacterium tuberculosis. Detection of drug-resistant mutations using MAS-PCR and validation through DNA sequencing. MAS-PCR targeted five loci on three genes, katG 315 and inhA -15 for the drug isoniazid (INH), and rpoB 516, 526, and 531 for rifampicin (RIF). Furthermore, the sequence data were analyzed to study the effect on interaction of the anti-TB drug molecule with the target protein using in silico docking. We identified drug-resistant mutations in 8 out of 114 isolates with 2 of them as multidrug-resistant TB using MAS-PCR. DNA sequencing confirmed only six of these, recording a sensitivity of 85.7% and specificity of 99.3% for MAS-PCR. Molecular docking showed estimated free energy of binding (ΔG) being higher for RIF binding with RpoB S531L mutant. Codon 315 in KatG does not directly interact with INH but blocks the drug access to active site. We propose DNA sequencing-based drug resistance detection for TB, which is more accurate than MAS-PCR. Understanding the action of resistant mutations in disrupting the normal drug-protein interaction aids in designing effective drug alternatives.

A highly efficient approach to protein interactome mapping based on collaborative filtering framework.

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Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-09

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

Anhedonia correlates with abnormal functional connectivity of the superior temporal gyrus and the caudate nucleus in patients with first-episode drug-naive major depressive disorder.

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Yang, Xin-Hua; Tian, Kai; Wang, Dong-Fang; Wang, Yi; Cheung, Eric F C; Xie, Guang-Rong; Chan, Raymond C K

2017-08-15

Recent empirical findings have suggested that imbalanced neural networks may underlie the pathophysiology of major depressive disorder (MDD). However, the contribution of the superior temporal gyrus (STG) and the caudate nucleus to its pathophysiology remains unclear. Functional magnetic resonance imaging (MRI) date were acquired from 40 patients with first-episode drug-naive MDD and 36 matched healthy controls during wakeful rest. We used whole-brain voxel-wise statistical maps to quantify within-group resting state functional connectivity (RSFC) and between-group differences of bilateral caudate and STG seeds. Compared with healthy controls, first-episode MDD patients were found to have reduced connectivity between the ventral caudate and several brain regions including the superior frontal gyrus (SFG), the superior parietal lobule (SPL) and the middle temporal gyrus (MTG), as well as increased connectivity with the cuneus. We also found increased connectivity between the left STG and the precuneus, the angular gyrus and the cuneus. Moreover, we found that increased anhedonia severity was correlated with the magnitude of ventral caudate functional connectivity with the cuneus and the MTG in MDD patients. Due to our small sample size, we did not correct the statistical threshold in the correlation analyses between clinical variables and connectivity abnormalities. The present study suggests that anhedonia is mainly associated with altered ventral caudate-cortical connectivity and highlights the importance of the ventral caudate in the neurobiology of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Novel in silico multivariate mapping of intrinsic and anticorrelated connectivity to neurocognitive functional maps supports the maturational hypothesis of ADHD.

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de Lacy, Nina; Kodish, Ian; Rachakonda, Srinivas; Calhoun, Vince D

2018-04-22

From childhood to adolescence, strengthened coupling in frontal, striatal and parieto-temporal regions associated with cognitive control, and increased anticorrelation between task-positive and task-negative circuits, subserve the reshaping of behavior. ADHD is a common condition peaking in adolescence and regressing in adulthood, with a wide variety of cognitive control deficits. Alternate hypotheses of ADHD emphasize lagging circuitry refinement versus categorical differences in network function. However, quantifying the individual circuit contributions to behavioral findings, and relative roles of maturational versus categorical effects, is challenging in vivo or in meta-analyses using task-based paradigms within the same pipeline, given the multiplicity of neurobehavioral functions implicated. To address this, we analyzed 46 positively-correlated and anticorrelated circuits in a multivariate model in resting-state data from 504 age- and gender-matched youth, and created a novel in silico method to map individual quantified effects to reverse inference maps of 8 neurocognitive functions consistently implicated in ADHD, as well as dopamine and hyperactivity. We identified only age- and gender-related effects in intrinsic connectivity, and found that maturational refinement of circuits in youth with ADHD occupied 3-10x more brain locations than in typical development, with the footprint, effect size and contribution of individual circuits varying substantially. Our analysis supports the maturational hypothesis of ADHD, suggesting lagging connectivity reorganization within specific subnetworks of fronto-parietal control, ventral attention, cingulo-opercular, temporo-limbic and cerebellar sub-networks contribute across neurocognitive findings present in this complex condition. We present the first analysis of anti-correlated connectivity in ADHD and suggest new directions for exploring residual and non-responsive symptoms. © 2018 Wiley Periodicals, Inc.

Hybrid protein-synthetic polymer nanoparticles for drug delivery.

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Koseva, Neli S; Rydz, Joanna; Stoyanova, Ekaterina V; Mitova, Violeta A

2015-01-01

Among the most common nanoparticulate systems, the polymeric nanocarriers have a number of key benefits, which give a great choice of delivery platforms. Nevertheless, polymeric nanoparticles possess some limitations that include use of toxic solvents in the production process, polymer degradation, drug leakage outside the diseased tissue, and polymer cytotoxicity. The combination of polymers of biological and synthetic origin is an appealing modern strategy for the production of novel nanocarriers with unprecedented properties. Proteins' interface can play an important role in determining bioactivity and toxicity and gives perspective for future development of the polymer-based nanoparticles. The design of hybrid constructs composed of synthetic polymer and biological molecules such as proteins can be considered as a straightforward tool to integrate a broad spectrum of properties and biofunctions into a single device. This review discusses hybrid protein-synthetic polymer nanoparticles with different structures and levels in complexity and functionality, in view of their applications as drug delivery systems. © 2015 Elsevier Inc. All rights reserved.

Oxidative stress and CCN1 protein in human skin connective tissue aging

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Zhaoping Qin

2016-06-01

Full Text Available Reactive oxygen species (ROS is an important pathogenic factor involved in human aging. Human skin is a primary target of oxidative stress from ROS generated from both extrinsic and intrinsic sources, like ultraviolet irradiation (UV and endogenous oxidative metabolism. Oxidative stress causes the alterations of collagen-rich extracellular matrix (ECM, the hallmark of skin connective tissue aging. Age-related alteration of dermal collagenous ECM impairs skin structural integrity and creates a tissue microenvironment that promotes age-related skin diseases, such as poor wound healing and skin cancer. Here, we review recent advances in our understanding of oxidative stress and CCN1 protein (first member of CCN family proteins, a critical mediator of oxidative stress-induced skin connective tissue aging.

A sight on protein-based nanoparticles as drug/gene delivery systems.

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Salatin, Sara; Jelvehgari, Mitra; Maleki-Dizaj, Solmaz; Adibkia, Khosro

2015-01-01

Polymeric nanomaterials have extensively been applied for the preparation of targeted and controlled release drug/gene delivery systems. However, problems involved in the formulation of synthetic polymers such as using of the toxic solvents and surfactants have limited their desirable applications. In this regard, natural biomolecules including proteins and polysaccharide are suitable alternatives due to their safety. According to literature, protein-based nanoparticles possess many advantages for drug and gene delivery such as biocompatibility, biodegradability and ability to functionalize with targeting ligands. This review provides a general sight on the application of biodegradable protein-based nanoparticles in drug/gene delivery based on their origins. Their unique physicochemical properties that help them to be formulated as pharmaceutical carriers are also discussed.

An overview on the delivery of antitumor drug doxorubicin by carrier proteins.

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Agudelo, D; Bérubé, G; Tajmir-Riahi, H A

2016-07-01

Serum proteins play an increasing role as drug carriers in the clinical settings. In this review, we have compared the binding modalities of anticancer drug doxorubicin (DOX) to three model carrier proteins, human serum albumin (HSA), bovine serum albumin (BSA) and milk beta-lactoglobulin (β-LG) in order to determine the potential application of these model proteins in DOX delivery. Molecular modeling studies showed stronger binding of DOX with HSA than BSA and β-LG with the free binding energies of -10.75 (DOX-HSA), -9.31 (DOX-BSA) and -8.12kcal/mol (DOX-β-LG). Extensive H-boding network stabilizes DOX-protein conjugation and played a major role in drug-protein complex formation. DOX complexation induced major alterations of HSA and BSA conformations, while did not alter β-LG secondary structure. The literature review shows that these proteins can potentially be used for delivery of DOX in vitro and in vivo. Copyright © 2016 Elsevier B.V. All rights reserved.

Heterogeneity mapping of protein expression in tumors using quantitative immunofluorescence.

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Faratian, Dana; Christiansen, Jason; Gustavson, Mark; Jones, Christine; Scott, Christopher; Um, InHwa; Harrison, David J

2011-10-25

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor(1,2), and some of these sub-clones give rise to metastatic (and therefore lethal) disease. Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension(3), or on macrodissection(4). A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue(5), providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi

Fast mapping of global protein folding states by multivariate NMR:

DEFF Research Database (Denmark)

Malmendal, Anders; Underhaug, Jarl; Otzen, Daniel

2010-01-01

To obtain insight into the functions of proteins and their specific roles, it is important to establish efficient procedures for exploring the states that encapsulate their conformational space. Global Protein folding State mapping by multivariate NMR (GPS NMR) is a powerful high-throughput method......-lactalbumin in the presence of the anionic surfactant sodium dodecyl sulfate, SDS, and compare these with other surfactants, acid, denaturants and heat....

Structure-based drug design for G protein-coupled receptors.

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Congreve, Miles; Dias, João M; Marshall, Fiona H

2014-01-01

Our understanding of the structural biology of G protein-coupled receptors has undergone a transformation over the past 5 years. New protein-ligand complexes are described almost monthly in high profile journals. Appreciation of how small molecules and natural ligands bind to their receptors has the potential to impact enormously how medicinal chemists approach this major class of receptor targets. An outline of the key topics in this field and some recent examples of structure- and fragment-based drug design are described. A table is presented with example views of each G protein-coupled receptor for which there is a published X-ray structure, including interactions with small molecule antagonists, partial and full agonists. The possible implications of these new data for drug design are discussed. © 2014 Elsevier B.V. All rights reserved.

CNNcon: improved protein contact maps prediction using cascaded neural networks.

Directory of Open Access Journals (Sweden)

Wang Ding

Full Text Available BACKGROUNDS: Despite continuing progress in X-ray crystallography and high-field NMR spectroscopy for determination of three-dimensional protein structures, the number of unsolved and newly discovered sequences grows much faster than that of determined structures. Protein modeling methods can possibly bridge this huge sequence-structure gap with the development of computational science. A grand challenging problem is to predict three-dimensional protein structure from its primary structure (residues sequence alone. However, predicting residue contact maps is a crucial and promising intermediate step towards final three-dimensional structure prediction. Better predictions of local and non-local contacts between residues can transform protein sequence alignment to structure alignment, which can finally improve template based three-dimensional protein structure predictors greatly. METHODS: CNNcon, an improved multiple neural networks based contact map predictor using six sub-networks and one final cascade-network, was developed in this paper. Both the sub-networks and the final cascade-network were trained and tested with their corresponding data sets. While for testing, the target protein was first coded and then input to its corresponding sub-networks for prediction. After that, the intermediate results were input to the cascade-network to finish the final prediction. RESULTS: The CNNcon can accurately predict 58.86% in average of contacts at a distance cutoff of 8 Å for proteins with lengths ranging from 51 to 450. The comparison results show that the present method performs better than the compared state-of-the-art predictors. Particularly, the prediction accuracy keeps steady with the increase of protein sequence length. It indicates that the CNNcon overcomes the thin density problem, with which other current predictors have trouble. This advantage makes the method valuable to the prediction of long length proteins. As a result, the effective

Non-invasive and real-time passive acoustic mapping of ultrasound-mediated drug delivery

International Nuclear Information System (INIS)

Choi, James J; Carlisle, Robert C; Coviello, Christian; Coussios, Constantin-C; Seymour, Len

2014-01-01

New classes of biologically active materials, such as viruses, siRNA, antibodies and a wide range of engineered nanoparticles have emerged as potent agents for diagnosing and treating diseases, yet many of these agents fail because there is no effective route of delivery to their intended targets. Focused ultrasound and its ability to drive microbubble-seeded cavitation have been shown to facilitate drug delivery. However, cavitation is difficult to control temporally and spatially, making prediction of therapeutic outcomes deep in the body difficult. Here, we utilized passive acoustic mapping in vivo to understand how ultrasound parameters influence cavitation dynamics and to correlate spatial maps of cavitation to drug delivery. Focused ultrasound (center frequency: 0.5 MHz, peak-rarefactional pressure: 1.2 MPa, pulse length: 25 cycles or 50,000 cycles, pulse repetition interval: 0.02, 0.2, 1 or 3 s, number of pulses: 80 pulses) was applied to murine xenograft-model tumors in vivo during systemic injection of microbubbles with and without cavitation-sensitive liposomes or type 5 adenoviruses. Analysis of in vivo cavitation dynamics through several pulses revealed that cavitation was more efficiently produced at a lower pulse repetition frequency of 1 Hz than at 50 Hz. Within a pulse, inertial cavitation activity was shown to persist but reduced to 50% and 25% of its initial magnitude in 4.3 and 29.3 ms, respectively. Both through several pulses and within a pulse, the spatial distribution of cavitation was shown to change in time due to variations in microbubble distribution present in tumors. Finally, we demonstrated that the centroid of the mapped cavitation activity was within 1.33  ±  0.6 mm and 0.36 mm from the centroid location of drug release from liposomes and expression of the reporter gene encoded by the adenovirus, respectively. Thus passive acoustic mapping not only unraveled key mechanisms whereby a successful outcome is

The calcium-binding protein ALG-2 regulates protein secretion and trafficking via interactions with MISSL and MAP1B proteins.

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Takahara, Terunao; Inoue, Kuniko; Arai, Yumika; Kuwata, Keiko; Shibata, Hideki; Maki, Masatoshi

2017-10-13

Mobilization of intracellular calcium is essential for a wide range of cellular processes, including signal transduction, apoptosis, and vesicular trafficking. Several lines of evidence have suggested that apoptosis-linked gene 2 (ALG-2, also known as PDCD6 ), a calcium-binding protein, acts as a calcium sensor linking calcium levels with efficient vesicular trafficking, especially at the endoplasmic reticulum (ER)-to-Golgi transport step. However, how ALG-2 regulates these processes remains largely unclear. Here, we report that M APK1- i nteracting and s pindle- s tabilizing (MISS)- l ike (MISSL), a previously uncharacterized protein, interacts with ALG-2 in a calcium-dependent manner. Live-cell imaging revealed that upon a rise in intracellular calcium levels, GFP-tagged MISSL (GFP-MISSL) dynamically relocalizes in a punctate pattern and colocalizes with ALG-2. MISSL knockdown caused disorganization of the components of the ER exit site, the ER-Golgi intermediate compartment, and Golgi. Importantly, knockdown of either MISSL or ALG-2 attenuated the secretion of se creted a lkaline p hosphatase (SEAP), a model secreted cargo protein, with similar reductions in secretion by single- and double-protein knockdowns, suggesting that MISSL and ALG-2 act in the same pathway to regulate the secretion process. Furthermore, ALG-2 or MISSL knockdown delayed ER-to-Golgi transport of procollagen type I. We also found that ALG-2 and MISSL interact with microtubule-associated protein 1B (MAP1B) and that MAP1B knockdown reverts the reduced secretion of SEAP caused by MISSL or ALG-2 depletion. These results suggest that a change in the intracellular calcium level plays a role in regulation of the secretory pathway via interaction of ALG-2 with MISSL and MAP1B. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Mappability of drug-like space: towards a polypharmacologically competent map of drug-relevant compounds

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Sidorov, Pavel; Gaspar, Helena; Marcou, Gilles; Varnek, Alexandre; Horvath, Dragos

2015-12-01

Intuitive, visual rendering—mapping—of high-dimensional chemical spaces (CS), is an important topic in chemoinformatics. Such maps were so far dedicated to specific compound collections—either limited series of known activities, or large, even exhaustive enumerations of molecules, but without associated property data. Typically, they were challenged to answer some classification problem with respect to those same molecules, admired for their aesthetical virtues and then forgotten—because they were set-specific constructs. This work wishes to address the question whether a general, compound set-independent map can be generated, and the claim of "universality" quantitatively justified, with respect to all the structure-activity information available so far—or, more realistically, an exploitable but significant fraction thereof. The "universal" CS map is expected to project molecules from the initial CS into a lower-dimensional space that is neighborhood behavior-compliant with respect to a large panel of ligand properties. Such map should be able to discriminate actives from inactives, or even support quantitative neighborhood-based, parameter-free property prediction (regression) models, for a wide panel of targets and target families. It should be polypharmacologically competent, without requiring any target-specific parameter fitting. This work describes an evolutionary growth procedure of such maps, based on generative topographic mapping, followed by the validation of their polypharmacological competence. Validation was achieved with respect to a maximum of exploitable structure-activity information, covering all of Homo sapiens proteins of the ChEMBL database, antiparasitic and antiviral data, etc. Five evolved maps satisfactorily solved hundreds of activity-based ligand classification challenges for targets, and even in vivo properties independent from training data. They also stood chemogenomics-related challenges, as cumulated responsibility

Solution NMR Spectroscopy in Target-Based Drug Discovery.

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Li, Yan; Kang, Congbao

2017-08-23

Solution NMR spectroscopy is a powerful tool to study protein structures and dynamics under physiological conditions. This technique is particularly useful in target-based drug discovery projects as it provides protein-ligand binding information in solution. Accumulated studies have shown that NMR will play more and more important roles in multiple steps of the drug discovery process. In a fragment-based drug discovery process, ligand-observed and protein-observed NMR spectroscopy can be applied to screen fragments with low binding affinities. The screened fragments can be further optimized into drug-like molecules. In combination with other biophysical techniques, NMR will guide structure-based drug discovery. In this review, we describe the possible roles of NMR spectroscopy in drug discovery. We also illustrate the challenges encountered in the drug discovery process. We include several examples demonstrating the roles of NMR in target-based drug discoveries such as hit identification, ranking ligand binding affinities, and mapping the ligand binding site. We also speculate the possible roles of NMR in target engagement based on recent processes in in-cell NMR spectroscopy.

Optimization of protein and peptide drugs based on the mechanisms of kidney clearance.

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Huang, Jiaguo; Wu, Huizi

2018-05-30

Development of proteins and peptides into drugs has been considered as a promising strategy to target certain diseases. However, only few proteins and peptides has been approved as new drugs into the market each year. One major problem is that proteins and peptides often exhibit short plasma half-life times, which limits the application for their clinical use. In most cases a short half-life time is not effective to deliver sufficient amount of drugs to the target organs and tissues, which is generally caused by fast renal clearance and low plasma stability due to proteolytic degradation during systemic circulation, because the most common clearance pathway of small proteins and peptides is through glomerular filtration by the kidneys. In this review, enzymatic degradation of proteins and peptides were discussed. Furthermore, several approaches to lengthen the half-life of peptides and proteins drugs based on the unique structures of glomerular capillary wall and the mechanisms of glomerular filtration were summarized, such as increasing the size and hydrodynamic diameter; increasing the negative charge to delay the filtration; increasing plasma protein binding to decrease plasma clearance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Human Prostate Cancer Hallmarks Map

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Datta, Dipamoy; Aftabuddin, Md.; Gupta, Dinesh Kumar; Raha, Sanghamitra; Sen, Prosenjit

2016-01-01

Human prostate cancer is a complex heterogeneous disease that mainly affects elder male population of the western world with a high rate of mortality. Acquisitions of diverse sets of hallmark capabilities along with an aberrant functioning of androgen receptor signaling are the central driving forces behind prostatic tumorigenesis and its transition into metastatic castration resistant disease. These hallmark capabilities arise due to an intense orchestration of several crucial factors, including deregulation of vital cell physiological processes, inactivation of tumor suppressive activity and disruption of prostate gland specific cellular homeostasis. The molecular complexity and redundancy of oncoproteins signaling in prostate cancer demands for concurrent inhibition of multiple hallmark associated pathways. By an extensive manual curation of the published biomedical literature, we have developed Human Prostate Cancer Hallmarks Map (HPCHM), an onco-functional atlas of human prostate cancer associated signaling and events. It explores molecular architecture of prostate cancer signaling at various levels, namely key protein components, molecular connectivity map, oncogenic signaling pathway map, pathway based functional connectivity map etc. Here, we briefly represent the systems level understanding of the molecular mechanisms associated with prostate tumorigenesis by considering each and individual molecular and cell biological events of this disease process. PMID:27476486

Identifying secondary structures in proteins using NMR chemical shift 3D correlation maps

Science.gov (United States)

Kumari, Amrita; Dorai, Kavita

2013-06-01

NMR chemical shifts are accurate indicators of molecular environment and have been extensively used as aids in protein structure determination. This work focuses on creating empirical 3D correlation maps of backbone chemical shift nuclei for use as identifiers of secondary structure elements in proteins. A correlated database of backbone nuclei chemical shifts was constructed from experimental structural data gathered from entries in the Protein Data Bank (PDB) as well as isotropic chemical shift values from the RefDB database. Rigorous statistical analysis of the maps led to the conclusion that specific correlations between triplets of backbone chemical shifts are best able to differentiate between different secondary structures such as α-helices, β-strands and turns. The method is compared with similar techniques that use NMR chemical shift information as aids in biomolecular structure determination and performs well in tests done on experimental data determined for different types of proteins, including large multi-domain proteins and membrane proteins.

HIV infection and drugs of abuse: role of acute phase proteins.

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Samikkannu, Thangavel; Rao, Kurapati V K; Arias, Adriana Y; Kalaichezian, Aarthi; Sagar, Vidya; Yoo, Changwon; Nair, Madhavan P N

2013-09-17

HIV infection and drugs of abuse such as methamphetamine (METH), cocaine, and alcohol use have been identified as risk factors for triggering inflammation. Acute phase proteins such as C-reactive protein (CRP) and serum amyloid A (SAA) are the biomarkers of inflammation. Hence, the interactive effect of drugs of abuse with acute phase proteins in HIV-positive subjects was investigated. Plasma samples were utilized from 75 subjects with METH use, cocaine use, alcohol use, and HIV-positive alone and HIV-positive METH, cocaine, and alcohol users, and age-matched control subjects. The plasma CRP and SAA levels were measured by ELISA and western blot respectively and the CD4 counts were also measured. Observed results indicated that the CRP and SAA levels in HIV-positive subjects who are METH, cocaine and alcohol users were significantly higher when compared with either drugs of abuse or HIV-positive alone. The CD4 counts were also dramatically reduced in HIV-positive with drugs of abuse subjects compared with only HIV-positive subjects. These results suggest that, in HIV-positive subjects, drugs of abuse increase the levels of CRP and SAA, which may impact on the HIV infection and disease progression.

Site-specific antibody-drug conjugates: the nexus of bioorthogonal chemistry, protein engineering, and drug development.

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Agarwal, Paresh; Bertozzi, Carolyn R

2015-02-18

Antibody-drug conjugates (ADCs) combine the specificity of antibodies with the potency of small molecules to create targeted drugs. Despite the simplicity of this concept, generation of clinically successful ADCs has been very difficult. Over the past several decades, scientists have learned a great deal about the constraints on antibodies, linkers, and drugs as they relate to successful construction of ADCs. Once these components are in hand, most ADCs are prepared by nonspecific modification of antibody lysine or cysteine residues with drug-linker reagents, which results in heterogeneous product mixtures that cannot be further purified. With advances in the fields of bioorthogonal chemistry and protein engineering, there is growing interest in producing ADCs by site-specific conjugation to the antibody, yielding more homogeneous products that have demonstrated benefits over their heterogeneous counterparts in vivo. Here, we chronicle the development of a multitude of site-specific conjugation strategies for assembly of ADCs and provide a comprehensive account of key advances and their roots in the fields of bioorthogonal chemistry and protein engineering.

Semiconductor technology in protein kinase research and drug discovery: sensing a revolution.

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Bhalla, Nikhil; Di Lorenzo, Mirella; Estrela, Pedro; Pula, Giordano

2017-02-01

Since the discovery of protein kinase activity in 1954, close to 600 kinases have been discovered that have crucial roles in cell physiology. In several pathological conditions, aberrant protein kinase activity leads to abnormal cell and tissue physiology. Therefore, protein kinase inhibitors are investigated as potential treatments for several diseases, including dementia, diabetes, cancer and autoimmune and cardiovascular disease. Modern semiconductor technology has recently been applied to accelerate the discovery of novel protein kinase inhibitors that could become the standard-of-care drugs of tomorrow. Here, we describe current techniques and novel applications of semiconductor technologies in protein kinase inhibitor drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

Decreased long- and short-range functional connectivity at rest in drug-naive major depressive disorder.

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Guo, Wenbin; Liu, Feng; Chen, Jindong; Wu, Renrong; Zhang, Zhikun; Yu, Miaoyu; Xue, Zhimin; Zhao, Jingping

2016-08-01

Abnormal functional connectivity has been observed in major depressive disorder. Anatomical distance may affect functional connectivity in patients with major depressive disorder. However, whether and how anatomical distance affects functional connectivity at rest remains unclear in drug-naive patients with major depressive disorder. Forty-four patients with major depressive disorder, as well as 44 age-, sex- and education-matched healthy controls, underwent resting-state functional magnetic resonance imaging scanning. Regional functional connectivity strength was calculated for each voxel in the whole brain, which was further divided into short- and long-range functional connectivity strength. The patients showed decreased long-range positive functional connectivity strength in the right inferior parietal lobule, as well as decreased short-range positive functional connectivity strength in the right insula and right superior temporal gyrus relative to those of the controls. No significant correlations existed between abnormal functional connectivity strength and the clinical variables of the patients. The findings revealed that anatomical distance decreases long- and short-range functional connectivity strength in patients with major depressive disorder, which may underlie the neurobiology of major depressive disorder. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Identification, activity and disulfide connectivity of C-di-GMP regulating proteins in Mycobacterium tuberculosis.

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Kajal Gupta

2010-11-01

Full Text Available C-di-GMP, a bacterial second messenger plays a key role in survival and adaptation of bacteria under different environmental conditions. The level of c-di-GMP is regulated by two opposing activities, namely diguanylate cyclase (DGC and phosphodiesterase (PDE-A exhibited by GGDEF and EAL domain, respectively in the same protein. Previously, we reported a bifunctional GGDEF-EAL domain protein, MSDGC-1 from Mycobacterium smegmatis showing both these activities (Kumar and Chatterji, 2008. In this current report, we have identified and characterized the homologous protein from Mycobacterium tuberculosis (Rv 1354c named as MtbDGC. MtbDGC is also a bifunctional protein, which can synthesize and degrade c-di-GMP in vitro. Further we expressed Mtbdgc in M. smegmatis and it was able to complement the MSDGC-1 knock out strain by restoring the long term survival of M. smegmatis. Another protein Rv 1357c, named as MtbPDE, is an EAL domain protein and degrades c-di-GMP to pGpG in vitro. Rv1354c and 1357c have seven cysteine amino acids in their sequence, distributed along the full length of the protein. Disulfide bonds play an important role in stabilizing protein structure and regulating protein function. By proteolytic digestion and mass spectrometric analysis of MtbDGC, connectivity between cysteine pairs Cys94-Cys584, Cys2-Cys479 and Cys429-Cys614 was determined, whereas the third cysteine (Cys406 from N terminal was found to be free in MtbDGC protein, which was further confirmed by alkylation with iodoacetamide labeling. Bioinformatics modeling investigations also supported the pattern of disulfide connectivity obtained by Mass spectrometric analysis. Cys406 was mutated to serine by site directed mutagenesis and the mutant MtbC406S was not found to be active and was not able to synthesize or degrade c-di-GMP. The disulfide connectivity established here would help further in understanding the structure - function relationship in MtbDGC.

Mapping of the Mouse Actin Capping Protein Beta Subunit Gene

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Cooper John A

2000-07-01

Full Text Available Abstract Background Capping protein (CP, a heterodimer of α and β subunits, is found in all eukaryotes. CP binds to the barbed ends of actin filaments in vitro and controls actin assembly and cell motility in vivo. Vertebrates have three isoforms of CPβ produced by alternatively splicing from one gene; lower organisms have one gene and one isoform. Results We isolated genomic clones corresponding to the β subunit of mouse CP and identified its chromosomal location by interspecies backcross mapping. Conclusions The CPβ gene (Cappb1 mapped to Chromosome 4 between Cdc42 and D4Mit312. Three mouse mutations, snubnose, curly tail, and cribriform degeneration, map in the vicinity of the β gene.

Dissecting genomic hotspots underlying seed protein, oil, and sucrose content in an interspecific mapping population of soybean using high-density linkage mapping.

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Patil, Gunvant; Vuong, Tri D; Kale, Sandip; Valliyodan, Babu; Deshmukh, Rupesh; Zhu, Chengsong; Wu, Xiaolei; Bai, Yonghe; Yungbluth, Dennis; Lu, Fang; Kumpatla, Siva; Grover Shannon, J; Varshney, Rajeev K; Nguyen, Henry T

2018-04-04

The cultivated [Glycine max (L) Merr.] and wild [Glycine soja Siebold & Zucc.] soybean species comprise wide variation in seed composition traits. Compared to wild soybean, cultivated soybean contains low protein, high oil and high sucrose. In this study, an inter-specific population was derived from a cross between G. max (Williams 82) and G. soja (PI 483460B). This recombinant inbred line (RIL) population of 188 lines was sequenced at 0.3x depth. Based on 91,342 single nucleotide polymorphisms (SNPs), recombination events in RILs were defined, and a high-resolution bin map was developed (4,070 bins). In addition to bin mapping, QTL analysis for protein, oil and sucrose was performed using 3,343 polymorphic SNPs (3K-SNP), derived from Illumina Infinium BeadChip sequencing platform. The QTL regions from both platforms were compared and a significant concordance was observed between bin and 3K-SNP markers. Importantly, the bin map derived from next generation sequencing technology enhanced mapping resolution (from 1325 Kb to 50 Kb). A total of 5, 9 and 4 QTLs were identified for protein, oil and sucrose content, respectively and some of the QTLs coincided with soybean domestication related genomic loci. The major QTL for protein and oil was mapped on Chr. 20 (qPro_20) and suggested negative correlation between oil and protein. In terms of sucrose content, a novel and major QTL was identified on Chr. 8 (qSuc_08) and harbors putative genes involved in sugar transport. In addition, genome-wide association (GWAS) using 91,342 SNPs confirmed the genomic loci derived from QTL mapping. A QTL based haplotype using whole genome resequencing of 106 diverse soybean lines identified unique allelic variation in wild soybean that could be utilized to widen the genetic base in cultivated soybean. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Cysteine-Rich Peptide Family with Unusual Disulfide Connectivity from Jasminum sambac.

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Kumari, Geeta; Serra, Aida; Shin, Joon; Nguyen, Phuong Q T; Sze, Siu Kwan; Yoon, Ho Sup; Tam, James P

2015-11-25

Cysteine-rich peptides (CRPs) are natural products with privileged peptidyl structures that represent a potentially rich source of bioactive compounds. Here, the discovery and characterization of a novel plant CRP family, jasmintides from Jasminum sambac of the Oleaceae family, are described. Two 27-amino acid jasmintides (jS1 and jS2) were identified at the gene and protein levels. Disulfide bond mapping of jS1 by mass spectrometry and its confirmation by NMR spectroscopy revealed disulfide bond connectivity of C-1-C-5, C-2-C-4, and C-3-C-6, a cystine motif that has not been reported in plant CRPs. Structural determination showed that jS1 displays a well-defined structure framed by three short antiparallel β-sheets. Genomic analysis showed that jasmintides share a three-domain precursor arrangement with a C-terminal mature domain preceded by a long pro-domain of 46 residues and an intron cleavage site between the signal sequence and pro-domain. The compact cysteine-rich structure together with an N-terminal pyroglutamic acid residue confers jasmintides high resistance to heat and enzymatic degradation, including exopeptidase treatment. Collectively, these results reveal a new plant CRP structure with an unusual cystine connectivity, which could be useful as a scaffold for designing peptide drugs.

Identify drug repurposing candidates by mining the protein data bank.

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Moriaud, Fabrice; Richard, Stéphane B; Adcock, Stewart A; Chanas-Martin, Laetitia; Surgand, Jean-Sébastien; Ben Jelloul, Marouane; Delfaud, François

2011-07-01

Predicting off-targets by computational methods is gaining increasing interest in early-stage drug discovery. Here, we present a computational method based on full 3D comparisons of 3D structures. When a similar binding site is detected in the Protein Data Bank (PDB) (or any protein structure database), it is possible that the corresponding ligand also binds to that similar site. On one hand, this target hopping case is probably rare because it requires a high similarity between the binding sites. On the other hand, it could be a strong rational evidence to highlight possible off-target reactions and possibly a potential undesired side effect. This target-based drug repurposing can be extended a significant step further with the capability of searching the full surface of all proteins in the PDB, and therefore not relying on pocket detection. Using this approach, we describe how MED-SuMo reproduces the repurposing of tadalafil from PDE5A to PDE4A and a structure of PDE4A with tadalafil. Searching for local protein similarities generates more hits than for whole binding site similarities and therefore fragment repurposing is more likely to occur than for drug-sized compounds. In this work, we illustrate that by mining the PDB for proteins sharing similarities with the hinge region of protein kinases. The experimentally validated examples, biotin carboxylase and synapsin, are retrieved. Further to fragment repurposing, this approach can be applied to the detection of druggable sites from 3D structures. This is illustrated with detection of the protein kinase hinge motif in the HIV-RT non-nucleosidic allosteric site.

Resting state cortico-cerebellar functional connectivity networks: A comparison of anatomical and self-organizing map approaches

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Jessica A Bernard

2012-08-01

Full Text Available The cerebellum plays a role in a wide variety of complex behaviors. In order to better understand the role of the cerebellum in human behavior, it is important to know how this structure interacts with cortical and other subcortical regions of the brain. To date, several studies have investigated the cerebellum using resting-state functional connectivity magnetic resonance imaging (fcMRI; Buckner et al., 2011; Krienen & Buckner, 2009; O’Reilly et al., 2009. However, none of this work has taken an anatomically-driven approach. Furthermore, though detailed maps of cerebral cortex and cerebellum networks have been proposed using different network solutions based on the cerebral cortex (Buckner et al., 2011, it remains unknown whether or not an anatomical lobular breakdown best encompasses the networks of the cerebellum. Here, we used fcMRI to create an anatomically-driven cerebellar connectivity atlas. Timecourses were extracted from the lobules of the right hemisphere and vermis. We found distinct networks for the individual lobules with a clear division into motor and non-motor regions. We also used a self-organizing map algorithm to parcellate the cerebellum. This allowed us to investigate redundancy and independence of the anatomically identified cerebellar networks. We found that while anatomical boundaries in the anterior cerebellum provide functional subdivisions of a larger motor grouping defined using our self-organizing map algorithm, in the posterior cerebellum, the lobules were made up of sub-regions associated with distinct functional networks. Together, our results indicate that the lobular boundaries of the human cerebellum are not indicative of functional boundaries, though anatomical divisions can be useful, as is the case of the anterior cerebellum. Additionally, driving the analyses from the cerebellum is key to determining the complete picture of functional connectivity within the structure.

Resting state functional connectivity magnetic resonance imaging integrated with intraoperative neuronavigation for functional mapping after aborted awake craniotomy

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Batra, Prag; Bandt, S. Kathleen; Leuthardt, Eric C.

2016-01-01

Background: Awake craniotomy is currently the gold standard for aggressive tumor resections in eloquent cortex. However, a significant subset of patients is unable to tolerate this procedure, particularly the very young or old or those with psychiatric comorbidities, cardiopulmonary comorbidities, or obesity, among other conditions. In these cases, typical alternative procedures include biopsy alone or subtotal resection, both of which are associated with diminished surgical outcomes. Case Description: Here, we report the successful use of a preoperatively obtained resting state functional connectivity magnetic resonance imaging (MRI) integrated with intraoperative neuronavigation software in order to perform functional cortical mapping in the setting of an aborted awake craniotomy due to loss of airway. Conclusion: Resting state functional connectivity MRI integrated with intraoperative neuronavigation software can provide an alternative option for functional cortical mapping in the setting of an aborted awake craniotomy. PMID:26958419

Maximum flow approach to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv from protein-protein interaction network.

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Melak, Tilahun; Gakkhar, Sunita

2015-12-01

In spite of the implementations of several strategies, tuberculosis (TB) is overwhelmingly a serious global public health problem causing millions of infections and deaths every year. This is mainly due to the emergence of drug-resistance varieties of TB. The current treatment strategies for the drug-resistance TB are of longer duration, more expensive and have side effects. This highlights the importance of identification and prioritization of targets for new drugs. This study has been carried out to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv based on their flow to resistance genes. The weighted proteome interaction network of the pathogen was constructed using a dataset from STRING database. Only a subset of the dataset with interactions that have a combined score value ≥770 was considered. Maximum flow approach has been used to prioritize potential drug targets. The potential drug targets were obtained through comparative genome and network centrality analysis. The curated set of resistance genes was retrieved from literatures. Detail literature review and additional assessment of the method were also carried out for validation. A list of 537 proteins which are essential to the pathogen and non-homologous with human was obtained from the comparative genome analysis. Through network centrality measures, 131 of them were found within the close neighborhood of the centre of gravity of the proteome network. These proteins were further prioritized based on their maximum flow value to resistance genes and they are proposed as reliable drug targets of the pathogen. Proteins which interact with the host were also identified in order to understand the infection mechanism. Potential drug targets of Mycobacterium tuberculosis H37Rv were successfully prioritized based on their flow to resistance genes of existing drugs which is believed to increase the druggability of the targets since inhibition of a protein that has a maximum flow to

Comparative characteristic of the methods of protein antigens epitope mapping

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O. Yu. Galkin

2014-08-01

Full Text Available Comparative analysis of experimental methods of epitope mapping of protein antigens has been carried out. The vast majority of known techniques are involved in immunochemical study of the interaction of protein molecules or peptides with antibodies of corresponding specifici­ty. The most effective and widely applicable metho­dological techniques are those that use synthetic and genetically engineered peptides. Over the past 30 years, these groups of methods have travelled a notable evolutionary path up to the maximum automation and the detection of antigenic determinants of various types (linear and conformational epitopes, and mimotopes. Most of epitope searching algorithms were integrated into a computer program, which greatly facilitates the analysis of experimental data and makes it possible to create spatial models. It is possible to use comparative epitope mapping for solving the applied problems; this less time-consuming method is based on the analysis of competition between different antibodies interactions with the same antigen. The physical method of antigenic structure study is X-ray analysis of antigen-antibody complexes, which may be applied only to crystallizing­ proteins, and nuclear magnetic resonance.

Identification of polycystic ovary syndrome potential drug targets based on pathobiological similarity in the protein-protein interaction network

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Li, Wan; Wei, Wenqing; Li, Yiran; Xie, Ruiqiang; Guo, Shanshan; Wang, Yahui; Jiang, Jing; Chen, Binbin; Lv, Junjie; Zhang, Nana; Chen, Lina; He, Weiming

2016-01-01

Polycystic ovary syndrome (PCOS) is one of the most common endocrinological disorders in reproductive aged women. PCOS and Type 2 Diabetes (T2D) are closely linked in multiple levels and possess high pathobiological similarity. Here, we put forward a new computational approach based on the pathobiological similarity to identify PCOS potential drug target modules (PPDT-Modules) and PCOS potential drug targets in the protein-protein interaction network (PPIN). From the systems level and biological background, 1 PPDT-Module and 22 PCOS potential drug targets were identified, 21 of which were verified by literatures to be associated with the pathogenesis of PCOS. 42 drugs targeting to 13 PCOS potential drug targets were investigated experimentally or clinically for PCOS. Evaluated by independent datasets, the whole PPDT-Module and 22 PCOS potential drug targets could not only reveal the drug response, but also distinguish the statuses between normal and disease. Our identified PPDT-Module and PCOS potential drug targets would shed light on the treatment of PCOS. And our approach would provide valuable insights to research on the pathogenesis and drug response of other diseases. PMID:27191267

Hydrophobic Interaction Chromatography for Bottom-Up Proteomics Analysis of Single Proteins and Protein Complexes.

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Rackiewicz, Michal; Große-Hovest, Ludger; Alpert, Andrew J; Zarei, Mostafa; Dengjel, Jörn

2017-06-02

Hydrophobic interaction chromatography (HIC) is a robust standard analytical method to purify proteins while preserving their biological activity. It is widely used to study post-translational modifications of proteins and drug-protein interactions. In the current manuscript we employed HIC to separate proteins, followed by bottom-up LC-MS/MS experiments. We used this approach to fractionate antibody species followed by comprehensive peptide mapping as well as to study protein complexes in human cells. HIC-reversed-phase chromatography (RPC)-mass spectrometry (MS) is a powerful alternative to fractionate proteins for bottom-up proteomics experiments making use of their distinct hydrophobic properties.

Exploring the binding sites and binding mechanism for hydrotrope encapsulated griseofulvin drug on γ-tubulin protein.

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Shubhadip Das

Full Text Available The protein γ-tubulin plays an important role in centrosomal clustering and this makes it an attractive therapeutic target for treating cancers. Griseofulvin, an antifungal drug, has recently been used to inhibit proliferation of various types of cancer cells. It can also affect the microtubule dynamics by targeting the γ-tubulin protein. So far, the binding pockets of γ-tubulin protein are not properly identified and the exact mechanism by which the drug binds to it is an area of intense speculation and research. The aim of the present study is to investigate the binding mechanism and binding affinity of griseofulvin on γ-tubulin protein using classical molecular dynamics simulations. Since the drug griseofulvin is sparingly soluble in water, here we also present a promising approach for formulating and achieving delivery of hydrophobic griseofulvin drug via hydrotrope sodium cumene sulfonate (SCS cluster. We observe that the binding pockets of γ-tubulin protein are mainly formed by the H8, H9 helices and S7, S8, S14 strands and the hydrophobic interactions between the drug and γ-tubulin protein drive the binding process. The release of the drug griseofulvin from the SCS cluster is confirmed by the coordination number analysis. We also find hydrotrope-induced alteration of the binding sites of γ-tubulin protein and the weakening of the drug-protein interactions.

A role for Pyk2 and Src in linking G-protein-coupled receptors with MAP kinase activation.

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Dikic, I; Tokiwa, G; Lev, S; Courtneidge, S A; Schlessinger, J

1996-10-10

The mechanisms by which mitogenic G-protein-coupled receptors activate the MAP kinase signalling pathway are poorly understood. Candidate protein tyrosine kinases that link G-protein-coupled receptors with MAP kinase include Src family kinases, the epidermal growth factor receptor, Lyn and Syk. Here we show that lysophosphatidic acid (LPA) and bradykinin induce tyrosine phosphorylation of Pyk2 and complex formation between Pyk2 and activated Src. Moreover, tyrosine phosphorylation of Pyk2 leads to binding of the SH2 domain of Src to tyrosine 402 of Pyk2 and activation of Src. Transient overexpression of a dominant interfering mutant of Pyk2 or the protein tyrosine kinase Csk reduces LPA- or bradykinin-induced activation of MAP kinase. LPA- or bradykinin-induced MAP kinase activation was also inhibited by overexpression of dominant interfering mutants of Grb2 and Sos. We propose that Pyk2 acts with Src to link Gi- and Gq-coupled receptors with Grb2 and Sos to activate the MAP kinase signalling pathway in PC12 cells.

A biotin-drug extraction and acid dissociation (BEAD) procedure to eliminate matrix and drug interference in a protein complex anti-drug antibody (ADA) isotype specific assay.

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Niu, Hongmei; Klem, Thomas; Yang, Jinsong; Qiu, Yongchang; Pan, Luying

2017-07-01

Monitoring anti-drug antibody (ADA) responses in patients receiving protein therapeutics treatment is an important safety assessment for regulatory agencies, drug manufacturers, clinicians and patients. Recombinant human IGF-1/IGFBP-3 (rhIGF-1/rhIGFBP-3) is a 1:1 formulation of naturally occurring protein complex. The individual IGF-1 and IGFBP-3 proteins have multiple binding partners in serum matrix with high binding affinity to each other, which presents challenges in ADA assay development. We have developed a biotin-drug extraction with acid dissociation (BEAD) procedure followed by an electrochemiluminescence (ECL) direct assay to overcome matrix and drug interference. The method utilizes two step acid dissociation and excess biotin-drug to extract total ADA, which are further captured by soluble biotin-drug and detected in an ECL semi-homogeneous direct assay format. The pre-treatment method effectively eliminates interference by serum matrix and free drug, and enhances assay sensitivity. The assays passed acceptance criteria for all validation parameters, and have been used for clinical sample Ab testing. This method principle exemplifies a new approach for anti-isotype ADA assays, and could be an effective strategy for neutralizing antibody (NAb), pharmacokinetic (PK) and biomarker analysis in need of overcoming interference factors. Copyright © 2017 Elsevier B.V. All rights reserved.

Influence of Stress Connected with Moving to a New Farm on Potentially MAP-Infected Mouflons.

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Pribylova-Dziedzinska, Radka; Slana, Iva; Lamka, Jiri; Pavlik, Ivo

2014-01-01

There is no European legislation concerning paratuberculosis that requires that imported animals be kept in quarantine and commonly they are directly released into areas with other animals. In this study, detection of latent infection of paratuberculosis in healthy mouflons previously diagnosed as paratuberculosis-free, but originating from a real time quantitative PCR- (qPCR-) positive herd, occurred after their transport to a new farm. During a twelve-day quarantine period, all mouflons irregularly shed Mycobacterium avium subsp. paratuberculosis (MAP) in faeces, and in a small number of cases also in milk. After the animals were released from quarantine, MAP was detected for a further two days, after which, testing was negative, except in one case. Therefore, the stress connected with transport, novel environment, dietary change, or limited area with high density of animals might have contributed to the induction of paratuberculosis and the shedding of MAP from the animals, previously diagnosed as MAP-negative. According to these results, the keeping of imported animals in quarantine and their examination for MAP presence not only before the transport but also afterwards should be recommended. The designation of a particular area of a farm as a quarantine enclosure could help to mitigate the impact of stress caused by a confined space with a high density of animals.

A two-dimensional proteome reference map of Herbaspirillum seropedicae proteins.

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Chaves, Daniela Fojo Seixas; Ferrer, Pércio Pereira; de Souza, Emanuel Maltempi; Gruz, Leonardo Magalhães; Monteiro, Rose Adele; de Oliveira Pedrosa, Fábio

2007-10-01

Herbaspirillum seropedicae is an endophytic diazotroph associated with economically important crops such as rice, sugarcane, and wheat. Here, we present a 2-D reference map for H. seropedicae. Using MALDI-TOF-MS we identified 205 spots representing 173 different proteins with a calculated average of 1.18 proteins/gene. Seventeen hypothetical or conserved hypothetical ORFs were shown to code for true gene products. These data will support the genome annotation process and provide a basis on which to undertake comparative proteomic studies.

Plant protein-based hydrophobic fine and ultrafine carrier particles in drug delivery systems.

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Malekzad, Hedieh; Mirshekari, Hamed; Sahandi Zangabad, Parham; Moosavi Basri, S M; Baniasadi, Fazel; Sharifi Aghdam, Maryam; Karimi, Mahdi; Hamblin, Michael R

2018-02-01

For thousands of years, plants and their products have been used as the mainstay of medicinal therapy. In recent years, besides attempts to isolate the active ingredients of medicinal plants, other new applications of plant products, such as their use to prepare drug delivery vehicles, have been discovered. Nanobiotechnology is a branch of pharmacology that can provide new approaches for drug delivery by the preparation of biocompatible carrier nanoparticles (NPs). In this article, we review recent studies with four important plant proteins that have been used as carriers for targeted delivery of drugs and genes. Zein is a water-insoluble protein from maize; Gliadin is a 70% alcohol-soluble protein from wheat and corn; legumin is a casein-like protein from leguminous seeds such as peas; lectins are glycoproteins naturally occurring in many plants that recognize specific carbohydrate residues. NPs formed from these proteins show good biocompatibility, possess the ability to enhance solubility, and provide sustained release of drugs and reduce their toxicity and side effects. The effects of preparation methods on the size and loading capacity of these NPs are also described in this review.

Identification of polycystic ovary syndrome potential drug targets based on pathobiological similarity in the protein-protein interaction network

OpenAIRE

Huang, Hao; He, Yuehan; Li, Wan; Wei, Wenqing; Li, Yiran; Xie, Ruiqiang; Guo, Shanshan; Wang, Yahui; Jiang, Jing; Chen, Binbin; Lv, Junjie; Zhang, Nana; Chen, Lina; He, Weiming

2016-01-01

Polycystic ovary syndrome (PCOS) is one of the most common endocrinological disorders in reproductive aged women. PCOS and Type 2 Diabetes (T2D) are closely linked in multiple levels and possess high pathobiological similarity. Here, we put forward a new computational approach based on the pathobiological similarity to identify PCOS potential drug target modules (PPDT-Modules) and PCOS potential drug targets in the protein-protein interaction network (PPIN). From the systems level and biologi...

Energetics investigation on encapsulation of protein/peptide drugs in carbon nanotubes.

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Chen, Qu; Wang, Qi; Liu, Ying-Chun; Wu, Tao; Kang, Yu; Moore, Joshua D; Gubbins, Keith E

2009-07-07

This work focuses on the dynamic properties and energetics of the protein/peptide drug during its transport through carbon nanotubes (CNTs). A systematic study was performed on the interaction between the peptide and the CNTs. In the molecular dynamics (MD) simulations, the protein/peptide molecule Zadaxin is observed to be encapsulated inside the nanotube after its spontaneous insertion and oscillates around the center of the tube, where the van der Waals interaction energy is observed to be a minimum. Furthermore, it is found by performing steered MD simulations that the pulling force applied to the peptide reaches a maximum value, which demonstrates the ability of the CNTs to trap protein/peptide drugs. Such effects, attributed to van der Waals interactions, can be influenced by varying the lengths and diameters of the CNTs. Longer nanotubes provide a broader area to trap the peptide, while smaller nanotubes are able to encapsulate the peptide with a deeper interaction energy well. This investigation provides insights into nanoscale pharmaceutical drug delivery devices.

CIKS, a connection to Ikappa B kinase and stress-activated protein kinase.

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Leonardi, A; Chariot, A; Claudio, E; Cunningham, K; Siebenlist, U

2000-09-12

Pathogens, inflammatory signals, and stress cause acute transcriptional responses in cells. The induced expression of genes in response to these signals invariably involves transcription factors of the NF-kappaB and AP-1/ATF families. Activation of NF-kappaB factors is thought to be mediated primarily via IkappaB kinases (IKK), whereas that of AP-1/ATF can be mediated by stress-activated protein kinases (SAPKs; also named Jun kinases or JNKs). IKKalpha and IKKbeta are two catalytic subunits of a core IKK complex that also contains the regulatory subunit NEMO (NF-kappaB essential modulator)/IKKgamma. The latter protein is essential for activation of the IKKs, but its mechanism of action is not known. Here we describe the molecular cloning of CIKS (connection to IKK and SAPK/JNK), a previously unknown protein that directly interacts with NEMO/IKKgamma in cells. When ectopically expressed, CIKS stimulates IKK and SAPK/JNK kinases and it transactivates an NF-kappaB-dependent reporter. Activation of NF-kappaB is prevented in the presence of kinase-deficient, interfering mutants of the IKKs. CIKS may help to connect upstream signaling events to IKK and SAPK/JNK modules. CIKS could coordinate the activation of two stress-induced signaling pathways, functions reminiscent of those noted for tumor necrosis factor receptor-associated factor adaptor proteins.

CIKS, a connection to IκB kinase and stress-activated protein kinase

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Leonardi, Antonio; Chariot, Alain; Claudio, Estefania; Cunningham, Kirk; Siebenlist, Ulrich

2000-01-01

Pathogens, inflammatory signals, and stress cause acute transcriptional responses in cells. The induced expression of genes in response to these signals invariably involves transcription factors of the NF-κB and AP-1/ATF families. Activation of NF-κB factors is thought to be mediated primarily via IκB kinases (IKK), whereas that of AP-1/ATF can be mediated by stress-activated protein kinases (SAPKs; also named Jun kinases or JNKs). IKKα and IKKβ are two catalytic subunits of a core IKK complex that also contains the regulatory subunit NEMO (NF-κB essential modulator)/IKKγ. The latter protein is essential for activation of the IKKs, but its mechanism of action is not known. Here we describe the molecular cloning of CIKS (connection to IKK and SAPK/JNK), a previously unknown protein that directly interacts with NEMO/IKKγ in cells. When ectopically expressed, CIKS stimulates IKK and SAPK/JNK kinases and it transactivates an NF-κB-dependent reporter. Activation of NF-κB is prevented in the presence of kinase-deficient, interfering mutants of the IKKs. CIKS may help to connect upstream signaling events to IKK and SAPK/JNK modules. CIKS could coordinate the activation of two stress-induced signaling pathways, functions reminiscent of those noted for tumor necrosis factor receptor-associated factor adaptor proteins. PMID:10962033

Single chain Fc-dimer-human growth hormone fusion protein for improved drug delivery.

Science.gov (United States)

Zhou, Li; Wang, Hsuan-Yao; Tong, Shanshan; Okamoto, Curtis T; Shen, Wei-Chiang; Zaro, Jennica L

2017-02-01

Fc fusion protein technology has been successfully used to generate long-acting forms of several protein therapeutics. In this study, a novel Fc-based drug carrier, single chain Fc-dimer (sc(Fc) 2 ), was designed to contain two Fc domains recombinantly linked via a flexible linker. Since the Fc dimeric structure is maintained through the flexible linker, the hinge region was omitted to further stabilize it against proteolysis and reduce FcγR-related effector functions. The resultant sc(Fc) 2 candidate preserved the neonatal Fc receptor (FcRn) binding. sc(Fc) 2 -mediated delivery was then evaluated using a therapeutic protein with a short plasma half-life, human growth hormone (hGH), as the protein drug cargo. This novel carrier protein showed a prolonged in vivo half-life and increased hGH-mediated bioactivity compared to the traditional Fc-based drug carrier. sc(Fc) 2 technology has the potential to greatly advance and expand the use of Fc-technology for improving the pharmacokinetics and bioactivity of protein therapeutics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America.

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Carroll, Carlos; McRae, Brad H; Brookes, Allen

2012-02-01

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost

Spectroscopic study of drug-binding characteristics of unmodified and pNPA-based acetylated human serum albumin: Does esterase activity affect microenvironment of drug binding sites on the protein?

Energy Technology Data Exchange (ETDEWEB)

Moradi, Nastaran [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Faculty of Pharmaceutical Sciences, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Ashrafi-Kooshk, Mohammad Reza [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Ghobadi, Sirous [Department of Biology, Faculty of Sciences, Razi University, Kermanshah (Iran, Islamic Republic of); Shahlaei, Mohsen [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Faculty of Pharmaceutical Sciences, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Khodarahmi, Reza, E-mail: rkhodarahmi@mbrc.ac.ir [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Faculty of Pharmaceutical Sciences, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of)

2015-04-15

Human serum albumin (HSA) is the most prominent extracellular protein in blood plasma. There are several binding sites on the protein which provide accommodation for structurally-unrelated endogenous and exogenous ligands and a wide variety of drugs. “Esterase-like” activity (hydrolysis of p-nitrophenyl esters) by the protein has been also reported. In the current study, we set out to investigate the interaction of indomethacin and ibuprofen with the unmodified and modified HSA (pNPA-modified HSA) using various spectroscopic techniques. Fluorescence data showed that 1:1 binding of drug to HSA is associated with quenching of the protein intrinsic fluorescence. Decrease of protein surface hydrophobicity (PSH), alteration in drug binding affinity and change of the protein stability, after esterase-like activity and permanent acetylation of HSA, were also documented. Analysis of the quenching and thermodynamic parameters indicated that forces involved in drug–HSA interactions change upon the protein modification. - Highlights: • Binding propensity of indomethacin extremely decreased upon the protein acetylation. • There is no ibuprofen binding after protein acetylation. • Protein stability changes upon drug binding as well as protein acetylation. • Drug pharmacokinetics may be influenced under co-administration of HSA-modifier drugs.

Spectroscopic study of drug-binding characteristics of unmodified and pNPA-based acetylated human serum albumin: Does esterase activity affect microenvironment of drug binding sites on the protein?

International Nuclear Information System (INIS)

Moradi, Nastaran; Ashrafi-Kooshk, Mohammad Reza; Ghobadi, Sirous; Shahlaei, Mohsen; Khodarahmi, Reza

2015-01-01

Human serum albumin (HSA) is the most prominent extracellular protein in blood plasma. There are several binding sites on the protein which provide accommodation for structurally-unrelated endogenous and exogenous ligands and a wide variety of drugs. “Esterase-like” activity (hydrolysis of p-nitrophenyl esters) by the protein has been also reported. In the current study, we set out to investigate the interaction of indomethacin and ibuprofen with the unmodified and modified HSA (pNPA-modified HSA) using various spectroscopic techniques. Fluorescence data showed that 1:1 binding of drug to HSA is associated with quenching of the protein intrinsic fluorescence. Decrease of protein surface hydrophobicity (PSH), alteration in drug binding affinity and change of the protein stability, after esterase-like activity and permanent acetylation of HSA, were also documented. Analysis of the quenching and thermodynamic parameters indicated that forces involved in drug–HSA interactions change upon the protein modification. - Highlights: • Binding propensity of indomethacin extremely decreased upon the protein acetylation. • There is no ibuprofen binding after protein acetylation. • Protein stability changes upon drug binding as well as protein acetylation. • Drug pharmacokinetics may be influenced under co-administration of HSA-modifier drugs

Numerical conformal mapping and its inverse of unbounded multiply connected regions onto logarithmic spiral slit regions and straight slit regions.

Science.gov (United States)

Yunus, A A M; Murid, A H M; Nasser, M M S

2014-02-08

This paper presents a boundary integral equation method with the adjoint generalized Neumann kernel for computing conformal mapping of unbounded multiply connected regions and its inverse onto several classes of canonical regions. For each canonical region, two integral equations are solved before one can approximate the boundary values of the mapping function. Cauchy's-type integrals are used for computing the mapping function and its inverse for interior points. This method also works for regions with piecewise smooth boundaries. Three examples are given to illustrate the effectiveness of the proposed method.

Polysaccharides-based polyelectrolyte nanoparticles as protein drugs delivery system

Energy Technology Data Exchange (ETDEWEB)

Shu Shujun; Sun Lei; Zhang Xinge, E-mail: zhangxinge@nankai.edu.cn [Nankai University, Key Laboratory of Functional Polymer Materials Ministry of Education, Institute of Polymer Chemistry (China); Wu Zhongming [Tianjin Medical University, Metabolic Diseases Hospital (China); Wang Zhen; Li Chaoxing, E-mail: lcx@nankai.edu.cn [Nankai University, Key Laboratory of Functional Polymer Materials Ministry of Education, Institute of Polymer Chemistry (China)

2011-09-15

Polysaccharides-based nanoparticles were prepared by synthesized quaternized chitosan and dextran sulfate through simple ionic-gelation self-assembled method. Introduction of quaternized groups was intended to increase water solubility of chitosan and make the nanoparticles have broader pH sensitive range which can remain more stable in physiological pH and decrease the loss of protein drugs caused by the gastric cavity. The load of BSA was affected by molecular parameter, i.e., degree of substitution, and average molecular weight of quaternized chitosan, as well as concentration of BSA. Fast release occurred in phosphate buffer solution (pH 7.4) while the release was slow in hydrochloric acid (pH 1.4). The drug release mechanism is Fickian diffusion through release kinetics analysis. Cell uptake demonstrated nanoparicles can internalize into Caco-2 cells, which suggested that nanoparticles had good biocompatibility. No significant conformation change was noted for the released BSA in comparison with native BSA using circular dichroism spectroscopy. This kind of novel composite nanoparticles may be a promising delivery system for oral protein and peptide drugs.

Hybrid Semantic Analysis for Mapping Adverse Drug Reaction Mentions in Tweets to Medical Terminology.

Science.gov (United States)

Emadzadeh, Ehsan; Sarker, Abeed; Nikfarjam, Azadeh; Gonzalez, Graciela

2017-01-01

Social networks, such as Twitter, have become important sources for active monitoring of user-reported adverse drug reactions (ADRs). Automatic extraction of ADR information can be crucial for healthcare providers, drug manufacturers, and consumers. However, because of the non-standard nature of social media language, automatically extracted ADR mentions need to be mapped to standard forms before they can be used by operational pharmacovigilance systems. We propose a modular natural language processing pipeline for mapping (normalizing) colloquial mentions of ADRs to their corresponding standardized identifiers. We seek to accomplish this task and enable customization of the pipeline so that distinct unlabeled free text resources can be incorporated to use the system for other normalization tasks. Our approach, which we call Hybrid Semantic Analysis (HSA), sequentially employs rule-based and semantic matching algorithms for mapping user-generated mentions to concept IDs in the Unified Medical Language System vocabulary. The semantic matching component of HSA is adaptive in nature and uses a regression model to combine various measures of semantic relatedness and resources to optimize normalization performance on the selected data source. On a publicly available corpus, our normalization method achieves 0.502 recall and 0.823 precision (F-measure: 0.624). Our proposed method outperforms a baseline based on latent semantic analysis and another that uses MetaMap.

Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders.

Science.gov (United States)

Hampson, M; Hoffman, R E

2010-01-01

There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS) provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders.

Directory of Open Access Journals (Sweden)

Michelle Hampson

2010-08-01

Full Text Available There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

Metabolic connectivity by interregional correlation analysis using statistical parametric mapping (SPM) and FDG brain PET; methodological development and patterns of metabolic connectivity in adults

International Nuclear Information System (INIS)

Lee, Dong Soo; Oh, Jungsu S.; Lee, Jae Sung; Lee, Myung Chul; Kang, Hyejin; Kim, Heejung; Park, Hyojin

2008-01-01

Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n=70) or as population-based cytoarchitectonic Brodmann areas (BA; n=28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain. (orig.)

Metabolic connectivity by interregional correlation analysis using statistical parametric mapping (SPM) and FDG brain PET; methodological development and patterns of metabolic connectivity in adults

Energy Technology Data Exchange (ETDEWEB)

Lee, Dong Soo; Oh, Jungsu S.; Lee, Jae Sung; Lee, Myung Chul [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Kang, Hyejin [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Seoul National University, Programs in Brain and Neuroscience, Seoul (Korea); Kim, Heejung; Park, Hyojin [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Seoul National University, Interdisciplinary Program in Cognitive Science, Seoul (Korea)

2008-09-15

Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n=70) or as population-based cytoarchitectonic Brodmann areas (BA; n=28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain. (orig.)

Detection and mapping of illicit drugs and their metabolites in fingermarks by MALDI MS and compatibility with forensic techniques

Science.gov (United States)

Groeneveld, G.; de Puit, M.; Bleay, S.; Bradshaw, R.; Francese, S.

2015-06-01

Despite the proven capabilities of Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS) in laboratory settings, research is still needed to integrate this technique into current forensic fingerprinting practice. Optimised protocols enabling the compatible application of MALDI to developed fingermarks will allow additional intelligence to be gathered around a suspect’s lifestyle and activities prior to the deposition of their fingermarks while committing a crime. The detection and mapping of illicit drugs and metabolites in latent fingermarks would provide intelligence that is beneficial for both police investigations and court cases. This study investigated MALDI MS detection and mapping capabilities for a large range of drugs of abuse and their metabolites in fingermarks; the detection and mapping of a mixture of these drugs in marks, with and without prior development with cyanoacrylate fuming or Vacuum Metal Deposition, was also examined. Our findings indicate the versatility of MALDI technology and its ability to retrieve chemical intelligence either by detecting the compounds investigated or by using their ion signals to reconstruct 2D maps of fingermark ridge details.

Alcohol and Other Drug Use: The Connection to Youth Suicide. Abstracts of Selected Research.

Science.gov (United States)

Laws, Kathy; Turner, Amy

This publication provides the reader with an overview of the research done on the connection between the use of alcohol and other drugs and the ideation and/or completion of suicide among adolescents. It also provides information and resources on how to develop a youth suicide prevention program. The introduction gives a brief overview of the…

Impact of germline and somatic missense variations on drug binding sites.

Science.gov (United States)

Yan, C; Pattabiraman, N; Goecks, J; Lam, P; Nayak, A; Pan, Y; Torcivia-Rodriguez, J; Voskanian, A; Wan, Q; Mazumder, R

2017-03-01

Advancements in next-generation sequencing (NGS) technologies are generating a vast amount of data. This exacerbates the current challenge of translating NGS data into actionable clinical interpretations. We have comprehensively combined germline and somatic nonsynonymous single-nucleotide variations (nsSNVs) that affect drug binding sites in order to investigate their prevalence. The integrated data thus generated in conjunction with exome or whole-genome sequencing can be used to identify patients who may not respond to a specific drug because of alterations in drug binding efficacy due to nsSNVs in the target protein's gene. To identify the nsSNVs that may affect drug binding, protein-drug complex structures were retrieved from Protein Data Bank (PDB) followed by identification of amino acids in the protein-drug binding sites using an occluded surface method. Then, the germline and somatic mutations were mapped to these amino acids to identify which of these alter protein-drug binding sites. Using this method we identified 12 993 amino acid-drug binding sites across 253 unique proteins bound to 235 unique drugs. The integration of amino acid-drug binding sites data with both germline and somatic nsSNVs data sets revealed 3133 nsSNVs affecting amino acid-drug binding sites. In addition, a comprehensive drug target discovery was conducted based on protein structure similarity and conservation of amino acid-drug binding sites. Using this method, 81 paralogs were identified that could serve as alternative drug targets. In addition, non-human mammalian proteins bound to drugs were used to identify 142 homologs in humans that can potentially bind to drugs. In the current protein-drug pairs that contain somatic mutations within their binding site, we identified 85 proteins with significant differential gene expression changes associated with specific cancer types. Information on protein-drug binding predicted drug target proteins and prevalence of both somatic and

The potential of protein-nanomaterial interaction for advanced drug delivery

DEFF Research Database (Denmark)

Peng, Qiang; Mu, Huiling

2016-01-01

Nanomaterials, like nanoparticles, micelles, nano-sheets, nanotubes and quantum dots, have great potentials in biomedical fields. However, their delivery is highly limited by the formation of protein corona upon interaction with endogenous proteins. This new identity, instead of nanomaterial itself...... of such interaction for advanced drug delivery are presented........ Therefore, protein-nanomaterial interaction is a great challenge for nanomaterial systems and should be inhibited. However, this interaction can also be used to functionalize nanomaterials by forming a selected protein corona. Unlike other decoration using exogenous molecules, nanomaterials functionalized...

Brain Mapping of drug addiction in witdrawal condition based P300 Signals

Science.gov (United States)

Turnip, Arjon; Esti Kusumandari, Dwi; Hidayat, Teddy

2018-04-01

Drug abuse for a long time will slowly cause changes in brain structure and performance. These changes tend to occur in the front of the brain which is directly interfere the concentration and the decision-making process. In this study an experiment involving 10 drug users was performed. The process of recording data with EEG system is conducted during craving condition and 1 hour after taking methadone. From brain mapping results obtained that brain activity tend to occur in the upper layer of the brain during craving conditions and tend to be in the midle layer of the brain after one hour of taking methadone.

From gene networks to drugs: systems pharmacology approaches for AUD.

Science.gov (United States)

Ferguson, Laura B; Harris, R Adron; Mayfield, Roy Dayne

2018-06-01

The alcohol research field has amassed an impressive number of gene expression datasets spanning key brain areas for addiction, species (humans as well as multiple animal models), and stages in the addiction cycle (binge/intoxication, withdrawal/negative effect, and preoccupation/anticipation). These data have improved our understanding of the molecular adaptations that eventually lead to dysregulation of brain function and the chronic, relapsing disorder of addiction. Identification of new medications to treat alcohol use disorder (AUD) will likely benefit from the integration of genetic, genomic, and behavioral information included in these important datasets. Systems pharmacology considers drug effects as the outcome of the complex network of interactions a drug has rather than a single drug-molecule interaction. Computational strategies based on this principle that integrate gene expression signatures of pharmaceuticals and disease states have shown promise for identifying treatments that ameliorate disease symptoms (called in silico gene mapping or connectivity mapping). In this review, we suggest that gene expression profiling for in silico mapping is critical to improve drug repurposing and discovery for AUD and other psychiatric illnesses. We highlight studies that successfully apply gene mapping computational approaches to identify or repurpose pharmaceutical treatments for psychiatric illnesses. Furthermore, we address important challenges that must be overcome to maximize the potential of these strategies to translate to the clinic and improve healthcare outcomes.

Data on overlapping brain disorders and emerging drug targets in human Dopamine Receptors Interaction Network

Directory of Open Access Journals (Sweden)

Avijit Podder

2017-06-01

Full Text Available Intercommunication of Dopamine Receptors (DRs with their associate protein partners is crucial to maintain regular brain function in human. Majority of the brain disorders arise due to malfunctioning of such communication process. Hence, contributions of genetic factors, as well as phenotypic indications for various neurological and psychiatric disorders are often attributed as sharing in nature. In our earlier research article entitled “Human Dopamine Receptors Interaction Network (DRIN: a systems biology perspective on topology, stability and functionality of the network” (Podder et al., 2014 [1], we had depicted a holistic interaction map of human Dopamine Receptors. Given emphasis on the topological parameters, we had characterized the functionality along with the vulnerable properties of the network. In support of this, we hereby provide an additional data highlighting the genetic overlapping of various brain disorders in the network. The data indicates the sharing nature of disease genes for various neurological and psychiatric disorders in dopamine receptors connecting protein-protein interactions network. The data also indicates toward an alternative approach to prioritize proteins for overlapping brain disorders as valuable drug targets in the network.

The human multidrug resistance-associated protein MRP is a plasma membrane drug-efflux pump

NARCIS (Netherlands)

Zaman, G. J.; Flens, M. J.; van Leusden, M. R.; de Haas, M.; Mülder, H. S.; Lankelma, J.; Pinedo, H. M.; Scheper, R. J.; Baas, F.; Broxterman, H. J.

1994-01-01

The multidrug-resistance associated protein MRP is a 180- to 195-kDa membrane protein associated with resistance of human tumor cells to cytotoxic drugs. We have investigated how MRP confers drug resistance in SW-1573 human lung carcinoma cells by generating a subline stably transfected with an

Identification of putative drug targets in Vancomycin-resistant Staphylococcus aureus (VRSA) using computer aided protein data analysis.

Science.gov (United States)

Hasan, Md Anayet; Khan, Md Arif; Sharmin, Tahmina; Hasan Mazumder, Md Habibul; Chowdhury, Afrin Sultana

2016-01-01

Vancomycin-resistant Staphylococcus aureus (VRSA) is a Gram-positive, facultative aerobic bacterium which is evolved from the extensive exposure of Vancomycin to Methicillin resistant S. aureus (MRSA) that had become the most common cause of hospital and community-acquired infections. Due to the emergence of different antibiotic resistance strains, there is an exigency to develop novel drug targets to address the provocation of multidrug-resistant bacteria. In this study, in-silico genome subtraction methodology was used to design potential and pathogen specific drug targets against VRSA. Our study divulged 1987 proteins from the proteome of 34,549 proteins, which have no homologues in human genome after sequential analysis through CD-HIT and BLASTp. The high stringency analysis of the remaining proteins against database of essential genes (DEG) resulted in 169 proteins which are essential for S. aureus. Metabolic pathway analysis of human host and pathogen by KAAS at the KEGG server sorted out 19 proteins involved in unique metabolic pathways. 26 human non-homologous membrane-bound essential proteins including 4 which were also involved in unique metabolic pathway were deduced through PSORTb, CELLO v.2.5, ngLOC. Functional classification of uncharacterized proteins through SVMprot derived 7 human non-homologous membrane-bound hypothetical essential proteins. Study of potential drug target against Drug Bank revealed pbpA-penicillin-binding protein 1 and hypothetical protein MQW_01796 as the best drug target candidate. 2D structure was predicted by PRED-TMBB, 3D structure and functional analysis was also performed. Protein-protein interaction network of potential drug target proteins was analyzed by using STRING. The identified drug targets are expected to have great potential for designing novel drugs against VRSA infections and further screening of the compounds against these new targets may result in the discovery of novel therapeutic compounds that can be

Structural analysis of protein-ligand interactions: the binding of endogenous compounds and of synthetic drugs.

Science.gov (United States)

Gallina, Anna M; Bork, Peer; Bordo, Domenico

2014-02-01

The large number of macromolecular structures deposited with the Protein Data Bank (PDB) describing complexes between proteins and either physiological compounds or synthetic drugs made it possible a systematic analysis of the interactions occurring between proteins and their ligands. In this work, the binding pockets of about 4000 PDB protein-ligand complexes were investigated and amino acid and interaction types were analyzed. The residues observed with lowest frequency in protein sequences, Trp, His, Met, Tyr, and Phe, turned out to be the most abundant in binding pockets. Significant differences between drug-like and physiological compounds were found. On average, physiological compounds establish with respect to drugs about twice as many hydrogen bonds with protein atoms, whereas drugs rely more on hydrophobic interactions to establish target selectivity. The large number of PDB structures describing homologous proteins in complex with the same ligand made it possible to analyze the conservation of binding pocket residues among homologous protein structures bound to the same ligand, showing that Gly, Glu, Arg, Asp, His, and Thr are more conserved than other amino acids. Also in the cases in which the same ligand is bound to unrelated proteins, the binding pockets showed significant conservation in the residue types. In this case, the probability of co-occurrence of the same amino acid type in the binding pockets could be up to thirteen times higher than that expected on a random basis. The trends identified in this study may provide an useful guideline in the process of drug design and lead optimization. Copyright © 2014 John Wiley & Sons, Ltd.

Specific degradation of the mucus adhesion-promoting protein (MapA) of Lactobacillus reuteri to an antimicrobial peptide.

Science.gov (United States)

Bøhle, Liv Anette; Brede, Dag Anders; Diep, Dzung B; Holo, Helge; Nes, Ingolf F

2010-11-01

The intestinal flora of mammals contains lactic acid bacteria (LAB) that may provide positive health effects for the host. Such bacteria are referred to as probiotic bacteria. From a pig, we have isolated a Lactobacillus reuteri strain that produces an antimicrobial peptide (AMP). The peptide was purified and characterized, and it was unequivocally shown that the AMP was a well-defined degradation product obtained from the mucus adhesion-promoting protein (MapA); it was therefore termed AP48-MapA. This finding demonstrates how large proteins might inherit unexpected pleiotropic functions by conferring antimicrobial capacities on the producer. The MapA/AP48-MapA system is the first example where a large protein of an intestinal LAB is shown to give rise to such an AMP. It is also of particular interest that the protein that provides this AMP is associated with the binding of the bacterium producing it to the surface/lining of the gut. This finding gives us new perspective on how some probiotic bacteria may successfully compete in this environment and thereby contribute to a healthy microbiota.

Finding undetected protein associations in cell signaling by belief propagation.

Science.gov (United States)

Bailly-Bechet, M; Borgs, C; Braunstein, A; Chayes, J; Dagkessamanskaia, A; François, J-M; Zecchina, R

2011-01-11

External information propagates in the cell mainly through signaling cascades and transcriptional activation, allowing it to react to a wide spectrum of environmental changes. High-throughput experiments identify numerous molecular components of such cascades that may, however, interact through unknown partners. Some of them may be detected using data coming from the integration of a protein-protein interaction network and mRNA expression profiles. This inference problem can be mapped onto the problem of finding appropriate optimal connected subgraphs of a network defined by these datasets. The optimization procedure turns out to be computationally intractable in general. Here we present a new distributed algorithm for this task, inspired from statistical physics, and apply this scheme to alpha factor and drug perturbations data in yeast. We identify the role of the COS8 protein, a member of a gene family of previously unknown function, and validate the results by genetic experiments. The algorithm we present is specially suited for very large datasets, can run in parallel, and can be adapted to other problems in systems biology. On renowned benchmarks it outperforms other algorithms in the field.

High-throughput mapping of brain-wide activity in awake and drug-responsive vertebrates.

Science.gov (United States)

Lin, Xudong; Wang, Shiqi; Yu, Xudong; Liu, Zhuguo; Wang, Fei; Li, Wai Tsun; Cheng, Shuk Han; Dai, Qiuyun; Shi, Peng

2015-02-07

The reconstruction of neural activity across complete neural circuits, or brain activity mapping, has great potential in both fundamental and translational neuroscience research. Larval zebrafish, a vertebrate model, has recently been demonstrated to be amenable to whole brain activity mapping in behaving animals. Here we demonstrate a microfluidic array system ("Fish-Trap") that enables high-throughput mapping of brain-wide activity in awake larval zebrafish. Unlike the commonly practiced larva-processing methods using a rigid gel or a capillary tube, which are laborious and time-consuming, the hydrodynamic design of our microfluidic chip allows automatic, gel-free, and anesthetic-free processing of tens of larvae for microscopic imaging with single-cell resolution. Notably, this system provides the capability to directly couple pharmaceutical stimuli with real-time recording of neural activity in a large number of animals, and the local and global effects of pharmacoactive drugs on the nervous system can be directly visualized and evaluated by analyzing drug-induced functional perturbation within or across different brain regions. Using this technology, we tested a set of neurotoxin peptides and obtained new insights into how to exploit neurotoxin derivatives as therapeutic agents. The novel and versatile "Fish-Trap" technology can be readily unitized to study other stimulus (optical, acoustic, or physical) associated functional brain circuits using similar experimental strategies.

All-optical functional synaptic connectivity mapping in acute brain slices using the calcium integrator CaMPARI.

Science.gov (United States)

Zolnik, Timothy A; Sha, Fern; Johenning, Friedrich W; Schreiter, Eric R; Looger, Loren L; Larkum, Matthew E; Sachdev, Robert N S

2017-03-01

The genetically encoded fluorescent calcium integrator calcium-modulated photoactivatable ratiobetric integrator (CaMPARI) reports calcium influx induced by synaptic and neural activity. Its fluorescence is converted from green to red in the presence of violet light and calcium. The rate of conversion - the sensitivity to activity - is tunable and depends on the intensity of violet light. Synaptic activity and action potentials can independently initiate significant CaMPARI conversion. The level of conversion by subthreshold synaptic inputs is correlated to the strength of input, enabling optical readout of relative synaptic strength. When combined with optogenetic activation of defined presynaptic neurons, CaMPARI provides an all-optical method to map synaptic connectivity. The calcium-modulated photoactivatable ratiometric integrator (CaMPARI) is a genetically encoded calcium integrator that facilitates the study of neural circuits by permanently marking cells active during user-specified temporal windows. Permanent marking enables measurement of signals from large swathes of tissue and easy correlation of activity with other structural or functional labels. One potential application of CaMPARI is labelling neurons postsynaptic to specific populations targeted for optogenetic stimulation, giving rise to all-optical functional connectivity mapping. Here, we characterized the response of CaMPARI to several common types of neuronal calcium signals in mouse acute cortical brain slices. Our experiments show that CaMPARI is effectively converted by both action potentials and subthreshold synaptic inputs, and that conversion level is correlated to synaptic strength. Importantly, we found that conversion rate can be tuned: it is linearly related to light intensity. At low photoconversion light levels CaMPARI offers a wide dynamic range due to slower conversion rate; at high light levels conversion is more rapid and more sensitive to activity. Finally, we employed Ca

Thiomers and thiomer-based nanoparticles in protein and DNA drug delivery.

Science.gov (United States)

Hauptstein, Sabine; Bernkop-Schnürch, Andreas

2012-09-01

Thanks to advances in biotechnology, more and more highly efficient protein- and DNA-based drugs have been developed. Unfortunately, these kinds of drugs underlie poor non-parental bioavailability. To overcome hindrances like low mucosal permeability and enzymatic degradation polymeric excipients are utilized as drug carrier whereat thiolated excipients showed several promising qualities in comparison to the analogical unmodified polymer. The article deals with the comparatively easy modification of well-established polymers like chitosan or poly(acrylates) to synthesize thiomers. Further, the recently developed "next generation" thiomers e.g. preactivated or S-protected thiomers are introduced. Designative properties like mucoadhesion, uptake and permeation enhancement, efflux pump inhibition and protection against enzymatic degradation will be discussed and differences between first and next generation thiomers will be pointed out. Additionally, nanoparticles prepared with thiomers will be dealt with regarding to protein and DNA drug delivery as thiomers seem to be a promising approach to avoid parenteral application. Properties of thiomers per se and results of in vivo studies carried out so far for peptide and DNA drugs demonstrate their potential as multifunctional excipients. However, further investigations and optimizations have to be done before establishing a carrier system ready for clinical approval.

Discovery and fine mapping of serum protein loci through transethnic meta-analysis.

Science.gov (United States)

Franceschini, Nora; van Rooij, Frank J A; Prins, Bram P; Feitosa, Mary F; Karakas, Mahir; Eckfeldt, John H; Folsom, Aaron R; Kopp, Jeffrey; Vaez, Ahmad; Andrews, Jeanette S; Baumert, Jens; Boraska, Vesna; Broer, Linda; Hayward, Caroline; Ngwa, Julius S; Okada, Yukinori; Polasek, Ozren; Westra, Harm-Jan; Wang, Ying A; Del Greco M, Fabiola; Glazer, Nicole L; Kapur, Karen; Kema, Ido P; Lopez, Lorna M; Schillert, Arne; Smith, Albert V; Winkler, Cheryl A; Zgaga, Lina; Bandinelli, Stefania; Bergmann, Sven; Boban, Mladen; Bochud, Murielle; Chen, Y D; Davies, Gail; Dehghan, Abbas; Ding, Jingzhong; Doering, Angela; Durda, J Peter; Ferrucci, Luigi; Franco, Oscar H; Franke, Lude; Gunjaca, Grog; Hofman, Albert; Hsu, Fang-Chi; Kolcic, Ivana; Kraja, Aldi; Kubo, Michiaki; Lackner, Karl J; Launer, Lenore; Loehr, Laura R; Li, Guo; Meisinger, Christa; Nakamura, Yusuke; Schwienbacher, Christine; Starr, John M; Takahashi, Atsushi; Torlak, Vesela; Uitterlinden, André G; Vitart, Veronique; Waldenberger, Melanie; Wild, Philipp S; Kirin, Mirna; Zeller, Tanja; Zemunik, Tatijana; Zhang, Qunyuan; Ziegler, Andreas; Blankenberg, Stefan; Boerwinkle, Eric; Borecki, Ingrid B; Campbell, Harry; Deary, Ian J; Frayling, Timothy M; Gieger, Christian; Harris, Tamara B; Hicks, Andrew A; Koenig, Wolfgang; O' Donnell, Christopher J; Fox, Caroline S; Pramstaller, Peter P; Psaty, Bruce M; Reiner, Alex P; Rotter, Jerome I; Rudan, Igor; Snieder, Harold; Tanaka, Toshihiro; van Duijn, Cornelia M; Vollenweider, Peter; Waeber, Gerard; Wilson, James F; Witteman, Jacqueline C M; Wolffenbuttel, Bruce H R; Wright, Alan F; Wu, Qingyu; Liu, Yongmei; Jenny, Nancy S; North, Kari E; Felix, Janine F; Alizadeh, Behrooz Z; Cupples, L Adrienne; Perry, John R B; Morris, Andrew P

2012-10-05

Many disorders are associated with altered serum protein concentrations, including malnutrition, cancer, and cardiovascular, kidney, and inflammatory diseases. Although these protein concentrations are highly heritable, relatively little is known about their underlying genetic determinants. Through transethnic meta-analysis of European-ancestry and Japanese genome-wide association studies, we identified six loci at genome-wide significance (p Japanese individuals) and three loci for total protein (TNFRS13B, 6q21.3, and ELL2, in up to 25,539 European-ancestry and 10,168 Japanese individuals). We observed little evidence of heterogeneity in allelic effects at these loci between groups of European and Japanese ancestry but obtained substantial improvements in the resolution of fine mapping of potential causal variants by leveraging transethnic differences in the distribution of linkage disequilibrium. We demonstrated a functional role for the most strongly associated serum albumin locus, HPN, for which Hpn knockout mice manifest low plasma albumin concentrations. Other loci associated with serum albumin harbor genes related to ribosome function, protein translation, and proteasomal degradation, whereas those associated with serum total protein include genes related to immune function. Our results highlight the advantages of transethnic meta-analysis for the discovery and fine mapping of complex trait loci and have provided initial insights into the underlying genetic architecture of serum protein concentrations and their association with human disease. Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: a proposed framework.

Science.gov (United States)

Glusman, Gustavo; Rose, Peter W; Prlić, Andreas; Dougherty, Jennifer; Duarte, José M; Hoffman, Andrew S; Barton, Geoffrey J; Bendixen, Emøke; Bergquist, Timothy; Bock, Christian; Brunk, Elizabeth; Buljan, Marija; Burley, Stephen K; Cai, Binghuang; Carter, Hannah; Gao, JianJiong; Godzik, Adam; Heuer, Michael; Hicks, Michael; Hrabe, Thomas; Karchin, Rachel; Leman, Julia Koehler; Lane, Lydie; Masica, David L; Mooney, Sean D; Moult, John; Omenn, Gilbert S; Pearl, Frances; Pejaver, Vikas; Reynolds, Sheila M; Rokem, Ariel; Schwede, Torsten; Song, Sicheng; Tilgner, Hagen; Valasatava, Yana; Zhang, Yang; Deutsch, Eric W

2017-12-18

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods.

Viral Organization of Human Proteins

Science.gov (United States)

Wuchty, Stefan; Siwo, Geoffrey; Ferdig, Michael T.

2010-01-01

Although maps of intracellular interactions are increasingly well characterized, little is known about large-scale maps of host-pathogen protein interactions. The investigation of host-pathogen interactions can reveal features of pathogenesis and provide a foundation for the development of drugs and disease prevention strategies. A compilation of experimentally verified interactions between HIV-1 and human proteins and a set of HIV-dependency factors (HDF) allowed insights into the topology and intricate interplay between viral and host proteins on a large scale. We found that targeted and HDF proteins appear predominantly in rich-clubs, groups of human proteins that are strongly intertwined among each other. These assemblies of proteins may serve as an infection gateway, allowing the virus to take control of the human host by reaching protein pathways and diversified cellular functions in a pronounced and focused way. Particular transcription factors and protein kinases facilitate indirect interactions between HDFs and viral proteins. Discerning the entanglement of directly targeted and indirectly interacting proteins may uncover molecular and functional sites that can provide novel perspectives on the progression of HIV infection and highlight new avenues to fight this virus. PMID:20827298

Activity-dependent modulation of neural circuit synaptic connectivity

Directory of Open Access Journals (Sweden)

Charles R Tessier

2009-07-01

Full Text Available In many nervous systems, the establishment of neural circuits is known to proceed via a two-stage process; 1 early, activity-independent wiring to produce a rough map characterized by excessive synaptic connections, and 2 subsequent, use-dependent pruning to eliminate inappropriate connections and reinforce maintained synapses. In invertebrates, however, evidence of the activity-dependent phase of synaptic refinement has been elusive, and the dogma has long been that invertebrate circuits are “hard-wired” in a purely activity-independent manner. This conclusion has been challenged recently through the use of new transgenic tools employed in the powerful Drosophila system, which have allowed unprecedented temporal control and single neuron imaging resolution. These recent studies reveal that activity-dependent mechanisms are indeed required to refine circuit maps in Drosophila during precise, restricted windows of late-phase development. Such mechanisms of circuit refinement may be key to understanding a number of human neurological diseases, including developmental disorders such as Fragile X syndrome (FXS and autism, which are hypothesized to result from defects in synaptic connectivity and activity-dependent circuit function. This review focuses on our current understanding of activity-dependent synaptic connectivity in Drosophila, primarily through analyzing the role of the fragile X mental retardation protein (FMRP in the Drosophila FXS disease model. The particular emphasis of this review is on the expanding array of new genetically-encoded tools that are allowing cellular events and molecular players to be dissected with ever greater precision and detail.

Vibrational energy flow through the green fluorescent protein-water interface: communication maps and thermal boundary conductance.

Science.gov (United States)

Xu, Yao; Leitner, David M

2014-07-17

We calculate communication maps for green fluorescent protein (GFP) to elucidate energy transfer pathways between the chromophore and other parts of the protein in the ground and excited state. The approach locates energy transport channels from the chromophore to remote regions of the protein via residues and water molecules that hydrogen bond to the chromophore. We calculate the thermal boundary conductance between GFP and water over a wide range of temperature and find that the interface between the protein and the cluster of water molecules in the β-barrel poses negligible resistance to thermal flow, consistent with facile vibrational energy transfer from the chromophore to the β-barrel waters observed in the communication maps.

A map of representations of Use / s User / s of illegal drugs from semiotics Statements

Directory of Open Access Journals (Sweden)

Fernando Palazzolo

2014-12-01

Full Text Available The aim of this paper is to describe, implement and evaluate the scope of the analytical method known as Statements Semiotics for the analysis of social representations, from interviews with actors involved in the phenomenon of illegal drugs. This time it made possible to establish a first conceptual map of how different actors (lawmakers, social activists, drug users and ex drug users, state workers on addictions, members of civil organizations define use and users of illegal drugs, being identified two discursive formations that are in tension. Also shows clearly some tensions within each discursive formation, as well as correlations between the two formations, and contradictions or opacities in the discourse of the actors

Antibodies directed to drug epitopes to investigate the structure of drug-protein photoadducts. Recognition of a common photobound substructure in tiaprofenic acid/ketoprofen cross-photoreactivity.

Science.gov (United States)

Lahoz, A; Hernández, D; Miranda, M A; Pérez-Prieto, J; Morera, I M; Castell, J V

2001-11-01

Drug-induced photoallergy is an immune adverse reaction to the combined effect of drugs and light. From the mechanistic point of view, it first involves covalent binding of drug to protein resulting in the formation of a photoantigen. Hence, determination of the structures of drug-protein photoadducts is of great relevance to understand the molecular basis of photoallergy and cross-immunoreactivity among drugs. Looking for new strategies to investigate the covalent photobinding of drugs to proteins, we generated highly specific antibodies to drug chemical substructures. The availability of such antibodies has allowed us to discriminate between the different modes by which tiaprofenic acid (TPA), suprofen (SUP), and ketoprofen (KTP) photobind to proteins. The finding that the vast majority of the TPA photoadduct can be accounted for by means of antibody anti-benzoyl strongly supports the view that the drug binds preferentially via the thiophene ring, leaving the benzene ring more accessible. By contrast, selective recognition of SUP-protein photoadducts by antibody anti-thenoyl evidences a preferential coupling via the benzene ring leaving the thiophene moiety more distant from the protein matrix. In the case of KTP, photoadducts are exclusively recognized by antibody anti-benzoyl, indicating that the benzene ring is again more accessible. As a result of this research, we have been able to identify a common substructure that is present in TPA-albumin and KTP-albumin photoadducts. This is remarkable since, at a first sight, the greatest structural similarities can be found between TPA and SUP as they share the same benzoylthiophene chromophore. These findings can explain the previously reported observations of cross-reactivity to KTP (or TPA) in patients photosensitized to TPA (or KTP).

A Physiologically Based Pharmacokinetic Model to Predict the Pharmacokinetics of Highly Protein-Bound Drugs and Impact of Errors in Plasma Protein Binding

Science.gov (United States)

Ye, Min; Nagar, Swati; Korzekwa, Ken

2015-01-01

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data was often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding, and blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for terminal elimination half-life (t1/2, 100% of drugs), peak plasma concentration (Cmax, 100%), area under the plasma concentration-time curve (AUC0–t, 95.4%), clearance (CLh, 95.4%), mean retention time (MRT, 95.4%), and steady state volume (Vss, 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. PMID:26531057

Effect of nonsteroidal antiinflammatory drugs on the C-reactive protein level in rheumatoid arthritis

DEFF Research Database (Denmark)

Tarp, Simon; Bartels, Else M.; Bliddal, Henning

2012-01-01

To evaluate the effects of oral nonsteroidal antiinflammatory drugs (NSAIDs) on C-reactive protein (CRP) levels in rheumatoid arthritis (RA) patients, with a prespecified focus on the different NSAIDs.......To evaluate the effects of oral nonsteroidal antiinflammatory drugs (NSAIDs) on C-reactive protein (CRP) levels in rheumatoid arthritis (RA) patients, with a prespecified focus on the different NSAIDs....

Polyionic hydrocolloids for the intestinal delivery of protein drugs: alginate and chitosan--a review.

Science.gov (United States)

George, Meera; Abraham, T Emilia

2006-08-10

The protein pharmaceutical market is rapidly growing, since it is gaining support from the recombinant DNA technology. To deliver these drugs via the oral route, the most preferred route, is the toughest challenge. In the design of oral delivery of peptide or protein drugs, pH sensitive hydrogels like alginate and chitosan have attracted increasing attention, since most of the synthetic polymers are immunogenic and the incorporation of proteins in to these polymers require harsh environment which may denature and inactivate the desired protein. Alginate is a water-soluble linear polysaccharide composed of alternating blocks of 1-4 linked alpha-L-guluronic and beta-D-mannuronic acid residues where as chitosan is a co polymer of D-glucosamine and N-acetyl glucosamine. The incorporation of protein into these two matrices can be done under relatively mild environment and hence the chances of protein denaturation are minimal. The limitations of these polymers, like drug leaching during preparation can be overcome by different techniques which increase their encapsulation efficiency. Alginate, being an anionic polymer with carboxyl end groups, is a good mucoadhesive agent. The pore size of alginate gel microbeads has been shown to be between 5 and 200 nm and coated beads and microspheres are found to be better oral delivery vehicles. Cross-linked alginate has more capacity to retain the entrapped drugs and mixing of alginate with other polymers such as neutral gums, pectin, chitosan, and eudragit have been found to solve the problem of drug leaching. Chitosan has only limited ability for controlling the release of encapsulated compound due to its hydrophilic nature and easy solubility in acidic medium. By simple covalent modifications of the polymer, its physicochemical properties can be changed and can be made suitable for the peroral drug delivery purpose. Ionic interactions between positively charged amino groups in chitosan and the negatively charged mucus gel layer

Combined chemical shift changes and amino acid specific chemical shift mapping of protein-protein interactions

Energy Technology Data Exchange (ETDEWEB)

Schumann, Frank H.; Riepl, Hubert [University of Regensburg, Institute of Biophysics and Physical Biochemistry (Germany); Maurer, Till [Boehringer Ingelheim Pharma GmbH and Co. KG, Analytical Sciences Department (Germany); Gronwald, Wolfram [University of Regensburg, Institute of Biophysics and Physical Biochemistry (Germany); Neidig, Klaus-Peter [Bruker BioSpin GmbH, Software Department (Germany); Kalbitzer, Hans Robert [University of Regensburg, Institute of Biophysics and Physical Biochemistry (Germany)], E-mail: hans-robert.kalbitzer@biologie.uni-regensburg.de

2007-12-15

Protein-protein interactions are often studied by chemical shift mapping using solution NMR spectroscopy. When heteronuclear data are available the interaction interface is usually predicted by combining the chemical shift changes of different nuclei to a single quantity, the combined chemical shift perturbation {delta}{delta}{sub comb}. In this paper different procedures (published and non-published) to calculate {delta}{delta}{sub comb} are examined that include a variety of different functional forms and weighting factors for each nucleus. The predictive power of all shift mapping methods depends on the magnitude of the overlap of the chemical shift distributions of interacting and non-interacting residues and the cut-off criterion used. In general, the quality of the prediction on the basis of chemical shift changes alone is rather unsatisfactory but the combination of chemical shift changes on the basis of the Hamming or the Euclidian distance can improve the result. The corrected standard deviation to zero of the combined chemical shift changes can provide a reasonable cut-off criterion. As we show combined chemical shifts can also be applied for a more reliable quantitative evaluation of titration data.

On the history of the connectivity index: from the connectivity index to the exact solution of the protein alignment problem.

Science.gov (United States)

Randić, M

2015-01-01

We briefly review the history of the connectivity index from 1975 to date. We hope to throw some light on why this unique, by its design, graph theoretical molecular descriptor continues to be of interest in QSAR, having wide use in applications in structure-property and structure-activity studies. We will elaborate on its generalizations and the insights it offered on applications in Multiple Regression Analysis (MRA). Going beyond the connectivity index we will outline several related developments in the development of molecular descriptors used in MRA, including molecular ID numbers (1986), the variable connectivity index (1991), orthogonal regression (1991), irrelevance of co-linearity of descriptors (1997), anti-connectivity (2006), and high discriminatory descriptors characterizing molecular similarity (2015). We will comment on beauty in QSAR and recent progress in searching for similarity of DNA, proteins and the proteome. This review reports on several results which are little known to the structure-property-activity community, the significance of which may surprise those unfamiliar with the application of discrete mathematics to chemistry. It tells the reader many unknown stories about the connectivity index, which may help the reader to better understand the meaning of this index. Readers are not required to be familiar with graph theory.

Identification of repaglinide as a therapeutic drug for glioblastoma multiforme

International Nuclear Information System (INIS)

Xiao, Zui Xuan; Chen, Ruo Qiao; Hu, Dian Xing; Xie, Xiao Qiang; Yu, Shang Bin; Chen, Xiao Qian

2017-01-01

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with a median survival time of only 14 months after treatment. It is urgent to find new therapeutic drugs that increase survival time of GBM patients. To achieve this goal, we screened differentially expressed genes between long-term and short-term survived GBM patients from Gene Expression Omnibus database and found gene expression signature for the long-term survived GBM patients. The signaling networks of all those differentially expressed genes converged to protein binding, extracellular matrix and tissue development as revealed in BiNGO and Cytoscape. Drug repositioning in Connectivity Map by using the gene expression signature identified repaglinide, a first-line drug for diabetes mellitus, as the most promising novel drug for GBM. In vitro experiments demonstrated that repaglinide significantly inhibited the proliferation and migration of human GBM cells. In vivo experiments demonstrated that repaglinide prominently prolonged the median survival time of mice bearing orthotopic glioma. Mechanistically, repaglinide significantly reduced Bcl-2, Beclin-1 and PD-L1 expression in glioma tissues, indicating that repaglinide may exert its anti-cancer effects via apoptotic, autophagic and immune checkpoint signaling. Taken together, repaglinide is likely to be an effective drug to prolong life span of GBM patients. - Highlights: • Gene expression signarue in long-term survived GBM patients are identified from Gene Expression Omnibus database. • Repaglinide is identified as a survival-related drug for GBM via drug repositioning in CMap. • Repaglinide effectively kills GBM cells, inhibits GBM cell migration and increases survival of mice bearing orthotopic glioma. • Repaglinide reduces Bcl-2, Beclin-1 and PD-L1 in GBM tissues.

Protein encapsulated magnetic carriers for micro/nanoscale drug delivery systems.

Energy Technology Data Exchange (ETDEWEB)

Xie, Y.; Kaminski, M. D.; Mertz, C. J.; Finck, M. R.; Guy, S. G.; Chen, H.; Rosengart, A. J.; Chemical Engineering; Univ. of Chicago, Pritzker School of Medicine

2005-01-01

Novel methods for drug delivery may be based on nanotechnology using non-invasive magnetic guidance of drug loaded magnetic carriers to the targeted site and thereafter released by external ultrasound energy. The key building block of this system is to successfully synthesize biodegradable, magnetic drug carriers. Magnetic carriers using poly(D,L-lactide-co-glycolide) (PLGA) or poly(lactic acid)-poly(ethylene glycol) (PLA-PEG) as matrix materials were loaded with bovine serum albumin (BSA) by a double-emulsion technique. BSA-loaded magnetic microspheres were characterized for size, morphology, surface charge, and magnetization. The BSA encapsulation efficiency was determined by recovering albumin from the microspheres using dimethyl sulfoxide and 0.05N NaOH/0.5% SDS then quantifying with the Micro-BCA protein assay. BSA release profiles were also determined by the Micro-BCA protein assay. The microspheres had drug encapsulation efficiencies up to 90% depending on synthesis parameters. Particles were spherical with a smooth or porous surface having a size range less than 5 {mu}m. The surface charge (expressed as zeta potential) was near neutral, optimal for prolonged intravascular survival. The magnetization of these BSA loaded magnetic carriers was 2 to 6 emu/g, depending on the specific magnetic materials used during synthesis.

The dopamine transporter protein gene (SLC6A3): Primary linage mapping and linkage studies in Tourette syndrome

Energy Technology Data Exchange (ETDEWEB)

Gelernter, J.; Kruger, S.D.; Pakstis, A.J. [Yale Univ., New Haven, CT (United States)]|[West Haven Veterans Affairs Medical Center, CT (United States)] [and others

1995-12-10

The dopamine transporter, the molecule responsible for presynaptic reuptake of dopamine and a major site of action of psychostimulant drugs, including cocaine, is encoded by locus SLC6A3 (alias DAT1). The protein`s actions and DAT`s specific localization to dopaminergic neurons make it a candidate gene for several psychiatric illnesses. SLC6A3 has been mapped to distal chromosome 5p, using physical methods. Genetic linkage methods were used to place SLC6A3 in the genetic linkage map. Four extended pedigrees (one of which overlaps with CEPH) were typed. Linkage with Tourette syndrome (TS) was also examined. SLC6A3 showed close linkage with several markers previously mapped to distal chromosome 5p, including D5S11 (Z{sub max} = 16.0, {theta}{sub M} = {theta}{sub F} = 0.03, results from four families) and D5S678 (Z{sub max} = 7.84, {theta}{sub M} = {theta}{sub F} = 0, results from two families). Observed crossovers established that SLC6A3 is a distal marker close to D5S10 and D5S678, but these three distal markers could not be ordered. Linkage between TS and SLC6A3 could be excluded independently in two branches of a large kindred segregating TS; the lod score in a third family was also negative, but not significant. Cumulative results show a lod score of -6.2 at {theta} = 0 and of -3.9 at {theta} = 0.05 (dominant model, narrow disease definition). SLC6A3 thus maps to distal chromosome 5p by linkage analysis, in agreement with previous physical mapping data. A mutation at SLC6A3 is not causative for TS in the two large families that generated significant negative lod scores (if the parameters of our analyses were correct) and is unlikely to be causative in the family that generated a negative lod score that did not reach significance. These results do not exclude a role for the dopamine transporter in influencing risk for TS in combination with other loci. 23 refs., 1 fig., 2 tabs.

PhosphOrtholog: a web-based tool for cross-species mapping of orthologous protein post-translational modifications.

Science.gov (United States)

Chaudhuri, Rima; Sadrieh, Arash; Hoffman, Nolan J; Parker, Benjamin L; Humphrey, Sean J; Stöckli, Jacqueline; Hill, Adam P; James, David E; Yang, Jean Yee Hwa

2015-08-19

Most biological processes are influenced by protein post-translational modifications (PTMs). Identifying novel PTM sites in different organisms, including humans and model organisms, has expedited our understanding of key signal transduction mechanisms. However, with increasing availability of deep, quantitative datasets in diverse species, there is a growing need for tools to facilitate cross-species comparison of PTM data. This is particularly important because functionally important modification sites are more likely to be evolutionarily conserved; yet cross-species comparison of PTMs is difficult since they often lie in structurally disordered protein domains. Current tools that address this can only map known PTMs between species based on known orthologous phosphosites, and do not enable the cross-species mapping of newly identified modification sites. Here, we addressed this by developing a web-based software tool, PhosphOrtholog ( www.phosphortholog.com ) that accurately maps protein modification sites between different species. This facilitates the comparison of datasets derived from multiple species, and should be a valuable tool for the proteomics community. Here we describe PhosphOrtholog, a web-based application for mapping known and novel orthologous PTM sites from experimental data obtained from different species. PhosphOrtholog is the only generic and automated tool that enables cross-species comparison of large-scale PTM datasets without relying on existing PTM databases. This is achieved through pairwise sequence alignment of orthologous protein residues. To demonstrate its utility we apply it to two sets of human and rat muscle phosphoproteomes generated following insulin and exercise stimulation, respectively, and one publicly available mouse phosphoproteome following cellular stress revealing high mapping and coverage efficiency. Although coverage statistics are dataset dependent, PhosphOrtholog increased the number of cross-species mapped sites

Effect of Antimalarial Drugs on Plasmodia Cell-Free Protein Synthesis

Directory of Open Access Journals (Sweden)

Ana Ferreras

2002-04-01

Full Text Available A cell-free system from Plasmodium falciparum able to translate endogenous mRNA was used to determine the effect of artemisinin, chloroquine and primaquine on the protein synthesis mechanism of the parasite. The antimalarial drugs did not inhibit the incorporation of [³H] methionine into parasite proteins even at concentrations higher than the ones found to strongly inhibit the parasite growth. Results clearly indicate that these compounds do not have a direct effect on protein synthesis activity of P. falciparum coded by endogenous mRNA.

Specific Degradation of the Mucus Adhesion-Promoting Protein (MapA) of Lactobacillus reuteri to an Antimicrobial Peptide ▿

Science.gov (United States)

Bøhle, Liv Anette; Brede, Dag Anders; Diep, Dzung B.; Holo, Helge; Nes, Ingolf F.

2010-01-01

The intestinal flora of mammals contains lactic acid bacteria (LAB) that may provide positive health effects for the host. Such bacteria are referred to as probiotic bacteria. From a pig, we have isolated a Lactobacillus reuteri strain that produces an antimicrobial peptide (AMP). The peptide was purified and characterized, and it was unequivocally shown that the AMP was a well-defined degradation product obtained from the mucus adhesion-promoting protein (MapA); it was therefore termed AP48-MapA. This finding demonstrates how large proteins might inherit unexpected pleiotropic functions by conferring antimicrobial capacities on the producer. The MapA/AP48-MapA system is the first example where a large protein of an intestinal LAB is shown to give rise to such an AMP. It is also of particular interest that the protein that provides this AMP is associated with the binding of the bacterium producing it to the surface/lining of the gut. This finding gives us new perspective on how some probiotic bacteria may successfully compete in this environment and thereby contribute to a healthy microbiota. PMID:20833791

Towards a map of the Populus biomass protein-protein interaction network

Energy Technology Data Exchange (ETDEWEB)

Beers, Eric [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Brunner, Amy [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Helm, Richard [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Dickerman, Allan [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

2015-07-31

-depth characterizations. Characterizations involved both in vivo and in vitro independent methods to confirm protein-protein interactions and the evaluation of novel phenotypes resulting from creation of transgenic poplar and Arabidopsis plants engineered for increased or decreased expression of the selected genes. Transgenic poplar trees were studied in growth chamber, greenhouse, and two separate replicated field trials involving over 25 distinct wood-associated proteins. In-depth characterizations yielding positive results include the following. First, a NAC domain transcription factor (NAC154) that is a promoter of stress response and dormancy in trees was discovered. Increasing expression of NAC154 caused stunted growth and premature senescence, while decreasing expression led to both delayed bud and leaf expansion in spring and delayed leaf drop (i.e., prolonged leaf retention) in fall. Second, we discovered and characterized a new connection between a negative regulator of wood formation, the NAC domain transcription factor XND1, and an important regulator of cell division and cell differentiation, RBR. Third, we identified a new network of interacting wood-associated transcription factors belonging to the MYB and HD families. One of the HD family proteins, WOX13, was used to prepare transgenic poplar for high-level expression, resulting in significantly increased lateral branch growth. Finally, we modeled and performed in vitro analyses of the insect protein rubber resilin and we prepared transgenic Arabidopsis plants for expression of resilin to test the feasibility of using resilin to modify lignin cross-linking in wood and reduce recalcitrance and improve yield of fermentable sugars for biofuels production. Analysis of these and additional transgenics created with this support is continuing.

Protein-lipid nanohybrids as emerging platforms for drug and gene delivery: Challenges and outcomes.

Science.gov (United States)

Gaber, Mohamed; Medhat, Waseem; Hany, Mark; Saher, Nourhan; Fang, Jia-You; Elzoghby, Ahmed

2017-05-28

Nanoparticulate drug delivery systems have been long used to deliver a vast range of drugs and bioactives owing to their ability to demonstrate novel physical, chemical, and/or biological properties. An exponential growth has spurred in research and development of these nanocarriers which led to the evolution of a great number of diverse nanosystems including liposomes, nanoemulsions, solid lipid nanoparticles (SLNs), micelles, dendrimers, polymeric nanoparticles (NPs), metallic NPs, and carbon nanotubes. Among them, lipid-based nanocarriers have made the largest progress whether commercially or under development. Despite this progress, these lipid-based nanocarriers suffer from several limitations that led to the development of many protein-coated lipid nanocarriers. To less extent, protein-based nanocarriers suffer from limitations that led to the fabrication of some lipid bilayer enveloping protein nanocarriers. This review discusses in-depth some limitations associated with the lipid-based or protein-based nanocarriers and the fruitful outcomes brought by protein-lipid hybridization. Also discussed are the various hybridization techniques utilized to formulate these protein-lipid nanohybrids and the mechanisms involved in the drug loading process. Copyright © 2017 Elsevier B.V. All rights reserved.

Oral Delivery of Protein Drugs Bioencapsulated in Plant Cells.

Science.gov (United States)

Kwon, Kwang-Chul; Daniell, Henry

2016-08-01

Plants cells are now approved by the FDA for cost-effective production of protein drugs (PDs) in large-scale current Good Manufacturing Practice (cGMP) hydroponic growth facilities. In lyophilized plant cells, PDs are stable at ambient temperature for several years, maintaining their folding and efficacy. Upon oral delivery, PDs bioencapsulated in plant cells are protected in the stomach from acids and enzymes but are subsequently released into the gut lumen by microbes that digest the plant cell wall. The large mucosal area of the human intestine offers an ideal system for oral drug delivery. When tags (receptor-binding proteins or cell-penetrating peptides) are fused to PDs, they efficiently cross the intestinal epithelium and are delivered to the circulatory or immune system. Unique tags to deliver PDs to human immune or nonimmune cells have been developed recently. After crossing the epithelium, ubiquitous proteases cleave off tags at engineered sites. PDs are also delivered to the brain or retina by crossing the blood-brain or retinal barriers. This review highlights recent advances in PD delivery to treat Alzheimer's disease, diabetes, hypertension, Gaucher's or ocular diseases, as well as the development of affordable drugs by eliminating prohibitively expensive purification, cold chain and sterile delivery.

Computational Prediction of Atomic Structures of Helical Membrane Proteins Aided by EM Maps

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Kovacs, Julio A.; Yeager, Mark; Abagyan, Ruben

2007-01-01

Integral membrane proteins pose a major challenge for protein-structure prediction because only ≈100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane α-helices. However, when an intermediate-resolution electron microscopy (EM) map is available, it can be used to provide restraints which, in combination with a suitable computational protocol, make structure prediction feasible. In this work we present such a protocol, which proceeds in three stages: 1), generation of an ensemble of α-helices by flexible fitting into each of the density rods in the low-resolution EM map, spanning a range of rotational angles around the main helical axes and translational shifts along the density rods; 2), fast optimization of side chains and scoring of the resulting conformations; and 3), refinement of the lowest-scoring conformations with internal coordinate mechanics, by optimizing the van der Waals, electrostatics, hydrogen bonding, torsional, and solvation energy contributions. In addition, our method implements a penalty term through a so-called tethering map, derived from the EM map, which restrains the positions of the α-helices. The protocol was validated on three test cases: GpA, KcsA, and MscL. PMID:17496035

[An AIDS-related cognitive map in a sample of drug abusers in Buenos Aires City].

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Kornblit, A L; Bilyk, A

1990-01-01

This paper is an approach to AIDS as a topic among a drug abusers sample of the city of Buenos Aires. Research was carried out on the basis of a qualitative methodology. In an attempt at surveying opinions and attitudes of such a sample as regards AIDS (i.e. subjects' cognitive map), 21 drug abusers from three different rehabilitation programs operating in the B.A. area were interviewed. On the basis of the research performed, the authors elaborate communication strategies among drug abusers that would be helpful for authorities engaged in AIDS prevention to adopt. To boost a strategy likely to break up the AIDS-drug association existing in the mind of many an abuser would be highly advisable so that a separation be settled between both representations, thus giving drug abusers a higher motivation for self-care practice.

Self Organizing Maps to efficiently cluster and functionally interpret protein conformational ensembles

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Fabio Stella

2013-09-01

Full Text Available An approach that combines Self-Organizing maps, hierarchical clustering and network components is presented, aimed at comparing protein conformational ensembles obtained from multiple Molecular Dynamic simulations. As a first result the original ensembles can be summarized by using only the representative conformations of the clusters obtained. In addition the network components analysis allows to discover and interpret the dynamic behavior of the conformations won by each neuron. The results showed the ability of this approach to efficiently derive a functional interpretation of the protein dynamics described by the original conformational ensemble, highlighting its potential as a support for protein engineering.

Convective transport of highly plasma protein bound drugs facilitates direct penetration into deep tissues after topical application

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Dancik, Yuri; Anissimov, Yuri G; Jepps, Owen G; Roberts, Michael S

2012-01-01

AIMS To relate the varying dermal, subcutaneous and muscle microdialysate concentrations found in man after topical application to the nature of the drug applied and to the underlying physiology. METHODS We developed a physiologically based pharmacokinetic model in which transport to deeper tissues was determined by tissue diffusion, blood, lymphatic and intersitial flow transport and drug properties. The model was applied to interpret published human microdialysis data, estimated in vitro dermal diffusion and protein binding affinity of drugs that have been previously applied topically in vivo and measured in deep cutaneous tissues over time. RESULTS Deeper tissue microdialysis concentrations for various drugs in vivo vary widely. Here, we show that carriage by the blood to the deeper tissues below topical application sites facilitates the transport of highly plasma protein bound drugs that penetrate the skin, leading to rapid and significant concentrations in those tissues. Hence, the fractional concentration for the highly plasma protein bound diclofenac in deeper tissues is 0.79 times that in a probe 4.5 mm below a superficial probe whereas the corresponding fractional concentration for the poorly protein bound nicotine is 0.02. Their corresponding estimated in vivo lag times for appearance of the drugs in the deeper probes were 1.1 min for diclofenac and 30 min for nicotine. CONCLUSIONS Poorly plasma protein bound drugs are mainly transported to deeper tissues after topical application by tissue diffusion whereas the transport of highly plasma protein bound drugs is additionally facilitated by convective blood, lymphatic and interstitial transport to deep tissues. PMID:21999217

Increased Global Functional Connectivity Correlates with LSD-Induced Ego Dissolution.

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Tagliazucchi, Enzo; Roseman, Leor; Kaelen, Mendel; Orban, Csaba; Muthukumaraswamy, Suresh D; Murphy, Kevin; Laufs, Helmut; Leech, Robert; McGonigle, John; Crossley, Nicolas; Bullmore, Edward; Williams, Tim; Bolstridge, Mark; Feilding, Amanda; Nutt, David J; Carhart-Harris, Robin

2016-04-25

Lysergic acid diethylamide (LSD) is a non-selective serotonin-receptor agonist that was first synthesized in 1938 and identified as (potently) psychoactive in 1943. Psychedelics have been used by indigenous cultures for millennia [1]; however, because of LSD's unique potency and the timing of its discovery (coinciding with a period of major discovery in psychopharmacology), it is generally regarded as the quintessential contemporary psychedelic [2]. LSD has profound modulatory effects on consciousness and was used extensively in psychological research and psychiatric practice in the 1950s and 1960s [3]. In spite of this, however, there have been no modern human imaging studies of its acute effects on the brain. Here we studied the effects of LSD on intrinsic functional connectivity within the human brain using fMRI. High-level association cortices (partially overlapping with the default-mode, salience, and frontoparietal attention networks) and the thalamus showed increased global connectivity under the drug. The cortical areas showing increased global connectivity overlapped significantly with a map of serotonin 2A (5-HT2A) receptor densities (the key site of action of psychedelic drugs [4]). LSD also increased global integration by inflating the level of communication between normally distinct brain networks. The increase in global connectivity observed under LSD correlated with subjective reports of "ego dissolution." The present results provide the first evidence that LSD selectively expands global connectivity in the brain, compromising the brain's modular and "rich-club" organization and, simultaneously, the perceptual boundaries between the self and the environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

A high-throughput shotgun mutagenesis approach to mapping B-cell antibody epitopes.

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Davidson, Edgar; Doranz, Benjamin J

2014-09-01

Characterizing the binding sites of monoclonal antibodies (mAbs) on protein targets, their 'epitopes', can aid in the discovery and development of new therapeutics, diagnostics and vaccines. However, the speed of epitope mapping techniques has not kept pace with the increasingly large numbers of mAbs being isolated. Obtaining detailed epitope maps for functionally relevant antibodies can be challenging, particularly for conformational epitopes on structurally complex proteins. To enable rapid epitope mapping, we developed a high-throughput strategy, shotgun mutagenesis, that enables the identification of both linear and conformational epitopes in a fraction of the time required by conventional approaches. Shotgun mutagenesis epitope mapping is based on large-scale mutagenesis and rapid cellular testing of natively folded proteins. Hundreds of mutant plasmids are individually cloned, arrayed in 384-well microplates, expressed within human cells, and tested for mAb reactivity. Residues are identified as a component of a mAb epitope if their mutation (e.g. to alanine) does not support candidate mAb binding but does support that of other conformational mAbs or allows full protein function. Shotgun mutagenesis is particularly suited for studying structurally complex proteins because targets are expressed in their native form directly within human cells. Shotgun mutagenesis has been used to delineate hundreds of epitopes on a variety of proteins, including G protein-coupled receptor and viral envelope proteins. The epitopes mapped on dengue virus prM/E represent one of the largest collections of epitope information for any viral protein, and results are being used to design better vaccines and drugs. © 2014 John Wiley & Sons Ltd.

Three-dimensional models of Mycobacterium tuberculosis proteins Rv1555, Rv1554 and their docking analyses with sildenafil, tadalafil, vardenafil drugs, suggest interference with quinol binding likely to affect protein's function.

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Dash, Pallabini; Bala Divya, M; Guruprasad, Lalitha; Guruprasad, Kunchur

2018-04-18

Earlier based on bioinformatics analyses, we had predicted the Mycobacterium tuberculosis (M.tb) proteins; Rv1555 and Rv1554, among the potential new tuberculosis drug targets. According to the 'TB-drugome' the Rv1555 protein is 'druggable' with sildenafil (Viagra), tadalafil (Cialis) and vardenafil (Levitra) drugs. In the present work, we intended to understand via computer modeling studies, how the above drugs are likely to inhibit the M.tb protein's function. The three-dimensional computer models for M.tb proteins; Rv1555 and Rv1554 constructed on the template of equivalent membrane anchor subunits of the homologous E.coli quinol fumarate reductase respiratory protein complex, followed by drug docking analyses, suggested that the binding of above drugs interferes with quinol binding sites. Also, we experimentally observed the in-vitro growth inhibition of E.coli bacteria containing the homologous M.tb protein sequences with sildenafil and tadalafil drugs. The predicted binding sites of the drugs is likely to affect the above M.tb proteins function as quinol binding is known to be essential for electron transfer function during anaerobic respiration in the homologous E.coli protein complex. Therefore, sildenafil and related drugs currently used in the treatment of male erectile dysfunction targeting the human phosphodiesterase 5 enzyme may be evaluated for their plausible role as repurposed drugs to treat human tuberculosis.

Large-scale prediction of drug–target interactions using protein sequences and drug topological structures

International Nuclear Information System (INIS)

Cao Dongsheng; Liu Shao; Xu Qingsong; Lu Hongmei; Huang Jianhua; Hu Qiannan; Liang Yizeng

2012-01-01

Highlights: ► Drug–target interactions are predicted using an extended SAR methodology. ► A drug–target interaction is regarded as an event triggered by many factors. ► Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. ► Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug–target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug–target interactions in a timely manner. In this article, we aim at extending current structure–activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug–target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug–target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug–target interactions, and show a general compatibility between the new scheme and current SAR

A protein interaction map of the kalimantacin biosynthesis assembly line

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Birgit Uytterhoeven

2016-11-01

Full Text Available The antimicrobial secondary metabolite kalimantacin is produced by a hybrid polyketide/ non-ribosomal peptide system in Pseudomonas fluorescens BCCM_ID9359. In this study, the kalimantacin biosynthesis gene cluster is analyzed by yeast two-hybrid analysis, creating a protein-protein interaction map of the entire assembly line. In total, 28 potential interactions were identified, of which 13 could be confirmed further. These interactions include the dimerization of ketosynthase domains, a link between assembly line modules 9 and 10, and a specific interaction between the trans-acting enoyl reductase BatK and the carrier proteins of modules 8 and 10. These interactions reveal fundamental insight into the biosynthesis of secondary metabolites.This study is the first to reveal interactions in a complete biosynthetic pathway. Similar future studies could build a strong basis for engineering strategies in such clusters.

Development of multigene expression signature maps at the protein level from digitized immunohistochemistry slides.

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Gregory J Metzger

Full Text Available Molecular classification of diseases based on multigene expression signatures is increasingly used for diagnosis, prognosis, and prediction of response to therapy. Immunohistochemistry (IHC is an optimal method for validating expression signatures obtained using high-throughput genomics techniques since IHC allows a pathologist to examine gene expression at the protein level within the context of histologically interpretable tissue sections. Additionally, validated IHC assays may be readily implemented as clinical tests since IHC is performed on routinely processed clinical tissue samples. However, methods have not been available for automated n-gene expression profiling at the protein level using IHC data. We have developed methods to compute expression level maps (signature maps of multiple genes from IHC data digitized on a commercial whole slide imaging system. Areas of cancer for these expression level maps are defined by a pathologist on adjacent, co-registered H&E slides, allowing assessment of IHC statistics and heterogeneity within the diseased tissue. This novel way of representing multiple IHC assays as signature maps will allow the development of n-gene expression profiling databases in three dimensions throughout virtual whole organ reconstructions.

Altered network communication following a neuroprotective drug treatment.

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Kathleen Vincent

Full Text Available Preconditioning is defined as a range of stimuli that allow cells to withstand subsequent anaerobic and other deleterious conditions. While cell protection under preconditioning is well established, this paper investigates the influence of neuroprotective preconditioning drugs, 4-aminopyridine and bicuculline (4-AP/bic, on synaptic communication across a broad network of in vitro rat cortical neurons. Using a permutation test, we evaluated cross-correlations of extracellular spiking activity across all pairs of recording electrodes on a 64-channel multielectrode array. The resulting functional connectivity maps were analyzed in terms of their graph-theoretic properties. A small-world effect was found, characterized by a functional network with high clustering coefficient and short average path length. Twenty-four hours after exposure to 4-AP/bic, small-world properties were comparable to control cultures that were not treated with the drug. Four hours following drug washout, however, the density of functional connections increased, while path length decreased and clustering coefficient increased. These alterations in functional connectivity were maintained at four days post-washout, suggesting that 4-AP/bic preconditioning leads to long-term effects on functional networks of cortical neurons. Because of their influence on communication efficiency in neuronal networks, alterations in small-world properties hold implications for information processing in brain systems. The observed relationship between density, path length, and clustering coefficient is captured by a phenomenological model where connections are added randomly within a spatially-embedded network. Taken together, results provide information regarding functional consequences of drug therapies that are overlooked in traditional viability studies and present the first investigation of functional networks under neuroprotective preconditioning.

Topological and functional analysis of nonalcoholic steatohepatitis through protein interaction mapping

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Asadzadeh-Aghdaee, Hamid; Mansouri, Vahid; Peyvandi, Ali Asghar; Moztarzadeh, Fathollah; Okhovatian, Farshad; Lahmi, Farhad; Vafaee, Reza; Zali, Mohammad Reza

2016-01-01

Aim: The corresponding proteins are important for network mapping since the interaction analysis can provide a new interpretation about disease underlying mechanisms as the aim of this study. Backgroud: Nonalcoholic steatohepatitis (NASH) is one of the main causes of liver disease in the world. It has been known with many susceptible proteins that play essential role in its pathogenesis. Methods: In this paper, protein-protein interaction (PPI) network analysis of fatty liver disease retrieved from STRING db by the application of Cytoscape Software. ClueGO analyzed the associated pathways for the selected top proteins. Results: INS, PPARA, LEP, SREBF1, and ALB are the introduced biomarker panel for fatty liver disease. Conclusion: It seems that pathways related to insulin have a prominent role in fatty liver disease. Therefore, investigation in this case is required to confirm the possible linkage of introduced panel and involvement of insulin pathway in the disease. PMID:28224024

Mapping of the mouse actin capping protein {alpha} subunit genes and pseudogenes

Energy Technology Data Exchange (ETDEWEB)

Hart, M.C.; Korshunova, Y.O.; Cooper, J.A. [Washington Univ. School of Medicine, St. Louis, MO (United States)

1997-02-01

Capping protein (CP), a heterodimer of {alpha} and {beta} subunits, is found in all eukaryotes. CP binds to the barbed ends of actin filaments in vitro and controls actin assembly and cell motility in vivo. Vertebrates have three {alpha} isoforms ({alpha}1, {alpha}2, {alpha}3) produced from different genes, whereas lower organisms have only one gene and one isoform. We isolated genomic clones corresponding to the a subunits of mouse CP and found three {alpha}1 genes, two of which are pseudogenes, and a single gene for both {alpha}2 and {alpha}3. Their chromosomal locations were identified by interspecies backcross mapping. The {alpha}1 gene (Cappa1) mapped to Chromosome 3 between D3Mit11 and D3Mit13. The {alpha}1 pseudogenes (Cappa1-ps1 and Cappa1-ps2) mapped to Chromosomes 1 and 9, respectively. The {alpha}2 gene (Cappa2) mapped to Chromosome 6 near Ptn. The {alpha}3 gene (Cappa3) also mapped to Chromosome 6, approximately 68 cM distal from Cappa2 near Kras2. One mouse mutation, de, maps in the vicinity of the {alpha}1 gene. No known mouse mutations map to regions near the {alpha}2 or {alpha}3 genes. 29 refs., 3 figs., 1 tab.

Bioinformatic analysis of xenobiotic reactive metabolite target proteins and their interacting partners

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Hanzlik Robert P

2009-06-01

Full Text Available Abstract Background Protein covalent binding by reactive metabolites of drugs, chemicals and natural products can lead to acute cytotoxicity. Recent rapid progress in reactive metabolite target protein identification has shown that adduction is surprisingly selective and inspired the hope that analysis of target proteins might reveal protein factors that differentiate target- vs. non-target proteins and illuminate mechanisms connecting covalent binding to cytotoxicity. Results Sorting 171 known reactive metabolite target proteins revealed a number of GO categories and KEGG pathways to be significantly enriched in targets, but in most cases the classes were too large, and the "percent coverage" too small, to allow meaningful conclusions about mechanisms of toxicity. However, a similar analysis of the directlyinteracting partners of 28 common targets of multiple reactive metabolites revealed highly significant enrichments in terms likely to be highly relevant to cytotoxicity (e.g., MAP kinase pathways, apoptosis, response to unfolded protein. Machine learning was used to rank the contribution of 211 computed protein features to determining protein susceptibility to adduction. Protein lysine (but not cysteine content and protein instability index (i.e., rate of turnover in vivo were among the features most important to determining susceptibility. Conclusion As yet there is no good explanation for why some low-abundance proteins become heavily adducted while some abundant proteins become only lightly adducted in vivo. Analyzing the directly interacting partners of target proteins appears to yield greater insight into mechanisms of toxicity than analyzing target proteins per se. The insights provided can readily be formulated as hypotheses to test in future experimental studies.

Overcoming T. gondii infection and intracellular protein nanocapsules as biomaterials for ultrasonically controlled drug release.

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Aw, M S; Paniwnyk, L

2017-09-26

One of the pivotal matters of concern in intracellular drug delivery is the preparation of biomaterials containing drugs that are compatible with the host target. Nanocapsules for oral delivery are found to be suitable candidates for targeting Toxoplasma gondii (T. gondii), a maneuvering and smart protozoic parasite found across Europe and America that causes a subtle but deadly infection. To overcome this disease, there is much potential of integrating protein-based cells into bioinspired nanocompartments such as via biodegradable cross-linked disulfide polyelectrolyte nanoparticles. The inner membrane vesicle system of these protein-drugs is not as simple as one might think. It is a complex transport network that includes sequential pathways, namely, endocytosis, exocytosis and autophagy. Unfortunately, the intracellular trafficking routes for nanoparticles in cells have not been extensively and intensively investigated. Hence, there lies the need to create robust protein nanocapsules for precise tracing and triggering of drug release to combat this protozoic disease. Protein nanocapsules have the advantage over other biomaterials due to their biocompatibility, use of natural ingredients, non-invasiveness, patient compliance, cost and time effectiveness. They also offer low maintenance, non-toxicity to healthy cells and a strictly defined route toward intracellular elimination through controlled drug delivery within the therapeutic window. This review covers the unprecedented opportunities that exist for constructing advanced nanocapsules to meet the growing needs arising from many therapeutic fields. Their versatile use includes therapeutic ultrasound for tumor imaging, recombinant DNA, ligand and functional group binding, the delivery of drugs and peptides via protein nanocapsules and polyelectrolytes, ultrasound-(US)-aided drug release through the gastrointestinal (GI) tract, and the recent progress in targeting tumor cells and a vast range of cancer therapies

Effects of gender, digit ratio, and menstrual cycle on intrinsic brain functional connectivity: A whole-brain, voxel-wise exploratory study using simultaneous local and global functional connectivity mapping.

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Donishi, Tomohiro; Terada, Masaki; Kaneoke, Yoshiki

2018-01-01

Gender and sex hormones influence brain function, but their effects on functional network organization within the brain are not yet understood. We investigated the influence of gender, prenatal sex hormones (estimated by the 2D:4D digit ratio), and the menstrual cycle on the intrinsic functional network organization of the brain (as measured by 3T resting-state functional MRI (rs-fMRI)) using right-handed, age-matched university students (100 males and 100 females). The mean (± SD ) age was 20.9 ± 1.5 (range: 18-24) years and 20.8 ± 1.3 (range: 18-24) years for males and females, respectively. Using two parameters derived from the normalized alpha centrality analysis (one for local and another for global connectivity strength), we created mean functional connectivity strength maps. There was a significant difference between the male mean map and female mean map in the distributions of network properties in almost all cortical regions and the basal ganglia but not in the medial parietal, limbic, and temporal regions and the thalamus. A comparison between the mean map for the low 2D:4D digit ratio group (indicative of high exposure to testosterone during the prenatal period) and that for the high 2D:4D digit ratio group revealed a significant difference in the network properties of the medial parietal region for males and in the temporal region for females. The menstrual cycle affected network organization in the brain, which varied with the 2D:4D digit ratio. Most of these findings were reproduced with our other datasets created with different preprocessing steps. The results suggest that differences in gender, prenatal sex hormone exposure, and the menstrual cycle are useful for understanding the normal brain and investigating the mechanisms underlying the variable prevalence and symptoms of neurological and psychiatric diseases.

Assessing the structural conservation of protein pockets to study functional and allosteric sites: implications for drug discovery

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Daura Xavier

2010-03-01

Full Text Available Abstract Background With the classical, active-site oriented drug-development approach reaching its limits, protein ligand-binding sites in general and allosteric sites in particular are increasingly attracting the interest of medicinal chemists in the search for new types of targets and strategies to drug development. Given that allostery represents one of the most common and powerful means to regulate protein function, the traditional drug discovery approach of targeting active sites can be extended by targeting allosteric or regulatory protein pockets that may allow the discovery of not only novel drug-like inhibitors, but activators as well. The wealth of available protein structural data can be exploited to further increase our understanding of allosterism, which in turn may have therapeutic applications. A first step in this direction is to identify and characterize putative effector sites that may be present in already available structural data. Results We performed a large-scale study of protein cavities as potential allosteric and functional sites, by integrating publicly available information on protein sequences, structures and active sites for more than a thousand protein families. By identifying common pockets across different structures of the same protein family we developed a method to measure the pocket's structural conservation. The method was first parameterized using known active sites. We characterized the predicted pockets in terms of sequence and structural conservation, backbone flexibility and electrostatic potential. Although these different measures do not tend to correlate, their combination is useful in selecting functional and regulatory sites, as a detailed analysis of a handful of protein families shows. We finally estimated the numbers of potential allosteric or regulatory pockets that may be present in the data set, finding that pockets with putative functional and effector characteristics are widespread across

Distribution of Animal Drugs among Curd, Whey, and Milk Protein Fractions in Spiked Skim Milk and Whey.

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Shappell, Nancy W; Shelver, Weilin L; Lupton, Sara J; Fanaselle, Wendy; Van Doren, Jane M; Hakk, Heldur

2017-02-01

It is important to understand the partitioning of drugs in processed milk and milk products, when drugs are present in raw milk, in order to estimate the potential consumer exposure. Radioisotopically labeled erythromycin, ivermectin, ketoprofen, oxytetracycline, penicillin G, sulfadimethoxine, and thiabendazole were used to evaluate the distribution of animal drugs among rennet curd, whey, and protein fractions from skim cow milk. Our previous work reported the distribution of these same drugs between skim and fat fractions of milk. Drug distribution between curd and whey was significantly correlated (R 2 = 0.70) to the drug's lipophilicity (log P), with improved correlation using log D (R 2 = 0.95). Distribution of drugs was concentration independent over the range tested (20-2000 nM). With the exception of thiabendazole and ivermectin, more drug was associated with whey protein than casein on a nmol/g protein basis (oxytetracycline experiment not performed). These results provide insights into the distribution of animal drug residues, if present in cow milk, among milk fractions, with possible extrapolation to milk products.

Recent advances in protein and Peptide drug delivery: a special emphasis on polymeric nanoparticles.

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Patel, Ashaben; Patel, Mitesh; Yang, Xiaoyan; Mitra, Ashim K

2014-01-01

Proteins and peptides are widely indicated in many diseased states. Parenteral route is the most commonly em- ployed method of administration for therapeutic proteins and peptides. However, requirement of frequent injections due to short in vivo half-life results in poor patient compliance. Non-invasive drug delivery routes such as nasal, transdermal, pulmonary, and oral offer several advantages over parenteral administration. Intrinsic physicochemical properties and low permeability across biological membrane limit protein delivery via non-invasive routes. One of the strategies to improve protein and peptide absorption is by delivering through nanostructured delivery carriers. Among nanocarriers, polymeric nanoparticles (NPs) have demonstrated significant advantages over other delivery systems. This article summarizes the application of polymeric NPs for protein and peptide drug delivery following oral, nasal, pulmonary, parenteral, transder mal, and ocular administrations.

Evidence connecting old, new and neglected glucose-lowering drugs to bile acid-induced GLP-1 secretion

DEFF Research Database (Denmark)

Kårhus, Martin L; Brønden, Andreas; Sonne, David P

2017-01-01

Bile acids are amphipathic water-soluble steroid-based molecules best known for their important lipid-solubilizing role in the assimilation of fat. Recently, bile acids have emerged as metabolic integrators with glucose-lowering potential. Among a variety of gluco-metabolic effects, bile acids have...... current evidence connecting established glucose-lowering drugs to bile acid-induced GLP-1 secretion and discusses whether bile acid-induced GLP-1 secretion may constitute a new basis for understanding how metformin, inhibitors of the apical sodium-dependent bile acids transporter, and bile acid...... sequestrants - old, new and neglected glucose-lowering drugs - improve glucose metabolism....

Promotion of the transdermal delivery of protein drugs by N-trimethyl chitosan nanoparticles combined with polypropylene electret.

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Tu, Ye; Wang, Xinxia; Lu, Ying; Zhang, He; Yu, Yuan; Chen, Yan; Liu, Junjie; Sun, Zhiguo; Cui, Lili; Gao, Jing; Zhong, Yanqiang

We recently reported that electret, which was prepared by a corona charging system with polypropylene film, could enhance the transdermal delivery of several drugs of low molecular weight. The aim of this study was to investigate whether electret could enhance the transdermal delivery of protein drugs by N -trimethyl chitosan nanoparticles (TMC NPs) prepared by an ionic gelation method. A series of experiments were performed, including in vitro skin permeation assays and anti-inflammatory effects, to evaluate the transdermal delivery of protein drugs by TMC NPs in the presence of electret. The results showed that in the presence of electret, the transdermal delivery of protein drugs in TMC NPs was significantly enhanced, as demonstrated by in vitro permeation studies and confocal laser scanning microscopy. Notably, superoxide dismutase-loaded TMC NPs combined with electret exhibited the best inhibitory effect on the edema of the mouse ear. TMC NPs combined with electret represent a novel platform for the transdermal delivery of protein drugs.

Overview on zein protein: a promising pharmaceutical excipient in drug delivery systems and tissue engineering.

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Labib, Gihan

2018-01-01

Natural pharmaceutical excipients have been applied extensively in the past decades owing to their safety and biocompatibility. Zein, a natural protein of plant origin offers great benefit over other synthetic polymers used in controlled drug and biomedical delivery systems. It was used in a variety of medical fields including pharmaceutical and biomedical drug targeting, vaccine, tissue engineering, and gene delivery. Being biodegradable and biocompatible, the current review focuses on the history and the medical application of zein as an attractive still promising biopolymer. Areas covered: The current review gives a broadscope on zein as a still promising protein excipient in different fields. Zein- based drug and biomedical delivery systems are discussed with special focus on current and potential application in controlled drug delivery systems, and tissue engineering. Expert opinion: Zein as a protein of natural origin can still be considered a promising polymer in the field of drug delivery systems as well as in tissue engineering. Although different researchers spotted light on zein application in different industrial fields extensively, the feasibility of its use in the field of drug delivery replenished by investigators in recent years has not yet been fully approached.

Protein Kinase Mitogen-activated Protein Kinase Kinase Kinase Kinase 4 (MAP4K4) Promotes Obesity-induced Hyperinsulinemia.

Science.gov (United States)

Roth Flach, Rachel J; Danai, Laura V; DiStefano, Marina T; Kelly, Mark; Menendez, Lorena Garcia; Jurczyk, Agata; Sharma, Rohit B; Jung, Dae Young; Kim, Jong Hun; Kim, Jason K; Bortell, Rita; Alonso, Laura C; Czech, Michael P

2016-07-29

Previous studies revealed a paradox whereby mitogen-activated protein kinase kinase kinase kinase 4 (Map4k4) acted as a negative regulator of insulin sensitivity in chronically obese mice, yet systemic deletion of Map4k4 did not improve glucose tolerance. Here, we report markedly reduced glucose-responsive plasma insulin and C-peptide levels in whole body Map4k4-depleted mice (M4K4 iKO) as well as an impaired first phase of insulin secretion from islets derived from M4K4 iKO mice ex vivo After long-term high fat diet (HFD), M4K4 iKO mice pancreata also displayed reduced β cell mass, fewer proliferating β cells and reduced islet-specific gene mRNA expression compared with controls, although insulin content was normal. Interestingly, the reduced plasma insulin in M4K4 iKO mice exposed to chronic (16 weeks) HFD was not observed in response to acute HFD challenge or short term treatment with the insulin receptor antagonist S961. Furthermore, the improved insulin sensitivity in obese M4K4 iKO mice was abrogated by high exogenous insulin over the course of a euglycemic clamp study, indicating that hypoinsulinemia promotes insulin sensitivity in chronically obese M4K4 iKO mice. These results demonstrate that protein kinase Map4k4 drives obesity-induced hyperinsulinemia and insulin resistance in part by promoting insulin secretion from β cells in mice. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Molecular mapping and genomics of soybean seed protein: a review and perspective for the future.

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Patil, Gunvant; Mian, Rouf; Vuong, Tri; Pantalone, Vince; Song, Qijian; Chen, Pengyin; Shannon, Grover J; Carter, Tommy C; Nguyen, Henry T

2017-10-01

Genetic improvement of soybean protein meal is a complex process because of negative correlation with oil, yield, and temperature. This review describes the progress in mapping and genomics, identifies knowledge gaps, and highlights the need of integrated approaches. Meal protein derived from soybean [Glycine max (L) Merr.] seed is the primary source of protein in poultry and livestock feed. Protein is a key factor that determines the nutritional and economical value of soybean. Genetic improvement of soybean seed protein content is highly desirable, and major quantitative trait loci (QTL) for soybean protein have been detected and repeatedly mapped on chromosomes (Chr.) 20 (LG-I), and 15 (LG-E). However, practical breeding progress is challenging because of seed protein content's negative genetic correlation with seed yield, other seed components such as oil and sucrose, and interaction with environmental effects such as temperature during seed development. In this review, we discuss rate-limiting factors related to soybean protein content and nutritional quality, and potential control factors regulating seed storage protein. In addition, we describe advances in next-generation sequencing technologies for precise detection of natural variants and their integration with conventional and high-throughput genotyping technologies. A syntenic analysis of QTL on Chr. 15 and 20 was performed. Finally, we discuss comprehensive approaches for integrating protein and amino acid QTL, genome-wide association studies, whole-genome resequencing, and transcriptome data to accelerate identification of genomic hot spots for allele introgression and soybean meal protein improvement.

A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

Science.gov (United States)

Ye, Min; Nagar, Swati; Korzekwa, Ken

2016-04-01

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Intrinsically disordered proteins aggregate at fungal cell-to-cell channels and regulate intercellular connectivity.

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Lai, Julian; Koh, Chuan Hock; Tjota, Monika; Pieuchot, Laurent; Raman, Vignesh; Chandrababu, Karthik Balakrishna; Yang, Daiwen; Wong, Limsoon; Jedd, Gregory

2012-09-25

Like animals and plants, multicellular fungi possess cell-to-cell channels (septal pores) that allow intercellular communication and transport. Here, using a combination of MS of Woronin body-associated proteins and a bioinformatics approach that identifies related proteins based on composition and character, we identify 17 septal pore-associated (SPA) proteins that localize to the septal pore in rings and pore-centered foci. SPA proteins are not homologous at the primary sequence level but share overall physical properties with intrinsically disordered proteins. Some SPA proteins form aggregates at the septal pore, and in vitro assembly assays suggest aggregation through a nonamyloidal mechanism involving mainly α-helical and disordered structures. SPA loss-of-function phenotypes include excessive septation, septal pore degeneration, and uncontrolled Woronin body activation. Together, our data identify the septal pore as a complex subcellular compartment and focal point for the assembly of unstructured proteins controlling diverse aspects of intercellular connectivity.

Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

Directory of Open Access Journals (Sweden)

Antonio M Rezende

Full Text Available The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks

The Role of ABC Proteins in Drug Resistant Breast Cancer Cells

Science.gov (United States)

2008-04-01

called the Plasmodium falciparum Chloroquine Transporter (PfCRT). While PfCRT is known to be the main molecular determinant of chloroquine resistance...proteins (such as human P-glycoprotein) and labeled PfCRT with a photoaffinity drug analogue . A manuscript is currently in preparation detailing my results...directly responsible for drug response, the Plasmodium falciparum Chloroquine Resistance Transporter (PfCRT) (Fidock et al 2000). While not a member of

Putting the party down on paper: A novel method for mapping youth drug use in private places

DEFF Research Database (Denmark)

Ravn, Signe; Duff, Cameron

2015-01-01

This article proposes a novel method for generating context-rich knowledge about ‘hard-to-access’ places. We ground our discussion in a recent qualitative study of social settings of youth drug use in Denmark. The study confirmed that private house parties are common sites of youth drug use...... observations ‘from a distance’ in hard-to-access places. Further, we argue that the map-task has a number of analytical and logistical advantages for scholars interested in the health and social aspects of ‘hidden’ phenomena, such as youth drug use....

Structural mapping of the coiled-coil domain of a bacterial condensin and comparative analyses across all domains of life suggest conserved features of SMC proteins.

Science.gov (United States)

Waldman, Vincent M; Stanage, Tyler H; Mims, Alexandra; Norden, Ian S; Oakley, Martha G

2015-06-01

The structural maintenance of chromosomes (SMC) proteins form the cores of multisubunit complexes that are required for the segregation and global organization of chromosomes in all domains of life. These proteins share a common domain structure in which N- and C- terminal regions pack against one another to form a globular ATPase domain. This "head" domain is connected to a central, globular, "hinge" or dimerization domain by a long, antiparallel coiled coil. To date, most efforts for structural characterization of SMC proteins have focused on the globular domains. Recently, however, we developed a method to map interstrand interactions in the 50-nm coiled-coil domain of MukB, the divergent SMC protein found in γ-proteobacteria. Here, we apply that technique to map the structure of the Bacillus subtilis SMC (BsSMC) coiled-coil domain. We find that, in contrast to the relatively complicated coiled-coil domain of MukB, the BsSMC domain is nearly continuous, with only two detectable coiled-coil interruptions. Near the middle of the domain is a break in coiled-coil structure in which there are three more residues on the C-terminal strand than on the N-terminal strand. Close to the head domain, there is a second break with a significantly longer insertion on the same strand. These results provide an experience base that allows an informed interpretation of the output of coiled-coil prediction algorithms for this family of proteins. A comparison of such predictions suggests that these coiled-coil deviations are highly conserved across SMC types in a wide variety of organisms, including humans. © 2015 Wiley Periodicals, Inc.

Protein Drug Targets of Lavandula angustifolia on treatment of Rat Alzheimer's Disease

Science.gov (United States)

Zali, Hakimeh; Zamanian-Azodi, Mona; Rezaei Tavirani, Mostafa; Akbar-zadeh Baghban, Alireza

2015-01-01

Different treatment strategies of Alzheimer's disease (AD) are being studied for treating or slowing the progression of AD. Many pharmaceutically important regulation systems operate through proteins as drug targets. Here, we investigate the drug target proteins in beta-amyloid (Aβ) injected rat hippocampus treated with Lavandula angustifolia (LA) by proteomics techniques. The reported study showed that lavender extract (LE) improves the spatial performance in AD animal model by diminishing Aβ production in histopathology of hippocampus, so in this study neuroprotective proteins expressed in Aβ injected rats treated with LE were scrutinized. Rats were divided into three groups including normal, Aβ injected, and Aβ injected that was treated with LE. Protein expression profiles of hippocampus tissue were determined by two-dimensional electrophoresis (2DE) method and dysregulated proteins such as Snca, NF-L, Hspa5, Prdx2, Apoa1, and Atp5a1were identified by MALDI-TOF/TOF. KEGG pathway and gene ontology (GO) categories were used by searching DAVID Bioinformatics Resources. All detected protein spots were used to determine predictedinteractions with other proteins in STRING online database. Different isoforms of important protein, Snca that exhibited neuroprotective effects by anti-apoptotic properties were expressed. NF-L involved in the maintenance of neuronal caliber. Hspa5 likewise Prdx2 displays as anti-apoptotic protein that Prdx2 also involved in the neurotrophic effects. Apoa1 has anti-inflammatory activity and Atp5a1, produces ATP from ADP. To sum up, these proteins as potential drug targets were expressed in hippocampus in response to effective components in LA may have therapeutic properties for the treatment of AD and other neurodegenerative diseases. PMID:25561935

Effects of protein-coated nanofibers on conformation of gingival fibroblast spheroids: potential utility for connective tissues regeneration.

Science.gov (United States)

Kaufman, Gili; Whitescarver, Ryan; Nunes, Laiz; Palmer, Xavier-Lewis; Skrtic, Drago; Tutak, Wojtek

2017-10-09

Deep wounds in the gingiva caused by trauma or surgery require a rapid and robust healing of connective tissues. We propose utilizing gas-brushed nanofibers coated with collagen and fibrin for that purpose. Our hypotheses are that protein-coated nanofibers will: (i) attract and mobilize cells in various spatial orientations, and (ii) regulate the expression levels of specific extracellular matrix (ECM)-associated proteins, determining the initial conformational nature of dense and soft connective tissues. Gingival fibroblast monolayers and 3D spheroids were cultured on ECM substrate and covered with gas-blown poly-(DL-lactide-co-glycolide) (PLGA) nanofibers (uncoated/coated with collagen and fibrin). Cell attraction and rearrangement was followed by F-actin staining and confocal microscopy. Thicknesses of the cell layers, developed within the nanofibers, were quantified by imageJ software. The expression of collagen1α1 chain (Col1α1), fibronectin, and metalloproteinase 2 (MMP2) encoding genes was determined by quantitative reverse transcription analysis. Collagen- and fibrin- coated nanofibers induced cell migration toward fibers and supported cellular growth within the scaffolds. Both proteins affected the spatial rearrangement of fibroblasts by favoring packed cell clusters or intermittent cell spreading. These cell arrangements resembled the structural characteristic of dense and soft connective tissues, respectively. Within 3 days of incubation, fibroblast spheroids interacted with the fibers and grew robustly by increasing their thickness compared to monolayers. While the ECM key components, such as fibronectin and MMP2 encoding genes, were expressed in both protein groups, Col1α1 was predominantly expressed in bundled fibroblasts grown on collagen fibers. This enhanced expression of collagen1 is typical for dense connective tissue. Based on results of this study, our gas-blown, collagen- and fibrin-coated PLGA nanofibers are viable candidates for

Effects of protein-coated nanofibers on conformation of gingival fibroblast spheroids: potential utility for connective tissue regeneration.

Science.gov (United States)

Kaufman, Gili; Whitescarver, Ryan A; Nunes, Laiz; Palmer, Xavier-Lewis; Skrtic, Drago; Tutak, Wojtek

2018-01-24

Deep wounds in the gingiva caused by trauma or surgery require a rapid and robust healing of connective tissues. We propose utilizing gas-brushed nanofibers coated with collagen and fibrin for that purpose. Our hypotheses are that protein-coated nanofibers will: (i) attract and mobilize cells in various spatial orientations, and (ii) regulate the expression levels of specific extracellular matrix (ECM)-associated proteins, determining the initial conformational nature of dense and soft connective tissues. Gingival fibroblast monolayers and 3D spheroids were cultured on ECM substrate and covered with gas-blown poly-(DL-lactide-co-glycolide) (PLGA) nanofibers (uncoated/coated with collagen and fibrin). Cell attraction and rearrangement was followed by F-actin staining and confocal microscopy. Thicknesses of the cell layers, developed within the nanofibers, were quantified by ImageJ software. The expression of collagen1α1 chain (Col1α1), fibronectin, and metalloproteinase 2 (MMP2) encoding genes was determined by quantitative reverse transcription analysis. Collagen- and fibrin- coated nanofibers induced cell migration toward fibers and supported cellular growth within the scaffolds. Both proteins affected the spatial rearrangement of fibroblasts by favoring packed cell clusters or intermittent cell spreading. These cell arrangements resembled the structural characteristic of dense and soft connective tissues, respectively. Within three days of incubation, fibroblast spheroids interacted with the fibers, and grew robustly by increasing their thickness compared to monolayers. While the ECM key components, such as fibronectin and MMP2 encoding genes, were expressed in both protein groups, Col1α1 was predominantly expressed in bundled fibroblasts grown on collagen fibers. This enhanced expression of collagen1 is typical for dense connective tissue. Based on results of this study, our gas-blown, collagen- and fibrin-coated PLGA nanofibers are viable candidates for

Mechanisms of photosensitization by drugs: Involvement of tyrosines in the photomodification of proteins mediated by tiaprofenic acid in vitro.

Science.gov (United States)

Miranda, M A; Castell, J V; Sarabia, Z; Hernández, D; Puertes, I; Morera, I M; Gómez-Lechón, M J

1997-10-01

The photosensitizing potential of drugs must be related to their photoreactivity towards the target biomolecules. In this context, a representative photosensitizing drug (tiaprofenic acid) was co-irradiated with a model protein, bovine serum albumin (BSA). This led to a significant degree of protein crosslinking and to the formation of trace amounts of drug-BSA photoadducts. Amino acid analysis of the hydrolysed (HC1) protein showed that His and Tyr undergo a dramatic decrease (approx. 90%) as a consequence of drug-mediated photodynamic processes. When the drug was irradiated in the presence of the pure amino acids, extensive phototransformation of the latter was observed. Other photosensitizing drugs gave rise to similar processes when irradiated in the presence of BSA or the isolated amino acids. In conclusion, histidine and tyrosine appear to be key sites for the photosensitized damage to proteins. Photodegradation of the isolated amino acids in vitro may be an indicator of the photosensitizing potential of drugs.

Denatured protein-coated docetaxel nanoparticles: Alterable drug state and cytosolic delivery.

Science.gov (United States)

Zhang, Li; Xiao, Qingqing; Wang, Yiran; Zhang, Chenshuang; He, Wei; Yin, Lifang

2017-05-15

Many lead compounds have a low solubility in water, which substantially hinders their clinical application. Nanosuspensions have been considered a promising strategy for the delivery of water-insoluble drugs. Here, denatured soy protein isolate (SPI)-coated docetaxel nanosuspensions (DTX-NS) were developed using an anti-solvent precipitation-ultrasonication method to improve the water-solubility of DTX, thus improving its intracellular delivery. DTX-NS, with a diameter of 150-250nm and drug-loading up to 18.18%, were successfully prepared by coating drug particles with SPI. Interestingly, the drug state of DTX-NS was alterable. Amorphous drug nanoparticles were obtained at low drug-loading, whereas at a high drug-loading, the DTX-NS drug was mainly present in the crystalline state. Moreover, DTX-NS could be internalized at high levels by cancer cells and enter the cytosol by lysosomal escape, enhancing cell cytotoxicity and apoptosis compared with free DTX. Taken together, denatured SPI has a strong stabilization effect on nanosuspensions, and the drug state in SPI-coated nanosuspensions is alterable by changing the drug-loading. Moreover, DTX-NS could achieve cytosolic delivery, generating enhanced cell cytotoxicity against cancer cells. Copyright © 2017 Elsevier B.V. All rights reserved.

Hepatitis C virus infection protein network.

Science.gov (United States)

de Chassey, B; Navratil, V; Tafforeau, L; Hiet, M S; Aublin-Gex, A; Agaugué, S; Meiffren, G; Pradezynski, F; Faria, B F; Chantier, T; Le Breton, M; Pellet, J; Davoust, N; Mangeot, P E; Chaboud, A; Penin, F; Jacob, Y; Vidalain, P O; Vidal, M; André, P; Rabourdin-Combe, C; Lotteau, V

2008-01-01

A proteome-wide mapping of interactions between hepatitis C virus (HCV) and human proteins was performed to provide a comprehensive view of the cellular infection. A total of 314 protein-protein interactions between HCV and human proteins was identified by yeast two-hybrid and 170 by literature mining. Integration of this data set into a reconstructed human interactome showed that cellular proteins interacting with HCV are enriched in highly central and interconnected proteins. A global analysis on the basis of functional annotation highlighted the enrichment of cellular pathways targeted by HCV. A network of proteins associated with frequent clinical disorders of chronically infected patients was constructed by connecting the insulin, Jak/STAT and TGFbeta pathways with cellular proteins targeted by HCV. CORE protein appeared as a major perturbator of this network. Focal adhesion was identified as a new function affected by HCV, mainly by NS3 and NS5A proteins.

Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry.

Science.gov (United States)

Blundell, Tom L

2017-07-01

The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein-protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called 'linear model', where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world.

Quantitative autoradiographic mapping of herpes simplex virus encephalitis with a radiolabeled antiviral drug

International Nuclear Information System (INIS)

Saito, Y.; Price, R.W.; Rottenberg, D.A.; Fox, J.J.; Su, T.L.; Watanabe, K.A.; Philips, F.S.

1982-01-01

2'-Fluoro-5-methyl-1-ν-D-arabinosyluracil (FMAU) labeled with carbon-14 was used to image herpes simplex virus type 1-infected regions of rat brain by quantitative autoradiography. FMAU is a potent antiviral pyrimidine nucleoside which is selectively phosphorylated by virus-coded thymidine kinase. When the labeled FMAU was administered 6 hours before the rats were killed, the selective uptake and concentration of the drug and its metabolites by infected cells (defined by immunoperoxidase staining of viral antigens) allowed quantitative definition and mapping of HSV-1-infected structures in autoradiograms of brain sections. These results shown that quantitative autoradiography can be used to characterize the local metabolism of antiviral drugs by infected cells in vivo. They also suggest that the selective uptake of drugs that exploit viral thymidine kinase for their antiviral effect can, by appropriate labeling, be used in conjunction with clinical neuroimaging techniques to define infected regions of human brain, thereby providing a new approach to the diagnosis of herpes encephalitis in man

Patients with first-episode, drug-naive schizophrenia and subjects at ultra-high risk of psychosis shared increased cerebellar-default mode network connectivity at rest.

Science.gov (United States)

Wang, Houliang; Guo, Wenbin; Liu, Feng; Wang, Guodong; Lyu, Hailong; Wu, Renrong; Chen, Jindong; Wang, Shuai; Li, Lehua; Zhao, Jingping

2016-05-18

Increased cerebellar-default mode network (DMN) connectivity has been observed in first-episode, drug-naive patients with schizophrenia. However, it remains unclear whether increased cerebellar-DMN connectivity starts earlier than disease onset. Thirty-four ultra-high risk (UHR) subjects, 31 first-episode, drug-naive patients with schizophrenia and 37 healthy controls were enrolled for a resting-state scan. The imaging data were analyzed using the seed-based functional connectivity (FC) method. Compared with the controls, UHR subjects and patients with schizophrenia shared increased connectivity between the right Crus I and bilateral posterior cingulate cortex/precuneus and between Lobule IX and the left superior medial prefrontal cortex. There are positive correlations between the right Crus I-bilateral precuneus connectivity and clinical variables (Structured Interview for Prodromal Syndromes/Positive and Negative Symptom Scale negative symptoms/total scores) in the UHR subjects. Increased cerebellar-DMN connectivity shared by the UHR subjects and the patients not only highlights the importance of the DMN in the pathophysiology of psychosis but also may be a trait alteration for psychosis.

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

Science.gov (United States)

Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

Drug-target residence time--a case for G protein-coupled receptors.

Science.gov (United States)

Guo, Dong; Hillger, Julia M; IJzerman, Adriaan P; Heitman, Laura H

2014-07-01

A vast number of marketed drugs act on G protein-coupled receptors (GPCRs), the most successful category of drug targets to date. These drugs usually possess high target affinity and selectivity, and such combined features have been the driving force in the early phases of drug discovery. However, attrition has also been high. Many investigational new drugs eventually fail in clinical trials due to a demonstrated lack of efficacy. A retrospective assessment of successfully launched drugs revealed that their beneficial effects in patients may be attributed to their long drug-target residence times (RTs). Likewise, for some other GPCR drugs short RT could be beneficial to reduce the potential for on-target side effects. Hence, the compounds' kinetics behavior might in fact be the guiding principle to obtain a desired and durable effect in vivo. We therefore propose that drug-target RT should be taken into account as an additional parameter in the lead selection and optimization process. This should ultimately lead to an increased number of candidate drugs moving to the preclinical development phase and on to the market. This review contains examples of the kinetics behavior of GPCR ligands with improved in vivo efficacy and summarizes methods for assessing drug-target RT. © 2014 Wiley Periodicals, Inc.

TIMP-1 increases expression and phosphorylation of proteins associated with drug resistance in breast cancer cells

DEFF Research Database (Denmark)

Hekmat, Omid; Munk, Stephanie; Fogh, Louise

2013-01-01

may explain the resistance phenotype to topoisomerase inhibitors that was observed in cells with high TIMP-1 levels. Pathway analysis showed an enrichment of proteins from functional categories such as apoptosis, cell cycle, DNA repair, transcription factors, drug targets and proteins associated......Tissue inhibitor of metalloproteinase 1 (TIMP-1) is a protein with a potential biological role in drug resistance. To elucidate the unknown molecular mechanisms underlying the association between high TIMP-1 levels and increased chemotherapy resistance, we employed SILAC-based quantitative mass...... spectrometry to analyze global proteome and phosphoproteome differences of MCF-7 breast cancer cells expressing high or low levels of TIMP-1. In TIMP-1 high expressing cells, 312 proteins and 452 phosphorylation sites were up-regulated. Among these were the cancer drug targets topoisomerase 1, 2A and 2B, which...

The potential of protein-nanomaterial interaction for advanced drug delivery.

Science.gov (United States)

Peng, Qiang; Mu, Huiling

2016-03-10

Nanomaterials, like nanoparticles, micelles, nano-sheets, nanotubes and quantum dots, have great potentials in biomedical fields. However, their delivery is highly limited by the formation of protein corona upon interaction with endogenous proteins. This new identity, instead of nanomaterial itself, would be the real substance the organs and cells firstly encounter. Consequently, the behavior of nanomaterials in vivo is uncontrollable and some undesired effects may occur, like rapid clearance from blood stream; risk of capillary blockage; loss of targeting capacity; and potential toxicity. Therefore, protein-nanomaterial interaction is a great challenge for nanomaterial systems and should be inhibited. However, this interaction can also be used to functionalize nanomaterials by forming a selected protein corona. Unlike other decoration using exogenous molecules, nanomaterials functionalized by selected protein corona using endogenous proteins would have greater promise for clinical use. In this review, we aim to provide a comprehensive understanding of protein-nanomaterial interaction. Importantly, a discussion about how to use such interaction is launched and some possible applications of such interaction for advanced drug delivery are presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Proteins with complex architecture as potential targets for drug design: a case study of Mycobacterium tuberculosis.

Directory of Open Access Journals (Sweden)

Bálint Mészáros

2011-07-01

Full Text Available Lengthy co-evolution of Homo sapiens and Mycobacterium tuberculosis, the main causative agent of tuberculosis, resulted in a dramatically successful pathogen species that presents considerable challenge for modern medicine. The continuous and ever increasing appearance of multi-drug resistant mycobacteria necessitates the identification of novel drug targets and drugs with new mechanisms of action. However, further insights are needed to establish automated protocols for target selection based on the available complete genome sequences. In the present study, we perform complete proteome level comparisons between M. tuberculosis, mycobacteria, other prokaryotes and available eukaryotes based on protein domains, local sequence similarities and protein disorder. We show that the enrichment of certain domains in the genome can indicate an important function specific to M. tuberculosis. We identified two families, termed pkn and PE/PPE that stand out in this respect. The common property of these two protein families is a complex domain organization that combines species-specific regions, commonly occurring domains and disordered segments. Besides highlighting promising novel drug target candidates in M. tuberculosis, the presented analysis can also be viewed as a general protocol to identify proteins involved in species-specific functions in a given organism. We conclude that target selection protocols should be extended to include proteins with complex domain architectures instead of focusing on sequentially unique and essential proteins only.

G-protein-coupled receptors: new approaches to maximise the impact of GPCRS in drug discovery.

Science.gov (United States)

Davey, John

2004-04-01

IBC's Drug Discovery Technology Series is a group of conferences highlighting technological advances and applications in niche areas of the drug discovery pipeline. This 2-day meeting focused on G-protein-coupled receptors (GPCRs), probably the most important and certainly the most valuable class of targets for drug discovery. The meeting was chaired by J Beesley (Vice President, European Business Development for LifeSpan Biosciences, Seattle, USA) and included 17 presentations on various aspects of GPCR activity, drug screens and therapeutic analyses. Keynote Addresses covered two of the emerging areas in GPCR regulation; receptor dimerisation (G Milligan, Professor of Molecular Pharmacology and Biochemistry, University of Glasgow, UK) and proteins that interact with GPCRs (J Bockaert, Laboratory of Functional Genomics, CNRS Montpellier, France). A third Keynote Address from W Thomsen (Director of GPCR Drug Screening, Arena Pharmaceuticals, USA) discussed Arena's general approach to drug discovery and illustrated this with reference to the development of an agonist with potential efficacy in Type II diabetes.

Conformational transition paths harbor structures useful for aiding drug discovery and understanding enzymatic mechanisms in protein kinases.

Science.gov (United States)

Wong, Chung F

2016-01-01

This short article examines the usefulness of fast simulations of conformational transition paths in elucidating enzymatic mechanisms and guiding drug discovery for protein kinases. It applies the transition path method in the MOIL software package to simulate the paths of conformational transitions between six pairs of structures from the Protein Data Bank. The structures along the transition paths were found to resemble experimental structures that mimic transient structures believed to form during enzymatic catalysis or conformational transitions, or structures that have drug candidates bound. These findings suggest that such simulations could provide quick initial insights into the enzymatic mechanisms or pathways of conformational transitions of proteins kinases, or could provide structures useful for aiding structure-based drug design. © 2015 The Protein Society.

Mechanism of the pharmacokinetic interaction between methotrexate and benzimidazoles: potential role for breast cancer resistance protein in clinical drug-drug interactions

NARCIS (Netherlands)

Breedveld, Pauline; Zelcer, Noam; Pluim, Dick; Sönmezer, Ozgür; Tibben, Matthijs M.; Beijnen, Jos H.; Schinkel, Alfred H.; van Tellingen, Olaf; Borst, Piet; Schellens, Jan H. M.

2004-01-01

The antifolate drug methotrexate (MTX) is transported by breast cancer resistance protein (BCRP; ABCG2) and multidrug resistance-associated protein1-4 (MRP1-4; ABCC1-4). In cancer patients, coadministration of benzimidazoles and MTX can result in profound MTX-induced toxicity coinciding with an

Going Deeper or Flatter: Connecting Deep Mapping, Flat Ontologies and the Democratizing of Knowledge

Directory of Open Access Journals (Sweden)

Selina Springett

2015-10-01

Full Text Available The concept of “deep mapping”, as an approach to place, has been deployed as both a descriptor of a specific suite of creative works and as a set of aesthetic practices. While its definition has been amorphous and adaptive, a number of distinct, yet related, manifestations identify as, or have been identified by, the term. In recent times, it has garnered attention beyond literary discourse, particularly within the “spatial” turn of representation in the humanities and as a result of expanded platforms of data presentation. This paper takes a brief look at the practice of “deep mapping”, considering it as a consciously performative act and tracing a number of its various manifestations. It explores how deep mapping is a reflection of epistemological trends in ontological practices of connectivity and the “flattening” of knowledge systems. In particular those put forward by post structural and cultural theorists, such as Bruno Latour, Gilles Deleuze, and Felix Guattari, as well as by theorists who associate with speculative realism. The concept of deep mapping as an aesthetic, methodological, and ideological tool, enables an approach to place that democratizes knowledge by crossing temporal, spatial, and disciplinary boundaries.

Neuroimaging markers of glutamatergic and GABAergic systems in drug addiction: Relationships to resting-state functional connectivity.

Science.gov (United States)

Moeller, Scott J; London, Edythe D; Northoff, Georg

2016-02-01

Drug addiction is characterized by widespread abnormalities in brain function and neurochemistry, including drug-associated effects on concentrations of the excitatory and inhibitory neurotransmitters glutamate and gamma-aminobutyric acid (GABA), respectively. In healthy individuals, these neurotransmitters drive the resting state, a default condition of brain function also disrupted in addiction. Here, our primary goal was to review in vivo magnetic resonance spectroscopy and positron emission tomography studies that examined markers of glutamate and GABA abnormalities in human drug addiction. Addicted individuals tended to show decreases in these markers compared with healthy controls, but findings also varied by individual characteristics (e.g., abstinence length). Interestingly, select corticolimbic brain regions showing glutamatergic and/or GABAergic abnormalities have been similarly implicated in resting-state functional connectivity deficits in drug addiction. Thus, our secondary goals were to provide a brief review of this resting-state literature, and an initial rationale for the hypothesis that abnormalities in glutamatergic and/or GABAergic neurotransmission may underlie resting-state functional deficits in drug addiction. In doing so, we suggest future research directions and possible treatment implications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Protein Interaction Analysis Provides a Map of the Spatial and Temporal Organization of the Ciliary Gating Zone.

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Takao, Daisuke; Wang, Liang; Boss, Allison; Verhey, Kristen J

2017-08-07

The motility and signaling functions of the primary cilium require a unique protein and lipid composition that is determined by gating mechanisms localized at the base of the cilium. Several protein complexes localize to the gating zone and may regulate ciliary protein composition; however, the mechanisms of ciliary gating and the dynamics of the gating components are largely unknown. Here, we used the BiFC (bimolecular fluorescence complementation) assay and report for the first time on the protein-protein interactions that occur between ciliary gating components and transiting cargoes during ciliary entry. We find that the nucleoporin Nup62 and the C termini of the nephronophthisis (NPHP) proteins NPHP4 and NPHP5 interact with the axoneme-associated kinesin-2 motor KIF17 and thus spatially map to the inner region of the ciliary gating zone. Nup62 and NPHP4 exhibit rapid turnover at the transition zone and thus define dynamic components of the gate. We find that B9D1, AHI1, and the N termini of NPHP4 and NPHP5 interact with the transmembrane protein SSTR3 and thus spatially map to the outer region of the ciliary gating zone. B9D1, AHI1, and NPHP5 exhibit little to no turnover at the transition zone and thus define components of a stable gating structure. These data provide the first comprehensive map of the molecular orientations of gating zone components along the inner-to-outer axis of the ciliary gating zone. These results advance our understanding of the functional roles of gating zone components in regulating ciliary protein composition. Copyright © 2017 Elsevier Ltd. All rights reserved.

How to calculate clearance of highly protein-bound drugs during continuous venovenous hemofiltration demonstrated with flucloxacillin.

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Meyer, Brigitte; Ahmed el Gendy, Salwa; Delle Karth, Georg; Locker, Gottfried J; Heinz, Gottfried; Jaeger, Walter; Thalhammer, Florian

2003-01-01

Flucloxacillin is an important antimicrobial drug in the treatment of infections with Staphylococcus aureus and therefore is often used in staphylococcal infections. Furthermore, flucloxacillin has a high protein binding rate as for example ceftriaxone or teicoplanin--drugs which have formerly been characterized as not being dialyzable. The pharmacokinetic parameters of 4.0 g flucloxacillin every 8 h were examined in 10 intensive care patients during continuous venovenous hemofiltration (CVVH) using a polyamide capillary hemofilter. In addition, the difficulty of calculating the hemofiltration clearance of a highly protein-bound drug is described. Flucloxacillin serum levels were significantly lowered (56.9 +/- 24.0%) even though only 15% of the drug was detected in the ultrafiltrate. Elimination half-life, total body clearance and sieving coefficient were 4.9 +/- 0.7 h, 117.2 +/- 79.1 ml/min and 0.21 +/- 0.09, respectively. These discrepancies can be explained by the high protein binding of flucloxacillin, the adsorbing property of polyamide and the equation in order to calculate hemofiltration clearance. The unbound fraction of a 4.0 g flucloxacillin dosage facilitates time above the minimum inhibitory concentration (T > MIC) of 60% only for strains up to a minimum inhibitory concentration (MIC) of 0.5 mg/l. Based on the data of this study, we conclude that intensive care patients with staphylococcal infections on CVVH should be treated with 4.0 g flucloxacillin every 8 h which was safe and well tolerated. Moreover, further studies with highly protein-bound drugs are recommended to check the classical 'hemodialysis' equation as the standard equation in calculating the CVVH clearance of highly protein-bound drugs. Copyright 2003 S. Karger AG, Basel

Putative drug and vaccine target protein identification using comparative genomic analysis of KEGG annotated metabolic pathways of Mycoplasma hyopneumoniae.

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Damte, Dereje; Suh, Joo-Won; Lee, Seung-Jin; Yohannes, Sileshi Belew; Hossain, Md Akil; Park, Seung-Chun

2013-07-01

In the present study, a computational comparative and subtractive genomic/proteomic analysis aimed at the identification of putative therapeutic target and vaccine candidate proteins from Kyoto Encyclopedia of Genes and Genomes (KEGG) annotated metabolic pathways of Mycoplasma hyopneumoniae was performed for drug design and vaccine production pipelines against M.hyopneumoniae. The employed comparative genomic and metabolic pathway analysis with a predefined computational systemic workflow extracted a total of 41 annotated metabolic pathways from KEGG among which five were unique to M. hyopneumoniae. A total of 234 proteins were identified to be involved in these metabolic pathways. Although 125 non homologous and predicted essential proteins were found from the total that could serve as potential drug targets and vaccine candidates, additional prioritizing parameters characterize 21 proteins as vaccine candidate while druggability of each of the identified proteins evaluated by the DrugBank database prioritized 42 proteins suitable for drug targets. Copyright © 2013 Elsevier Inc. All rights reserved.

DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites.

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Gowthaman, Ragul; Miller, Sven A; Rogers, Steven; Khowsathit, Jittasak; Lan, Lan; Bai, Nan; Johnson, David K; Liu, Chunjing; Xu, Liang; Anbanandam, Asokan; Aubé, Jeffrey; Roy, Anuradha; Karanicolas, John

2016-05-12

Protein-protein interactions represent an exciting and challenging target class for therapeutic intervention using small molecules. Protein interaction sites are often devoid of the deep surface pockets presented by "traditional" drug targets, and crystal structures reveal that inhibitors typically engage these sites using very shallow binding modes. As a consequence, modern virtual screening tools developed to identify inhibitors of traditional drug targets do not perform as well when they are instead deployed at protein interaction sites. To address the need for novel inhibitors of important protein interactions, here we introduce an alternate docking strategy specifically designed for this regime. Our method, termed DARC (Docking Approach using Ray-Casting), matches the topography of a surface pocket "observed" from within the protein to the topography "observed" when viewing a potential ligand from the same vantage point. We applied DARC to carry out a virtual screen against the protein interaction site of human antiapoptotic protein Mcl-1 and found that four of the top-scoring 21 compounds showed clear inhibition in a biochemical assay. The Ki values for these compounds ranged from 1.2 to 21 μM, and each had ligand efficiency comparable to promising small-molecule inhibitors of other protein-protein interactions. These hit compounds do not resemble the natural (protein) binding partner of Mcl-1, nor do they resemble any known inhibitors of Mcl-1. Our results thus demonstrate the utility of DARC for identifying novel inhibitors of protein-protein interactions.

Relationship between hot spot residues and ligand binding hot spots in protein-protein interfaces.

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Zerbe, Brandon S; Hall, David R; Vajda, Sandor; Whitty, Adrian; Kozakov, Dima

2012-08-27

In the context of protein-protein interactions, the term "hot spot" refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research, a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment-sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening.

Protein redox chemistry: post-translational cysteine modifications that regulate signal transduction and drug pharmacology

Directory of Open Access Journals (Sweden)

Revati eWani

2014-10-01

Full Text Available The perception of reactive oxygen species (ROS has evolved over the past decade from agents of cellular damage to secondary messengers which modify signaling proteins in physiology and the disease state (e.g. cancer. New protein targets of specific oxidation are rapidly being identified. One emerging class of redox modification occurs to the thiol side chain of cysteine residues which can produce multiple chemically-distinct alterations to the protein (e.g. sulfenic/sulfinic/sulfonic acid, disulfides. These post-translational modifications (PTM are shown to affect the protein structure and function. Because redox-sensitive proteins can traffic between subcellular compartments that have different redox environments, cysteine oxidation enables a spatio-temporal control to signaling. Understanding ramifications of these oxidative modifications to the functions of signaling proteins is crucial for understanding cellular regulation as well as for informed-drug discovery process. The effects of EGFR oxidation of Cys797 on inhibitor pharmacology are presented to illustrate the principle. Taken together, cysteine redox PTM can impact both cell biology and drug pharmacology.

LS-SNP/PDB: annotated non-synonymous SNPs mapped to Protein Data Bank structures.

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Ryan, Michael; Diekhans, Mark; Lien, Stephanie; Liu, Yun; Karchin, Rachel

2009-06-01

LS-SNP/PDB is a new WWW resource for genome-wide annotation of human non-synonymous (amino acid changing) SNPs. It serves high-quality protein graphics rendered with UCSF Chimera molecular visualization software. The system is kept up-to-date by an automated, high-throughput build pipeline that systematically maps human nsSNPs onto Protein Data Bank structures and annotates several biologically relevant features. LS-SNP/PDB is available at (http://ls-snp.icm.jhu.edu/ls-snp-pdb) and via links from protein data bank (PDB) biology and chemistry tabs, UCSC Genome Browser Gene Details and SNP Details pages and PharmGKB Gene Variants Downloads/Cross-References pages.

Protein Recognition in Drug-Induced DNA Alkylation: When the Moonlight Protein GAPDH Meets S23906-1/DNA Minor Groove Adducts.

Science.gov (United States)

Savreux-Lenglet, Gaëlle; Depauw, Sabine; David-Cordonnier, Marie-Hélène

2015-11-05

DNA alkylating drugs have been used in clinics for more than seventy years. The diversity of their mechanism of action (major/minor groove; mono-/bis-alkylation; intra-/inter-strand crosslinks; DNA stabilization/destabilization, etc.) has undoubtedly major consequences on the cellular response to treatment. The aim of this review is to highlight the variety of established protein recognition of DNA adducts to then particularly focus on glyceraldehyde-3-phosphate dehydrogenase (GAPDH) function in DNA adduct interaction with illustration using original experiments performed with S23906-1/DNA adduct. The introduction of this review is a state of the art of protein/DNA adducts recognition, depending on the major or minor groove orientation of the DNA bonding as well as on the molecular consequences in terms of double-stranded DNA maintenance. It reviews the implication of proteins from both DNA repair, transcription, replication and chromatin maintenance in selective DNA adduct recognition. The main section of the manuscript is focusing on the implication of the moonlighting protein GAPDH in DNA adduct recognition with the model of the peculiar DNA minor groove alkylating and destabilizing drug S23906-1. The mechanism of action of S23906-1 alkylating drug and the large variety of GAPDH cellular functions are presented prior to focus on GAPDH direct binding to S23906-1 adducts.

The master two-dimensional gel database of human AMA cell proteins: towards linking protein and genome sequence and mapping information (update 1991)

DEFF Research Database (Denmark)

Celis, J E; Leffers, H; Rasmussen, H H

1991-01-01

autoantigens" and "cDNAs". For convenience we have included an alphabetical list of all known proteins recorded in this database. In the long run, the main goal of this database is to link protein and DNA sequencing and mapping information (Human Genome Program) and to provide an integrated picture......The master two-dimensional gel database of human AMA cells currently lists 3801 cellular and secreted proteins, of which 371 cellular polypeptides (306 IEF; 65 NEPHGE) were added to the master images during the last 10 months. These include: (i) very basic and acidic proteins that do not focus...

Altered drug binding to serum proteins in pregnant women: therapeutic relevance.

OpenAIRE

Perucca, E; Ruprah, M; Richens, A

1981-01-01

The binding of diazepam, phenytoin and valproic acid to serum proteins in vitro has been compared in pregnant women of different gestational ages and in controls. The unbound fraction of each of three drugs was elevated during pregnancy (particularly during the last 8 weeks) probably due, at least in part, to a fall in serum albumin concentration. These findings may provide a partial explanation for the increase in the clearance of certain drugs during pregnancy and need to be taken into acco...

About Connections

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Kathleen S Rockland

2015-05-01

Full Text Available Despite the attention attracted by connectomics, one can lose sight of the very real questions concerning What are connections? In the neuroimaging community, structural connectivity is ground truth and underlying constraint on functional or effective connectivity. It is referenced to underlying anatomy; but, as increasingly remarked, there is a large gap between the wealth of human brain mapping and the relatively scant data on actual anatomical connectivity. Moreover, connections have typically been discussed as pairwise, point x projecting to point y (or: to points y and z, or more recently, in graph theoretical terms, as nodes or regions and the interconnecting edges. This is a convenient shorthand, but tends not to capture the richness and nuance of basic anatomical properties as identified in the classic tradition of tracer studies. The present short review accordingly revisits connectional weights, heterogeneity, reciprocity, topography, and hierarchical organization, drawing on concrete examples. The emphasis is on presynaptic long-distance connections, motivated by the intention to probe current assumptions and promote discussions about further progress and synthesis.

Blood-brain barrier drug delivery of IgG fusion proteins with a transferrin receptor monoclonal antibody.

Science.gov (United States)

Pardridge, William M

2015-02-01

Biologic drugs are large molecules that do not cross the blood- brain barrier (BBB). Brain penetration is possible following the re-engineering of the biologic drug as an IgG fusion protein. The IgG domain is a MAb against an endogenous BBB receptor such as the transferrin receptor (TfR). The TfRMAb acts as a molecular Trojan horse to ferry the fused biologic drug into the brain via receptor-mediated transport on the endogenous BBB TfR. This review discusses TfR isoforms, models of BBB transport of transferrin and TfRMAbs, and the genetic engineering of TfRMAb fusion proteins, including BBB penetrating IgG-neurotrophins, IgG-decoy receptors, IgG-lysosomal enzyme therapeutics and IgG-avidin fusion proteins, as well as BBB transport of bispecific antibodies formed by fusion of a therapeutic antibody to a TfRMAb targeting antibody. Also discussed are quantitative aspects of the plasma pharmacokinetics and brain uptake of TfRMAb fusion proteins, as compared to the brain uptake of small molecules, and therapeutic applications of TfRMAb fusion proteins in mouse models of neural disease, including Parkinson's disease, stroke, Alzheimer's disease and lysosomal storage disorders. The review covers the engineering of TfRMAb-avidin fusion proteins for BBB targeted delivery of biotinylated peptide radiopharmaceuticals, low-affinity TfRMAb Trojan horses and the safety pharmacology of chronic administration of TfRMAb fusion proteins. The BBB delivery of biologic drugs is possible following re-engineering as a fusion protein with a molecular Trojan horse such as a TfRMAb. The efficacy of this technology will be determined by the outcome of future clinical trials.

An AIDS risk reduction program for Dutch drug users: an intervention mapping approach to planning.

Science.gov (United States)

van Empelen, Pepijn; Kok, Gerjo; Schaalma, Herman P; Bartholomew, L Kay

2003-10-01

This article presents the development of a theory- and evidence-based AIDS prevention program targeting Dutch drug users and aimed at promoting condom use. The emphasis is on the development of the program using a five-step intervention development protocol called intervention mapping (IM). Preceding Step 1 of the IM process, an assessment of the HIV problem among drug users was conducted. The product of IM Step 1 was a series of program objectives specifying what drug users should learn in order to use condoms consistently. In Step 2, theoretical methods for influencing the most important determinants were chosen and translated into practical strategies that fit the program objectives. The main strategy chosen was behavioral journalism. In Step 3, leaflets with role-model stories based on authentic interviews with drug users were developed and pilot tested. Finally, the need for cooperation with program users is discussed in IM Steps 4 and 5.

Identifying Interactions that Determine Fragment Binding at Protein Hotspots.

Science.gov (United States)

Radoux, Chris J; Olsson, Tjelvar S G; Pitt, Will R; Groom, Colin R; Blundell, Tom L

2016-05-12

Locating a ligand-binding site is an important first step in structure-guided drug discovery, but current methods do little to suggest which interactions within a pocket are the most important for binding. Here we illustrate a method that samples atomic hotspots with simple molecular probes to produce fragment hotspot maps. These maps specifically highlight fragment-binding sites and their corresponding pharmacophores. For ligand-bound structures, they provide an intuitive visual guide within the binding site, directing medicinal chemists where to grow the molecule and alerting them to suboptimal interactions within the original hit. The fragment hotspot map calculation is validated using experimental binding positions of 21 fragments and subsequent lead molecules. The ligands are found in high scoring areas of the fragment hotspot maps, with fragment atoms having a median percentage rank of 97%. Protein kinase B and pantothenate synthetase are examined in detail. In each case, the fragment hotspot maps are able to rationalize a Free-Wilson analysis of SAR data from a fragment-based drug design project.

Site-selective protein-modification chemistry for basic biology and drug development.

Science.gov (United States)

Krall, Nikolaus; da Cruz, Filipa P; Boutureira, Omar; Bernardes, Gonçalo J L

2016-02-01

Nature has produced intricate machinery to covalently diversify the structure of proteins after their synthesis in the ribosome. In an attempt to mimic nature, chemists have developed a large set of reactions that enable post-expression modification of proteins at pre-determined sites. These reactions are now used to selectively install particular modifications on proteins for many biological and therapeutic applications. For example, they provide an opportunity to install post-translational modifications on proteins to determine their exact biological roles. Labelling of proteins in live cells with fluorescent dyes allows protein uptake and intracellular trafficking to be tracked and also enables physiological parameters to be measured optically. Through the conjugation of potent cytotoxicants to antibodies, novel anti-cancer drugs with improved efficacy and reduced side effects may be obtained. In this Perspective, we highlight the most exciting current and future applications of chemical site-selective protein modification and consider which hurdles still need to be overcome for more widespread use.

Phylogenetic profiles of all membrane transport proteins of the malaria parasite highlight new drug targets

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January Weiner 3rd

2016-08-01

Full Text Available In order to combat the on-going malaria epidemic, discovery of new drug targets remains vital. Proteins that are essential to survival and specific to malaria parasites are key candidates. To survive within host cells, the parasites need to acquire nutrients and dispose of waste products across multiple membranes. Additionally, like all eukaryotes, they must redistribute ions and organic molecules between their various internal membrane bound compartments. Membrane transport proteins mediate all of these processes and are considered important mediators of drug resistance as well as drug targets in their own right. Recently, using advanced experimental genetic approaches and streamlined life cycle profiling, we generated a large collection of Plasmodium berghei gene deletion mutants and assigned essential gene functions, highlighting potential targets for prophylactic, therapeutic, and transmission-blocking anti-malarial drugs. Here, we present a comprehensive orthology assignment of all Plasmodium falciparum putative membrane transport proteins and provide a detailed overview of the associated essential gene functions obtained through experimental genetics studies in human and murine model parasites. Furthermore, we discuss the phylogeny of selected potential drug targets identified in our functional screen. We extensively discuss the results in the context of the functional assignments obtained using gene targeting available to date.

Protein Kinases C-Mediated Regulations of Drug Transporter Activity, Localization and Expression

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Abdullah Mayati

2017-04-01

Full Text Available Drug transporters are now recognized as major actors in pharmacokinetics, involved notably in drug–drug interactions and drug adverse effects. Factors that govern their activity, localization and expression are therefore important to consider. In the present review, the implications of protein kinases C (PKCs in transporter regulations are summarized and discussed. Both solute carrier (SLC and ATP-binding cassette (ABC drug transporters can be regulated by PKCs-related signaling pathways. PKCs thus target activity, membrane localization and/or expression level of major influx and efflux drug transporters, in various normal and pathological types of cells and tissues, often in a PKC isoform-specific manner. PKCs are notably implicated in membrane insertion of bile acid transporters in liver and, in this way, are thought to contribute to cholestatic or choleretic effects of endogenous compounds or drugs. The exact clinical relevance of PKCs-related regulation of drug transporters in terms of drug resistance, pharmacokinetics, drug–drug interactions and drug toxicity remains however to be precisely determined. This issue is likely important to consider in the context of the development of new drugs targeting PKCs-mediated signaling pathways, for treating notably cancers, diabetes or psychiatric disorders.

Improving Protocols for Protein Mapping through Proper Comparison to Crystallography Data

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Lexa, Katrina W.; Carlson, Heather A.

2013-01-01

Computational approaches to fragment-based drug design (FBDD) can complement experiments and facilitate the identification of potential hot spots along the protein surface. However, the evaluation of computational methods for mapping binding sites frequently focuses upon the ability to reproduce crystallographic coordinates to within a low RMSD threshold. This dependency on the deposited coordinate data overlooks the original electron density from the experiment, thus techniques may be developed based upon subjective - or even erroneous - atomic coordinates. This can become a significant drawback in applications to systems where the location of hot spots is unknown. Based on comparison to crystallographic density, we previously showed that mixed-solvent molecular dynamics (MixMD) accurately identifies the active site for HEWL, with acetonitrile as an organic solvent. Here, we concentrated on the influence of protic solvent on simulation and refined the optimal MixMD approach for extrapolation of the method to systems without established sites. Our results establish an accurate approach for comparing simulations to experiment. We have outlined the most efficient strategy for MixMD, based on simulation length and number of runs. The development outlined here makes MixMD a robust method which should prove useful across a broad range of target structures. Lastly, our results with MixMD match experimental data so well that consistency between simulations and density may be a useful way to aid the identification of probes vs waters during the refinement of future MSCS crystallographic structures. PMID:23327200

Drug-like density: a method of quantifying the "bindability" of a protein target based on a very large set of pockets and drug-like ligands from the Protein Data Bank.

Science.gov (United States)

Sheridan, Robert P; Maiorov, Vladimir N; Holloway, M Katharine; Cornell, Wendy D; Gao, Ying-Duo

2010-11-22

One approach to estimating the "chemical tractability" of a candidate protein target where we know the atomic resolution structure is to examine the physical properties of potential binding sites. A number of other workers have addressed this issue. We characterize ~290,000 "pockets" from ~42,000 protein crystal structures in terms of a three parameter "pocket space": volume, buriedness, and hydrophobicity. A metric DLID (drug-like density) measures how likely a pocket is to bind a drug-like molecule. This is calculated from the count of other pockets in its local neighborhood in pocket space that contain drug-like cocrystallized ligands and the count of total pockets in the neighborhood. Surprisingly, despite being defined locally, a global trend in DLID can be predicted by a simple linear regression on log(volume), buriedness, and hydrophobicity. Two levels of simplification are necessary to relate the DLID of individual pockets to "targets": taking the best DLID per Protein Data Bank (PDB) entry (because any given crystal structure can have many pockets), and taking the median DLID over all PDB entries for the same target (because different crystal structures of the same protein can vary because of artifacts and real conformational changes). We can show that median DLIDs for targets that are detectably homologous in sequence are reasonably similar and that median DLIDs correlate with the "druggability" estimate of Cheng et al. (Nature Biotechnology 2007, 25, 71-75).

Relationship between Duration of Untreated Psychosis and Intrinsic Corticostriatal Connectivity in Patients with Early Phase Schizophrenia.

Science.gov (United States)

Sarpal, Deepak K; Robinson, Delbert G; Fales, Christina; Lencz, Todd; Argyelan, Miklos; Karlsgodt, Katherine H; Gallego, Juan A; John, Majnu; Kane, John M; Szeszko, Philip R; Malhotra, Anil K

2017-10-01

Patients with first-episode psychosis experience psychotic symptoms for a mean of up to 2 years prior to initiation of treatment, and long duration of untreated psychosis (DUP) is associated with poor clinical outcomes. Meanwhile, evidence compiled from numerous studies suggests that longer DUP is not associated with structural brain abnormalities. To date, few studies have examined the relationship between DUP and functional neuroimaging measures. In the present study, we used seed-based resting-state functional connectivity to examine the impact of DUP on corticostriatal circuitry. We included 83 patients with early phase schizophrenia and minimal exposure to antipsychotic drugs (drugs. Functional connectivity maps of the striatum were generated and examined in relation to DUP as a covariate. Mediation analyses were performed on a composite measure of corticostriatal connectivity derived from the significant results of our DUP analysis. We found that longer DUP correlated with worse response to treatment as well as overall decreased functional connectivity between striatal nodes and specific regions within frontal and parietal cortices. Moreover, the relationship between DUP and treatment response was significantly mediated by corticostriatal connectivity. Our results indicate that variation in corticostriatal circuitry may play a role in the relationship between longer DUP and worsened response to treatment. Future prospective studies are necessary to further characterize potential causal links between DUP, striatal circuitry and clinical outcomes.

PockDrug-Server: a new web server for predicting pocket druggability on holo and apo proteins.

Science.gov (United States)

Hussein, Hiba Abi; Borrel, Alexandre; Geneix, Colette; Petitjean, Michel; Regad, Leslie; Camproux, Anne-Claude

2015-07-01

Predicting protein pocket's ability to bind drug-like molecules with high affinity, i.e. druggability, is of major interest in the target identification phase of drug discovery. Therefore, pocket druggability investigations represent a key step of compound clinical progression projects. Currently computational druggability prediction models are attached to one unique pocket estimation method despite pocket estimation uncertainties. In this paper, we propose 'PockDrug-Server' to predict pocket druggability, efficient on both (i) estimated pockets guided by the ligand proximity (extracted by proximity to a ligand from a holo protein structure) and (ii) estimated pockets based solely on protein structure information (based on amino atoms that form the surface of potential binding cavities). PockDrug-Server provides consistent druggability results using different pocket estimation methods. It is robust with respect to pocket boundary and estimation uncertainties, thus efficient using apo pockets that are challenging to estimate. It clearly distinguishes druggable from less druggable pockets using different estimation methods and outperformed recent druggability models for apo pockets. It can be carried out from one or a set of apo/holo proteins using different pocket estimation methods proposed by our web server or from any pocket previously estimated by the user. PockDrug-Server is publicly available at: http://pockdrug.rpbs.univ-paris-diderot.fr. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entrapment of alpha1-acid glycoprotein in high-performance affinity columns for drug-protein binding studies.

Science.gov (United States)

Bi, Cong; Jackson, Abby; Vargas-Badilla, John; Li, Rong; Rada, Giana; Anguizola, Jeanethe; Pfaunmiller, Erika; Hage, David S

2016-05-15

A slurry-based method was developed for the entrapment of alpha1-acid glycoprotein (AGP) for use in high-performance affinity chromatography to study drug interactions with this serum protein. Entrapment was achieved based on the physical containment of AGP in hydrazide-activated porous silica supports and by using mildly oxidized glycogen as a capping agent. The conditions needed for this process were examined and optimized. When this type of AGP column was used in binding studies, the association equilibrium constant (Ka) measured by frontal analysis at pH 7.4 and 37°C for carbamazepine with AGP was found to be 1.0 (±0.5)×10(5)M(-1), which agreed with a previously reported value of 1.0 (±0.1)×10(5)M(-1). Binding studies based on zonal elution were conducted for several other drugs with such columns, giving equilibrium constants that were consistent with literature values. An entrapped AGP column was also used in combination with a column containing entrapped HSA in a screening assay format to compare the binding of various drugs to AGP and HSA. These results also agreed with previous data that have been reported in literature for both of these proteins. The same entrapment method could be extended to other proteins and to the investigation of additional types of drug-protein interactions. Potential applications include the rapid quantitative analysis of biological interactions and the high-throughput screening of drug candidates for their binding to a given protein. Copyright © 2015 Elsevier B.V. All rights reserved.

PDB-Explorer: a web-based interactive map of the protein data bank in shape space.

Science.gov (United States)

Jin, Xian; Awale, Mahendra; Zasso, Michaël; Kostro, Daniel; Patiny, Luc; Reymond, Jean-Louis

2015-10-23

The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited. A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space. The 3DP property space groups proteins and protein assemblies according to their 3D-shape similarity, yet shows exquisite ability to distinguish between closely related structures. An interactive website called PDB-Explorer is presented featuring a color-coded interactive map of PDB in 3DP-space. Each pixel of the map contains one or more PDB-entries which are directly visualized as ribbon diagrams when the pixel is selected. The PDB-Explorer website allows performing 3DP-nearest neighbor searches of any PDB-entry or of any structure uploaded as protein-type PDB file. All functionalities on the website are implemented in JavaScript in a platform-independent manner and draw data from a server that is updated daily with the latest PDB additions, ensuring complete and up-to-date coverage. The essentially instantaneous 3DP-similarity search with the PDB-Explorer provides results comparable to those of much slower 3D-alignment algorithms, and automatically clusters proteins from the same superfamilies in tight groups. A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3

HDAPD: a web tool for searching the disease-associated protein structures

Science.gov (United States)

2010-01-01

Background The protein structures of the disease-associated proteins are important for proceeding with the structure-based drug design to against a particular disease. Up until now, proteins structures are usually searched through a PDB id or some sequence information. However, in the HDAPD database presented here the protein structure of a disease-associated protein can be directly searched through the associated disease name keyed in. Description The search in HDAPD can be easily initiated by keying some key words of a disease, protein name, protein type, or PDB id. The protein sequence can be presented in FASTA format and directly copied for a BLAST search. HDAPD is also interfaced with Jmol so that users can observe and operate a protein structure with Jmol. The gene ontological data such as cellular components, molecular functions, and biological processes are provided once a hyperlink to Gene Ontology (GO) is clicked. Further, HDAPD provides a link to the KEGG map such that where the protein is placed and its relationship with other proteins in a metabolic pathway can be found from the map. The latest literatures namely titles, journals, authors, and abstracts searched from PubMed for the protein are also presented as a length controllable list. Conclusions Since the HDAPD data content can be routinely updated through a PHP-MySQL web page built, the new database presented is useful for searching the structures for some disease-associated proteins that may play important roles in the disease developing process for performing the structure-based drug design to against the diseases. PMID:20158919

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

Science.gov (United States)

Lapek, John D; Greninger, Patricia; Morris, Robert; Amzallag, Arnaud; Pruteanu-Malinici, Iulian; Benes, Cyril H; Haas, Wilhelm

2017-10-01

The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

Establishment of a high-resolution 2-D reference map of human spermatozoal proteins from 12 fertile sperm-bank donors.

Science.gov (United States)

Li, Ling-Wei; Fan, Li-Qing; Zhu, Wen-Bing; Nien, Hong-Chuan; Sun, Bo-Lan; Luo, Ke-Li; Liao, Ting-Ting; Tang, Le; Lu, Guang-Xiu

2007-05-01

To extend the analysis of the proteome of human spermatozoa and establish a 2-D gel electrophoresis (2-DE) reference map of human spermatozoal proteins in a pH range of 3.5-9.0. In order to reveal more protein spots, immobilized pH gradient strips (24 cm) of broad range of pH 3-10 and the narrower range of pH 6-9, as well as different overlapping narrow range pH immobilized pH gradient (IPG) strips, including 3.5-4.5, 4.0-5.0, 4.5-5.5, 5.0-6.0 and 5.5-6.7, were used. After 2-DE, several visually identical spots between the different pH range 2-D gel pairs were cut from the gels and confirmed by mass spectrometry and used as landmarks for computer analysis. The 2-D reference map with pH value from 3.5 to 9.0 was synthesized by using the ImageMaster analysis software. The overlapping spots were excluded, so that every spot was counted only once. A total of 3872 different protein spots were identified from the reference map, an approximately 3-fold increase compared to the broad range pH 3-10 IPG strip (1306 spots). The present 2-D pattern is a high resolution 2-D reference map for human fertile spermatozoal protein spots. A comprehensive knowledge of the protein composition of human spermatozoa is very meaningful in studying dysregulation of male fertility.

Continuous-flow liquid microjunction surface sampling probe connected on-line with high-performance liquid chromatography/mass spectrometry for spatially resolved analysis of small molecules and proteins.

Science.gov (United States)

Van Berkel, Gary J; Kertesz, Vilmos

2013-06-30

A continuous-flow liquid microjunction surface sampling probe extracts soluble material from surfaces for direct ionization and detection by mass spectrometry. Demonstrated here is the on-line coupling of such a probe with high-performance liquid chromatography/mass spectrometry (HPLC/MS) enabling extraction, separation and detection of small molecules and proteins from surfaces in a spatially resolved (~0.5 mm diameter spots) manner. A continuous-flow liquid microjunction surface sampling probe was connected to a six-port, two-position valve for extract collection and injection to an HPLC column. A QTRAP® 5500 hybrid triple quadrupole linear ion trap equipped with a Turbo V™ ion source operated in positive electrospray ionization (ESI) mode was used for all experiments. The system operation was tested with the extraction, separation and detection of propranolol and associated metabolites from drug dosed tissues, caffeine from a coffee bean, cocaine from paper currency, and proteins from dried sheep blood spots on paper. Confirmed in the tissue were the parent drug and two different hydroxypropranolol glucuronides. The mass spectrometric response for these compounds from different locations in the liver showed an increase with increasing extraction time (5, 20 and 40 s). For on-line separation and detection/identification of extracted proteins from dried sheep blood spots, two major protein peaks dominated the chromatogram and could be correlated with the expected masses for the hemoglobin α and β chains. Spatially resolved sampling, separation, and detection of small molecules and proteins from surfaces can be accomplished using a continuous-flow liquid microjunction surface sampling probe coupled on-line with HPLC/MS detection. Published in 2013. This article is a U.S. Government work and is in the public domain in the USA.

Spatial Mapping of Protein Abundances in the Mouse Brain by Voxelation Integrated with High-Throughput Liquid Chromatography ? Mass Spectrometry

International Nuclear Information System (INIS)

Petyuk, Vladislav A.; Qian, Weijun; Chin, Mark H.; Wang, Haixing H.; Livesay, Eric A.; Monroe, Matthew E.; Adkins, Joshua N.; Jaitly, Navdeep; Anderson, David J.; Camp, David G.; Smith, Desmond J.; Smith, Richard D.

2007-01-01

Temporally and spatially resolved mapping of protein abundance patterns within the mammalian brain is of significant interest for understanding brain function and molecular etiologies of neurodegenerative diseases; however, such imaging efforts have been greatly challenged by complexity of the proteome, throughput and sensitivity of applied analytical methodologies, and accurate quantitation of protein abundances across the brain. Here, we describe a methodology for comprehensive spatial proteome mapping that addresses these challenges by employing voxelation integrated with automated microscale sample processing, high-throughput LC system coupled with high resolution Fourier transform ion cyclotron mass spectrometer and a ''universal'' stable isotope labeled reference sample approach for robust quantitation. We applied this methodology as a proof-of-concept trial for the analysis of protein distribution within a single coronal slice of a C57BL/6J mouse brain. For relative quantitation of the protein abundances across the slice, an 18O-isotopically labeled reference sample, derived from a whole control coronal slice from another mouse, was spiked into each voxel sample and stable isotopic intensity ratios were used to obtain measures of relative protein abundances. In total, we generated maps of protein abundance patterns for 1,028 proteins. The significant agreement of the protein distributions with previously reported data supports the validity of this methodology, which opens new opportunities for studying the spatial brain proteome and its dynamics during the course of disease progression and other important biological and associated health aspects in a discovery-driven fashion

Comparative study and grouping of nonstructural (NS1)proteins of influenza A viruses by the method of oligopeptide mapping

International Nuclear Information System (INIS)

Sokolov, B.P.; Rudneva, I.A.; Zhdanov, V.M.

1983-01-01

Oligopeptide mapping of 35 S-methionine labeled non-stuctural (NS1) proteins of 23 influenza A virus strains showed the presence of both common and variable oligopeptides. Analysis of the oligopeptide maps revealed at least four groups of NS1 proteins. The first group includes NS1 proteins of several human H1N1 influenza viruses (that were designated as H0N1 according to the old classification). The second group is composed of NS1 proteins of H1N1 and H2N2 viruses. The third group includes NS1 proteins of H3N2 human influenza viruses. The fourth group is composed of NS1 proteins of five avian influenza viruses and an equine (H3N8) influenza virus. Two animal influenza viruses A/equi/Prague/56 (H7N7) and A/duck/England/56 (H11N6) contain NS1 proteins that belong to the second group. (Author)

pH-sensitive polymeric nanoparticles to improve oral bioavailability of peptide/protein drugs and poorly water-soluble drugs.

Science.gov (United States)

Wang, Xue-Qing; Zhang, Qiang

2012-10-01

pH-sensitive polymeric nanoparticles are promising for oral drug delivery, especially for peptide/protein drugs and poorly water-soluble medicines. This review describes current status of pH-sensitive polymeric nanoparticles for oral drug delivery and introduces the mechanisms of drug release from them as well as possible reasons for absorption improvement, with emphasis on our contribution to this field. pH-sensitive polymeric nanoparticles are prepared mainly with polyanions, polycations, their mixtures or cross-linked polymers. The mechanisms of drug release are the result of carriers' dissolution, swelling or both of them at specific pH. The possible reasons for improvement of oral bioavailability include the following: improve drug stability, enhance mucoadhesion, prolong resident time in GI tract, ameliorate intestinal permeability and increase saturation solubility and dissolution rate for poorly water-soluble drugs. As for the advantages of pH-sensitive nanoparticles over conventional nanoparticles, we conclude that (1) most carriers used are enteric-coating materials and their safety has been approved. (2) The rapid dissolution or swelling of carriers at specific pH results in quick drug release and high drug concentration gradient, which is helpful for absorption. (3) At the specific pH carriers dissolve or swell, and the bioadhesion of carriers to mucosa becomes high because nanoparticles turn from solid to gel, which can facilitate drug absorption. Copyright © 2012 Elsevier B.V. All rights reserved.

Peptide drugs to target G protein-coupled receptors.

Science.gov (United States)

Bellmann-Sickert, Kathrin; Beck-Sickinger, Annette G

2010-09-01

Major indications for use of peptide-based therapeutics include endocrine functions (especially diabetes mellitus and obesity), infectious diseases, and cancer. Whereas some peptide pharmaceuticals are drugs, acting as agonists or antagonists to directly treat cancer, others (including peptide diagnostics and tumour-targeting pharmaceuticals) use peptides to 'shuttle' a chemotherapeutic agent or a tracer to the tumour and allow sensitive imaging or targeted therapy. Significant progress has been made in the last few years to overcome disadvantages in peptide design such as short half-life, fast proteolytic cleavage, and low oral bioavailability. These advances include peptide PEGylation, lipidisation or multimerisation; the introduction of peptidomimetic elements into the sequences; and innovative uptake strategies such as liposomal, capsule or subcutaneous formulations. This review focuses on peptides targeting G protein-coupled receptors that are promising drug candidates or that have recently entered the pharmaceutical market. Copyright 2010 Elsevier Ltd. All rights reserved.

Packaging protein drugs as bacterial inclusion bodies for therapeutic applications

Directory of Open Access Journals (Sweden)

Villaverde Antonio

2012-06-01

Full Text Available Abstract A growing number of insights on the biology of bacterial inclusion bodies (IBs have revealed intriguing utilities of these protein particles. Since they combine mechanical stability and protein functionality, IBs have been already exploited in biocatalysis and explored for bottom-up topographical modification in tissue engineering. Being fully biocompatible and with tuneable bio-physical properties, IBs are currently emerging as agents for protein delivery into mammalian cells in protein-replacement cell therapies. So far, IBs formed by chaperones (heat shock protein 70, Hsp70, enzymes (catalase and dihydrofolate reductase, grow factors (leukemia inhibitory factor, LIF and structural proteins (the cytoskeleton keratin 14 have been shown to rescue exposed cells from a spectrum of stresses and restore cell functions in absence of cytotoxicity. The natural penetrability of IBs into mammalian cells (reaching both cytoplasm and nucleus empowers them as an unexpected platform for the controlled delivery of essentially any therapeutic polypeptide. Production of protein drugs by biopharma has been traditionally challenged by IB formation. However, a time might have arrived in which recombinant bacteria are to be engineered for the controlled packaging of therapeutic proteins as nanoparticulate materials (nanopills, for their extra- or intra-cellular release in medicine and cosmetics.

Lipid and protein maps defining arterial layers in atherosclerotic aorta

Directory of Open Access Journals (Sweden)

Marta Martin-Lorenzo

2015-09-01

Full Text Available Subclinical atherosclerosis cannot be predicted and novel therapeutic targets are needed. The molecular anatomy of healthy and atherosclerotic tissue is pursued to identify ongoing molecular changes in atherosclerosis development. Mass Spectrometry Imaging (MSI accounts with the unique advantage of analyzing proteins and metabolites (lipids while preserving their original localization; thus two dimensional maps can be obtained. Main molecular alterations were investigated in a rabbit model in response to early development of atherosclerosis. Aortic arterial layers (intima and media and calcified regions were investigated in detail by MALDI-MSI and proteins and lipids specifically defining those areas of interest were identified. These data further complement main findings previously published in J Proteomics (M. Martin-Lorenzo et al., J. Proteomics. (In press; M. Martin-Lorenzo et al., J. Proteomics 108 (2014 465–468. [1,2].

Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

Science.gov (United States)

Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

2018-01-01

Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug distribution properties should be considered at the initial phases of the drug design and development. Therefore, PPB prediction models are receiving an increased attention. In the current study, we present a systematic approach using Support vector machine, Artificial neural network, k- nearest neighbor, Probabilistic neural network, Partial least square and Linear discriminant analysis to relate various in vitro and in silico molecular descriptors to a diverse dataset of 736 drugs/drug-like compounds. The overall accuracy of Support vector machine with Radial basis function kernel came out to be comparatively better than the rest of the applied algorithms. The training set accuracy, validation set accuracy, precision, sensitivity, specificity and F1 score for the Suprort vector machine was found to be 89.73%, 89.97%, 92.56%, 87.26%, 91.97% and 0.898, respectively. This model can potentially be useful in screening of relevant drug candidates at the preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Connective tissue growth factor and bone morphogenetic protein 2 are induced following myocardial ischemia in mice and humans.

Science.gov (United States)

Rutkovskiy, Arkady; Sagave, Julia; Czibik, Gabor; Baysa, Anton; Zihlavnikova Enayati, Katarina; Hillestad, Vigdis; Dahl, Christen Peder; Fiane, Arnt; Gullestad, Lars; Gravning, Jørgen; Ahmed, Shakil; Attramadal, Håvard; Valen, Guro; Vaage, Jarle

2017-09-01

We aimed to study the cardiac expression of bone morphogenetic protein 2, its receptor 1 b, and connective tissue growth factor, factors implicated in cardiac embryogenesis, following ischemia/hypoxia, heart failure, and in remodeling hearts from humans and mice. Biopsies from the left ventricle of patients with end-stage heart failure due to dilated cardiomyopathy or coronary artery disease were compared with donor hearts and biopsies from patients with normal heart function undergoing coronary artery bypass grafting. Mouse model of post-infarction remodeling was made by permanent ligation of the left coronary artery. Hearts were analyzed by real-time polymerase chain reaction and Western blotting after 24 hours and after 2 and 4 weeks. Patients with dilated cardiomyopathy and mice post-infarction had increased cardiac expression of connective tissue growth factor. Bone morphogenetic protein 2 was increased in human hearts failing due to coronary artery disease and in mice post-infarction. Gene expression of bone morphogenetic protein receptor 1 beta was reduced in hearts of patients with failure, but increased two weeks following permanent ligation of the left coronary artery in mice. In conclusion, connective tissue growth factor is upregulated in hearts of humans with dilated cardiomyopathy, bone morphogenetic protein 2 is upregulated in remodeling due to myocardial infarction while its receptor 1 b in human failing hearts is downregulated. A potential explanation might be an attempt to engage regenerative processes, which should be addressed by further, mechanistic studies.

Cloud computing for protein-ligand binding site comparison.

Science.gov (United States)

Hung, Che-Lun; Hua, Guan-Jie

2013-01-01

The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery.

On the structure of finite-sheeted coverings of compact connected groups

OpenAIRE

Grigorian, S. A.; Gumerov, R. N.

2004-01-01

Finite-sheeted covering mappings onto compact connected groups are studied. It is shown that a finite-sheeted covering mapping from a connected Hausdorff topological space onto a compact connected abelian group G must be a homeomorphism provided that the character group of G admits division by the degree of given covering mapping. Using this result, we obtain criteria of triviality for finite coverings of G in terms of its character group and means on G. In order to establish these facts, for...

Assignment of protein backbone resonances using connectivity, torsion angles and 13Cα chemical shifts

International Nuclear Information System (INIS)

Morris, Laura C.; Valafar, Homayoun; Prestegard, James H.

2004-01-01

A program is presented which will return the most probable sequence location for a short connected set of residues in a protein given just 13 C α chemical shifts (δ( 13 C α )) and data restricting the φ and ψ backbone angles. Data taken from both the BioMagResBank and the Protein Data Bank were used to create a probability density function (PDF) using a multivariate normal distribution in δ( 13 C α ), φ, and ψ space for each amino acid residue. Extracting and combining probabilities for particular amino acid residues in a short proposed sequence yields a score indicative of the correctness of the proposed assignment. The program is illustrated using several proteins for which structure and 13 C α chemical shift data are available

Neuroinformatics of the Allen Mouse Brain Connectivity Atlas.

Science.gov (United States)

Kuan, Leonard; Li, Yang; Lau, Chris; Feng, David; Bernard, Amy; Sunkin, Susan M; Zeng, Hongkui; Dang, Chinh; Hawrylycz, Michael; Ng, Lydia

2015-02-01

The Allen Mouse Brain Connectivity Atlas is a mesoscale whole brain axonal projection atlas of the C57Bl/6J mouse brain. Anatomical trajectories throughout the brain were mapped into a common 3D space using a standardized platform to generate a comprehensive and quantitative database of inter-areal and cell-type-specific projections. This connectivity atlas has several desirable features, including brain-wide coverage, validated and versatile experimental techniques, a single standardized data format, a quantifiable and integrated neuroinformatics resource, and an open-access public online database (http://connectivity.brain-map.org/). Meaningful informatics data quantification and comparison is key to effective use and interpretation of connectome data. This relies on successful definition of a high fidelity atlas template and framework, mapping precision of raw data sets into the 3D reference framework, accurate signal detection and quantitative connection strength algorithms, and effective presentation in an integrated online application. Here we describe key informatics pipeline steps in the creation of the Allen Mouse Brain Connectivity Atlas and include basic application use cases. Copyright © 2014 Elsevier Inc. All rights reserved.

Scaffold proteins LACK and TRACK as potential drug targets in kinetoplastid parasites: Development of inhibitors

Directory of Open Access Journals (Sweden)

Nir Qvit

2016-04-01

Full Text Available Parasitic diseases cause ∼500,000 deaths annually and remain a major challenge for therapeutic development. Using a rational design based approach, we developed peptide inhibitors with anti-parasitic activity that were derived from the sequences of parasite scaffold proteins LACK (Leishmania's receptor for activated C-kinase and TRACK (Trypanosoma receptor for activated C-kinase. We hypothesized that sequences in LACK and TRACK that are conserved in the parasites, but not in the mammalian ortholog, RACK (Receptor for activated C-kinase, may be interaction sites for signaling proteins that are critical for the parasites' viability. One of these peptides exhibited leishmanicidal and trypanocidal activity in culture. Moreover, in infected mice, this peptide was also effective in reducing parasitemia and increasing survival without toxic effects. The identified peptide is a promising new anti-parasitic drug lead, as its unique features may limit toxicity and drug-resistance, thus overcoming central limitations of most anti-parasitic drugs. Keywords: Chagas disease, Leishmaniasis, Peptide, LACK, TRACK, Scaffold protein

In-depth mapping of the mouse brain N-glycoproteome reveals widespread N-glycosylation of diverse brain proteins.

Science.gov (United States)

Fang, Pan; Wang, Xin-Jian; Xue, Yu; Liu, Ming-Qi; Zeng, Wen-Feng; Zhang, Yang; Zhang, Lei; Gao, Xing; Yan, Guo-Quan; Yao, Jun; Shen, Hua-Li; Yang, Peng-Yuan

2016-06-21

N-glycosylation is one of the most prominent and abundant posttranslational modifications of proteins. It is estimated that over 50% of mammalian proteins undergo glycosylation. However, the analysis of N-glycoproteins has been limited by the available analytical technology. In this study, we comprehensively mapped the N-glycosylation sites in the mouse brain proteome by combining complementary methods, which included seven protease treatments, four enrichment techniques and two fractionation strategies. Altogether, 13492 N-glycopeptides containing 8386 N-glycosylation sites on 3982 proteins were identified. After evaluating the performance of the above methods, we proposed a simple and efficient workflow for large-scale N-glycosylation site mapping. The optimized workflow yielded 80% of the initially identified N-glycosylation sites with considerably less effort. Analysis of the identified N-glycoproteins revealed that many of the mouse brain proteins are N-glycosylated, including those proteins in critical pathways for nervous system development and neurological disease. Additionally, several important biomarkers of various diseases were found to be N-glycosylated. These data confirm that N-glycosylation is important in both physiological and pathological processes in the brain, and provide useful details about numerous N-glycosylation sites in brain proteins.

Distribution of Spiked Drugs between Milk Fat, Skim Milk, Whey, Curd, and Milk Protein Fractions: Expansion of Partitioning Models.

Science.gov (United States)

Lupton, Sara J; Shappell, Nancy W; Shelver, Weilin L; Hakk, Heldur

2018-01-10

The distributions of eight drugs (acetaminophen, acetylsalicylic acid/salicylic acid, ciprofloxacin, clarithromycin, flunixin, phenylbutazone, praziquantel, and thiamphenicol) were determined in milk products (skim milk, milk fat, curd, whey, and whey protein) and used to expand a previous model (from 7 drugs to 15 drugs) for predicting drug distribution. Phenylbutazone and praziquantel were found to distribute with the lipid and curd phases (≥50%). Flunixin distribution was lower but similar in direction (12% in milk fat, 39% in curd). Acetaminophen, ciprofloxacin, and praziquantel preferentially associated with casein proteins, whereas thiamphenicol and clarithromycin associated preferentially to whey proteins. Regression analyses for log [milk fat]/[skim milk] and log [curd]/[whey] had r 2 values of 0.63 and 0.67, respectively, with p of <0.001 for 15 drugs (7 previously tested and 8 currently tested). The robustness of the distribution model was enhanced by doubling the number of drugs originally tested.

Peptide and low molecular weight proteins based kidney targeted drug delivery systems.

Science.gov (United States)

Xu, Pengfei; Zhang, Hailiang; Dang, Ruili; Jiang, Pei

2018-05-30

Renal disease is a worldwide public health problem, and unfortunately, the therapeutic index of regular drugs is limited. Thus, it is a great need to develop effective treatment strategies. Among the reported strategies, kidney-targeted drug delivery system is a promising method to increase renal efficacy and reduce extra-renal toxicity. In recent years, working as vehicles for targeted drug delivery, low molecular weight proteins (LMWP) and peptide have received immense attention due to their many advantages, such as selective accumulation in kidney, high drug loading capability, control over routes of biodegradation, convenience in modification at the amino terminus, and good biocompatibility. In this review, we describe the current LMWP and peptide carriers for kidney targeted drug delivery systems. In addition, we discuss different linking strategies between carriers and drugs. Furthermore, we briefly outline the current status and attempt to give an outlook on the further study. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Protein tethering enables rapid and label-free SERS platform for screening drugs of abuse (Conference Presentation)

Science.gov (United States)

Siddhanta, Soumik; Wróbel, Maciej S.; Barman, Ishan

2017-02-01

A quick, cost-effective method for detection of drugs of abuse in biological fluids would be of great value in healthcare, law enforcement, and home testing applications. The alarming rise in narcotics abuse has led to considerable focus on developing potent and versatile analytical tools that can address this societal problem. While laboratory testing plays a key role in the current detection of drug misuse and the evaluation of patients with drug induced intoxication, these typically require expensive reagents and trained personnel, and may take hours to complete. Thus, a significant unmet need is to engineer a facile method that can rapidly detect drugs with little sample preparation, especially the bound fraction that is typically dominant in the blood stream. Here we report an approach that combines the exquisite sensitivity of surface enhanced Raman spectroscopy (SERS) and a facile protein tethering mechanism to reliably detect four different classes of drugs, barbiturate, benzodiazepine, amphetamine and benzoylecgonine. The proposed approach harnesses the reliable and specific attachment of proteins to both drugs and nanoparticle to facilitate the enhancement of spectral markers that are sensitive to the presence of the drugs. In conjunction with chemometric tools, we have shown the ability to quantify these drugs lower than levels achievable by existing clinical immunoassays. Through molecular docking simulations, we also probe the mechanistic underpinnings of the protein tethering approach, opening the door to detection of a broad class of narcotics in biological fluids within a few minutes as well as for groundwater analysis and toxin detection.

LmxMPK4, an essential mitogen-activated protein kinase of Leishmania mexicana is phosphorylated and activated by the STE7-like protein kinase LmxMKK5

DEFF Research Database (Denmark)

John von Freyend, Simona; Rosenqvist, Heidi; Fink, Annette

2010-01-01

The essential mitogen-activated protein kinase (MAP kinase), LmxMPK4, of Leishmania mexicana is minimally active when purified following recombinant expression in Escherichia coli and was therefore unsuitable for drug screening until now. Using an E. coli protein co-expression system we identified...... LmxMKK5, a STE7-like protein kinase from L. mexicana, which phosphorylates and activates recombinant LmxMPK4 in vitro. LmxMKK5 is comprised of 525 amino acids and has a calculated molecular mass of 55.9kDa. The co-expressed, purified LmxMPK4 showed strong phosphotransferase activity in radiometric...... kinase assays and was confirmed by immunoblot and tandem mass spectrometry analyses to be phosphorylated on threonine 190 and tyrosine 192 of the typical TXY MAP kinase activation motif. The universal protein kinase inhibitor staurosporine reduced the phosphotransferase activity of co...