@article {19381286, title = {A kernel for open source drug discovery in tropical diseases}, journal = {PLoS Negl Trop Dis}, volume = {3}, number = {4}, year = {2009}, note = {Orti, Leticia Carbajo, Rodrigo J Pieper, Ursula Eswar, Narayanan Maurer, Stephen M Rai, Arti K Taylor, Ginger Todd, Matthew H Pineda-Lucena, Antonio Sali, Andrej Marti-Renom, Marc A United States PLoS neglected tropical diseases PLoS Negl Trop Dis. 2009;3(4):e418. Epub 2009 Apr 21.}, pages = {e418}, abstract = {BACKGROUND: Conventional patent-based drug development incentives work badly for the developing world, where commercial markets are usually small to non-existent. For this reason, the past decade has seen extensive experimentation with alternative R\&D institutions ranging from private-public partnerships to development prizes. Despite extensive discussion, however, one of the most promising avenues-open source drug discovery-has remained elusive. We argue that the stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. Historically, open source software collaborations have almost never succeeded without such "kernels". METHODOLOGY/PRINCIPAL FINDINGS: HERE, WE USE A COMPUTATIONAL PIPELINE FOR: (i) comparative structure modeling of target proteins, (ii) predicting the localization of ligand binding sites on their surfaces, and (iii) assessing the similarity of the predicted ligands to known drugs. Our kernel currently contains 143 and 297 protein targets from ten pathogen genomes that are predicted to bind a known drug or a molecule similar to a known drug, respectively. The kernel provides a source of potential drug targets and drug candidates around which an online open source community can nucleate. Using NMR spectroscopy, we have experimentally tested our predictions for two of these targets, confirming one and invalidating the other. CONCLUSIONS/SIGNIFICANCE: The TDI kernel, which is being offered under the Creative Commons attribution share-alike license for free and unrestricted use, can be accessed on the World Wide Web at http://www.tropicaldisease.org. We hope that the kernel will facilitate collaborative efforts towards the discovery of new drugs against parasites that cause tropical diseases.}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=19381286}, author = {Orti, L. and Carbajo, R. J. and Pieper, U. and Eswar, N. and Maurer, S. M. and Rai, A. K. and Taylor, G. and Todd, M. H. and Pineda-Lucena, A. and Sali, A. and M. A. Marti-Renom} } @article {19352362, title = {A kernel for the Tropical Disease Initiative}, journal = {Nat Biotechnol}, volume = {27}, number = {4}, year = {2009}, note = {

Orti, Leticia Carbajo, Rodrigo J Pieper, Ursula Eswar, Narayanan Maurer, Stephen M Rai, Arti K Taylor, Ginger Todd, Matthew H Pineda-Lucena, Antonio Sali, Andrej Marti-Renom, Marc A P01 AI035707/AI/NIAID NIH HHS/United States P01 GM71790/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States U54 GM074945/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t United States Nature biotechnology Nat Biotechnol. 2009 Apr;27(4):320-1.

}, pages = {320-1}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=19352362}, author = {Orti, L. and Carbajo, R. J. and Pieper, U. and Eswar, N. and Maurer, S. M. and Rai, A. K. and Taylor, G. and Todd, M. H. and Pineda-Lucena, A. and Sali, A. and M. A. Marti-Renom} } @article {18948282, title = {MODBASE, a database of annotated comparative protein structure models and associated resources}, journal = {Nucleic Acids Res}, volume = {37}, number = {Database issue}, year = {2009}, note = {Pieper, Ursula Eswar, Narayanan Webb, Ben M Eramian, David Kelly, Libusha Barkan, David T Carter, Hannah Mankoo, Parminder Karchin, Rachel Marti-Renom, Marc A Davis, Fred P Sali, Andrej GM08284/GM/NIGMS NIH HHS/United States P01 GM71790/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States U01 GM61390/GM/NIGMS NIH HHS/United States U54 GM074929/GM/NIGMS NIH HHS/United States U54 GM074945/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, Non-P.H.S. England Nucleic acids research Nucleic Acids Res. 2009 Jan;37(Database issue):D347-54. Epub 2008 Oct 23.}, pages = {D347-54}, abstract = {MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by MODPIPE, an automated modeling pipeline that relies primarily on MODELLER for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE currently contains 5,152,695 reliable models for domains in 1,593,209 unique protein sequences; only models based on statistically significant alignments and/or models assessed to have the correct fold are included. MODBASE also allows users to calculate comparative models on demand, through an interface to the MODWEB modeling server (http://salilab.org/modweb). Other resources integrated with MODBASE include databases of multiple protein structure alignments (DBAli), structurally defined ligand binding sites (LIGBASE), predicted ligand binding sites (AnnoLyze), structurally defined binary domain interfaces (PIBASE) and annotated single nucleotide polymorphisms and somatic mutations found in human proteins (LS-SNP, LS-Mut). MODBASE models are also available through the Protein Model Portal (http://www.proteinmodelportal.org/).}, keywords = {*Databases, Molecular Mutation Polymorphism, Protein Genomics Humans Ligands *Models, Protein User-Computer Interface, Single Nucleotide Protein Folding Protein Interaction Domains and Motifs *Protein Structure, Tertiary Proteins/genetics *Structural Homology}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18948282}, author = {Pieper, U. and Eswar, N. and Webb, B. M. and Eramian, D. and Kelly, L. and Barkan, D. T. and Carter, H. and Mankoo, P. and Karchin, R. and M. A. Marti-Renom and Davis, F. P. and Sali, A.} } @article {19357100, title = {ModLink+: Improving fold recognition by using protein-protein interactions}, journal = {Bioinformatics}, year = {2009}, note = {

Journal article Bioinformatics (Oxford, England) Bioinformatics. 2009 Apr 8.

}, abstract = {

MOTIVATION: Several strategies have been developed to predict the fold of a target protein sequence, most of which are based on aligning the target sequence to other sequences of known structure. Previously, we demonstrated that the consideration of protein-protein interactions significantly increases the accuracy of fold assignment compared to PSI-BLAST sequence comparisons. A drawback of our method was the low number of proteins to which a fold could be assigned. Here, we present an improved version of the method that addresses this limitation. We also compare our method to other state-of-the-art fold assignment methodologies. RESULTS: Our approach (ModLink+) has been tested on 3,716 proteins with domain folds classified in the Structural Classification Of Proteins (SCOP) as well as known interacting partners in the Database of Interacting Proteins (DIP). For this test set, the ratio of success (PPV) on fold assignment increases from 75\% for PSI-BLAST, 83\% for HHSearch and 81\% for PRC to more than 90\% for ModLink+ at the e-value cutoff of 10(-3). Under this e-value, ModLink+ can assign a fold to 30-45\% of the proteins in the test set, while our previous method could cover less than 25\%. When applied to 6,384 proteins with unknown fold in the yeast proteome, ModLink+ combined with PSI-BLAST assigns a fold for domains in 3,738 proteins, while PSI-BLAST alone only covers 2,122 proteins, HHSearch 2,969 and PRC 2,826 proteins, using a threshold e-value that would represent a PPV higher than 82\% for each method in the test set. AVAILABILITY: The ModLink+ server is freely accessible in the World Wide Web at http://sbi.imim.es/modlink/. CONTACT: boliva@imim.es.

}, keywords = {protein folding}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=19357100}, author = {Fornes, O. and Aragues, R. and Espadaler, J. and M. A. Marti-Renom and Sali, A. and Oliva, B.} } @article {18505562, title = {Prediction of enzyme function by combining sequence similarity and protein interactions}, journal = {BMC Bioinformatics}, volume = {9}, year = {2008}, note = {Espadaler, Jordi Eswar, Narayanan Querol, Enrique Aviles, Francesc X Sali, Andrej Marti-Renom, Marc A Oliva, Baldomero GM54762/GM/NIGMS NIH HHS/United States GM71790/GM/NIGMS NIH HHS/United States GM74929/GM/NIGMS NIH HHS/United States GM74945/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t England BMC bioinformatics BMC Bioinformatics. 2008 May 27;9:249.}, pages = {249}, abstract = {BACKGROUND: A number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners. RESULTS: The method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40\% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80\% to 90\% at 80\% coverage when compared to PSI-BLAST. CONCLUSION: Our method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10\% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.}, keywords = {Amino Acid *Software Structure-Activity Relationship Substrate Specificity/genetics, Amino Acid Sequence/physiology Databases, Automated Predictive Value of Tests Protein Interaction Mapping Proteins/analysis/metabolism Sequence Alignment Sequence Analysis, Protein *Sequence Homology, Protein Enzymes/analysis/*metabolism Fuzzy Logic Pattern Recognition}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18505562}, author = {Espadaler, J. and Eswar, N. and Querol, E. and Aviles, F. X. and Sali, A. and M. A. Marti-Renom and Oliva, B.} } @article {17570147, title = {The AnnoLite and AnnoLyze programs for comparative annotation of protein structures}, journal = {BMC Bioinformatics}, volume = {8 Suppl 4}, year = {2007}, note = {Marti-Renom, Marc A Rossi, Andrea Al-Shahrour, Fatima Davis, Fred P Pieper, Ursula Dopazo, Joaquin Sali, Andrej Research Support, Non-U.S. Gov{\textquoteright}t England BMC bioinformatics BMC Bioinformatics. 2007 May 22;8 Suppl 4:S4.}, pages = {S4}, abstract = {BACKGROUND: Advances in structural biology, including structural genomics, have resulted in a rapid increase in the number of experimentally determined protein structures. However, about half of the structures deposited by the structural genomics consortia have little or no information about their biological function. Therefore, there is a need for tools for automatically and comprehensively annotating the function of protein structures. We aim to provide such tools by applying comparative protein structure annotation that relies on detectable relationships between protein structures to transfer functional annotations. Here we introduce two programs, AnnoLite and AnnoLyze, which use the structural alignments deposited in the DBAli database. DESCRIPTION: AnnoLite predicts the SCOP, CATH, EC, InterPro, PfamA, and GO terms with an average sensitivity of 90\% and average precision of 80\%. AnnoLyze predicts ligand binding site and domain interaction patches with an average sensitivity of 70\% and average precision of 30\%, correctly localizing binding sites for small molecules in 95\% of its predictions. CONCLUSION: The AnnoLite and AnnoLyze programs for comparative annotation of protein structures can reliably and automatically annotate new protein structures. The programs are fully accessible via the Internet as part of the DBAli suite of tools at http://salilab.org/DBAli/.}, keywords = {*Algorithms Amino Acid Sequence Confidence Intervals Data Interpretation, Amino Acid *Software Structure-Activity Relationship, Protein Information Storage and Retrieval/methods Molecular Sequence Data Proteins/*chemistry/classification/*metabolism Sensitivity and Specificity Sequence Alignment/*methods Sequence Analysis, Protein/*methods Sequence Homology, Statistical *Databases}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17570147}, author = {M. A. Marti-Renom and Rossi, A. and Fatima Al-Shahrour and Davis, F. P. and Pieper, U. and Dopazo, J. and Sali, A.} } @article {17941705, title = {Characterization of protein hubs by inferring interacting motifs from protein interactions}, journal = {PLoS Comput Biol}, volume = {3}, number = {9}, year = {2007}, note = {Aragues, Ramon Sali, Andrej Bonet, Jaume Marti-Renom, Marc A Oliva, Baldo PN2 EY016525,/EY/NEI NIH HHS/United States U54 RR022220/RR/NCRR NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t United States PLoS computational biology PLoS Comput Biol. 2007 Sep;3(9):1761-71. Epub 2007 Jul 30.}, pages = {1761-71}, abstract = {The characterization of protein interactions is essential for understanding biological systems. While genome-scale methods are available for identifying interacting proteins, they do not pinpoint the interacting motifs (e.g., a domain, sequence segments, a binding site, or a set of residues). Here, we develop and apply a method for delineating the interacting motifs of hub proteins (i.e., highly connected proteins). The method relies on the observation that proteins with common interaction partners tend to interact with these partners through a common interacting motif. The sole input for the method are binary protein interactions; neither sequence nor structure information is needed. The approach is evaluated by comparing the inferred interacting motifs with domain families defined for 368 proteins in the Structural Classification of Proteins (SCOP). The positive predictive value of the method for detecting proteins with common SCOP families is 75\% at sensitivity of 10\%. Most of the inferred interacting motifs were significantly associated with sequence patterns, which could be responsible for the common interactions. We find that yeast hubs with multiple interacting motifs are more likely to be essential than hubs with one or two interacting motifs, thus rationalizing the previously observed correlation between essentiality and the number of interacting partners of a protein. We also find that yeast hubs with multiple interacting motifs evolve slower than the average protein, contrary to the hubs with one or two interacting motifs. The proposed method will help us discover unknown interacting motifs and provide biological insights about protein hubs and their roles in interaction networks.}, keywords = {Amino Acid Motifs Amino Acid Sequence Binding Sites Computer Simulation *Models, Chemical *Models, Molecular Molecular Sequence Data Protein Binding Protein Interaction Mapping/*methods Proteins/*chemistry Sequence Analysis, Protein/*methods}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17941705}, author = {Aragues, R. and Sali, A. and Bonet, J. and M. A. Marti-Renom and Oliva, B.} } @article {17478513, title = {DBAli tools: mining the protein structure space}, journal = {Nucleic Acids Res}, volume = {35}, number = {Web Server issue}, year = {2007}, note = {Marti-Renom, Marc A Pieper, Ursula Madhusudhan, M S Rossi, Andrea Eswar, Narayanan Davis, Fred P Al-Shahrour, Fatima Dopazo, Joaquin Sali, Andrej GM 62529/GM/NIGMS NIH HHS/United States GM074929/GM/NIGMS NIH HHS/United States GM54762/GM/NIGMS NIH HHS/United States GM71790/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2007 Jul;35(Web Server issue):W393-7. Epub 2007 May 3.}, pages = {W393-7}, abstract = {The DBAli tools use a comprehensive set of structural alignments in the DBAli database to leverage the structural information deposited in the Protein Data Bank (PDB). These tools include (i) the DBAlit program that allows users to input the 3D coordinates of a protein structure for comparison by MAMMOTH against all chains in the PDB; (ii) the AnnoLite and AnnoLyze programs that annotate a target structure based on its stored relationships to other structures; (iii) the ModClus program that clusters structures by sequence and structure similarities; (iv) the ModDom program that identifies domains as recurrent structural fragments and (v) an implementation of the COMPARER method in the SALIGN command in MODELLER that creates a multiple structure alignment for a set of related protein structures. Thus, the DBAli tools, which are freely accessible via the World Wide Web at http://salilab.org/DBAli/, allow users to mine the protein structure space by establishing relationships between protein structures and their functions.}, keywords = {*Algorithms Amino Acid Sequence Computational Biology/*methods Data Interpretation, Amino Acid *Software Structure-Activity Relationship, Protein Internet Molecular Sequence Data Protein Conformation Proteins/*chemistry/classification/*metabolism Pseudomonas aeruginosa/*metabolism Sequence Alignment/*methods Sequence Analysis, Protein/*methods Sequence Homology, Statistical *Databases}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17478513}, author = {M. A. Marti-Renom and Pieper, U. and Madhusudhan, M. S. and Rossi, A. and Eswar, N. and Davis, F. P. and Fatima Al-Shahrour and Dopazo, J. and Sali, A.} } @article {18428767, title = {Comparative protein structure modeling using Modeller}, journal = {Curr Protoc Bioinformatics}, volume = {Chapter 5}, year = {2006}, note = {Eswar, Narayanan Webb, Ben Marti-Renom, Marc A Madhusudhan, M S Eramian, David Shen, Min-Yi Pieper, Ursula Sali, Andrej P01 A135707/PHS HHS/United States P01 GM71790/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States U54 GM62529/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t United States Current protocols in bioinformatics / editoral board, Andreas D. Baxevanis ... [et al.] Curr Protoc Bioinformatics. 2006 Oct;Chapter 5:Unit 5.6.}, pages = {Unit 5 6}, abstract = {Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.}, keywords = {Algorithms Amino Acid Sequence Computer Simulation Crystallography/*methods *Models, Chemical *Models, Molecular Molecular Sequence Data Protein Conformation Protein Folding Proteins/*chemistry/*ultrastructure Sequence Analysis, Protein/*methods *Software}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18428767}, author = {Eswar, N. and Webb, B. and M. A. Marti-Renom and Madhusudhan, M. S. and Eramian, D. and Shen, M. Y. and Pieper, U. and Sali, A.} } @article {16751606, title = {A composite score for predicting errors in protein structure models}, journal = {Protein Sci}, volume = {15}, number = {7}, year = {2006}, note = {Eramian, David Shen, Min-yi Devos, Damien Melo, Francisco Sali, Andrej Marti-Renom, Marc A GM 08284/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, Non-P.H.S. United States Protein science : a publication of the Protein Society Protein Sci. 2006 Jul;15(7):1653-66. Epub 2006 Jun 2.}, pages = {1653-66}, abstract = {Reliable prediction of model accuracy is an important unsolved problem in protein structure modeling. To address this problem, we studied 24 individual assessment scores, including physics-based energy functions, statistical potentials, and machine learning-based scoring functions. Individual scores were also used to construct approximately 85,000 composite scoring functions using support vector machine (SVM) regression. The scores were tested for their abilities to identify the most native-like models from a set of 6000 comparative models of 20 representative protein structures. Each of the 20 targets was modeled using a template of <30\% sequence identity, corresponding to challenging comparative modeling cases. The best SVM score outperformed all individual scores by decreasing the average RMSD difference between the model identified as the best of the set and the model with the lowest RMSD (DeltaRMSD) from 0.63 A to 0.45 A, while having a higher Pearson correlation coefficient to RMSD (r=0.87) than any other tested score. The most accurate score is based on a combination of the DOPE non-hydrogen atom statistical potential; surface, contact, and combined statistical potentials from MODPIPE; and two PSIPRED/DSSP scores. It was implemented in the SVMod program, which can now be applied to select the final model in various modeling problems, including fold assignment, target-template alignment, and loop modeling.}, keywords = {*Models, Molecular Models, Theoretical Proteins/*chemistry}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16751606}, author = {Eramian, D. and Shen, M. Y. and Devos, D. and Melo, F. and Sali, A. and M. A. Marti-Renom} } @article {16963645, title = {Localization of binding sites in protein structures by optimization of a composite scoring function}, journal = {Protein Sci}, volume = {15}, number = {10}, year = {2006}, note = {Rossi, Andrea Marti-Renom, Marc A Sali, Andrej P01 AI035707/AI/NIAID NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t United States Protein science : a publication of the Protein Society Protein Sci. 2006 Oct;15(10):2366-80. Epub 2006 Sep 8.}, pages = {2366-80}, abstract = {The rise in the number of functionally uncharacterized protein structures is increasing the demand for structure-based methods for functional annotation. Here, we describe a method for predicting the location of a binding site of a given type on a target protein structure. The method begins by constructing a scoring function, followed by a Monte Carlo optimization, to find a good scoring patch on the protein surface. The scoring function is a weighted linear combination of the z-scores of various properties of protein structure and sequence, including amino acid residue conservation, compactness, protrusion, convexity, rigidity, hydrophobicity, and charge density; the weights are calculated from a set of previously identified instances of the binding-site type on known protein structures. The scoring function can easily incorporate different types of information useful in localization, thus increasing the applicability and accuracy of the approach. To test the method, 1008 known protein structures were split into 20 different groups according to the type of the bound ligand. For nonsugar ligands, such as various nucleotides, binding sites were correctly identified in 55\%-73\% of the cases. The method is completely automated (http://salilab.org/patcher) and can be applied on a large scale in a structural genomics setting.}, keywords = {Amino Acid Sequence Binding Sites Biomechanics Hydrophobicity Ligands *Monte Carlo Method Protein Conformation Proteins/*chemistry Static Electricity}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16963645}, author = {Rossi, A. and M. A. Marti-Renom and Sali, A.} } @article {16381869, title = {MODBASE: a database of annotated comparative protein structure models and associated resources}, journal = {Nucleic Acids Res}, volume = {34}, number = {Database issue}, year = {2006}, note = {Pieper, Ursula Eswar, Narayanan Davis, Fred P Braberg, Hannes Madhusudhan, M S Rossi, Andrea Marti-Renom, Marc Karchin, Rachel Webb, Ben M Eramian, David Shen, Min-Yi Kelly, Libusha Melo, Francisco Sali, Andrej GM 08284/GM/NIGMS NIH HHS/United States P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM 54762/GM/NIGMS NIH HHS/United States R33 CA84699/CA/NCI NIH HHS/United States U54 GM074945/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2006 Jan 1;34(Database issue):D291-5.}, pages = {D291-5}, abstract = {MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models for all available protein sequences that can be matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on MODELLER for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE is updated regularly to reflect the growth in protein sequence and structure databases, and improvements in the software for calculating the models. MODBASE currently contains 3 094 524 reliable models for domains in 1 094 750 out of 1 817 889 unique protein sequences in the UniProt database (July 5, 2005); only models based on statistically significant alignments and models assessed to have the correct fold despite insignificant alignments are included. MODBASE also allows users to generate comparative models for proteins of interest with the automated modeling server MODWEB (http://salilab.org/modweb). Our other resources integrated with MODBASE include comprehensive databases of multiple protein structure alignments (DBAli, http://salilab.org/dbali), structurally defined ligand binding sites and structurally defined binary domain interfaces (PIBASE, http://salilab.org/pibase) as well as predictions of ligand binding sites, interactions between yeast proteins, and functional consequences of human nsSNPs (LS-SNP, http://salilab.org/LS-SNP).}, keywords = {Binding Sites *Databases, Molecular Polymorphism, Protein Humans Internet Ligands *Models, Protein Systems Integration User-Computer Interface, Single Nucleotide Protein Structure, Tertiary Proteins/*chemistry/genetics/metabolism Software *Structural Homology}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16381869}, author = {Pieper, U. and Eswar, N. and Davis, F. P. and Braberg, H. and Madhusudhan, M. S. and Rossi, A. and M. A. Marti-Renom and Karchin, R. and Webb, B. M. and Eramian, D. and Shen, M. Y. and Kelly, L. and Melo, F. and Sali, A.} } @article {16490207, title = {Refinement of protein structures by iterative comparative modeling and CryoEM density fitting}, journal = {J Mol Biol}, volume = {357}, number = {5}, year = {2006}, note = {Topf, Maya Baker, Matthew L Marti-Renom, Marc A Chiu, Wah Sali, Andrej 2 PN2 EY016525-02/EY/NEI NIH HHS/United States P20RR020647/RR/NCRR NIH HHS/United States P41RR02250/RR/NCRR NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, Non-P.H.S. England Journal of molecular biology J Mol Biol. 2006 Apr 14;357(5):1655-68. Epub 2006 Feb 2.}, pages = {1655-68}, abstract = {We developed a method for structure characterization of assembly components by iterative comparative protein structure modeling and fitting into cryo-electron microscopy (cryoEM) density maps. Specifically, we calculate a comparative model of a given component by considering many alternative alignments between the target sequence and a related template structure while optimizing the fit of a model into the corresponding density map. The method relies on the previously developed Moulder protocol that iterates over alignment, model building, and model assessment. The protocol was benchmarked using 20 varied target-template pairs of known structures with less than 30\% sequence identity and corresponding simulated density maps at resolutions from 5A to 25A. Relative to the models based on the best existing sequence profile alignment methods, the percentage of C(alpha) atoms that are within 5A of the corresponding C(alpha) atoms in the superposed native structure increases on average from 52\% to 66\%, which is half-way between the starting models and the models from the best possible alignments (82\%). The test also reveals that despite the improvements in the accuracy of the fitness function, this function is still the bottleneck in reducing the remaining errors. To demonstrate the usefulness of the protocol, we applied it to the upper domain of the P8 capsid protein of rice dwarf virus that has been studied by cryoEM at 6.8A. The C(alpha) root-mean-square deviation of the model based on the remotely related template, bluetongue virus VP7, improved from 8.7A to 6.0A, while the best possible model has a C(alpha) RMSD value of 5.3A. Moreover, the resulting model fits better into the cryoEM density map than the initial template structure. The method is being implemented in our program MODELLER for protein structure modeling by satisfaction of spatial restraints and will be applicable to the rapidly increasing number of cryoEM density maps of macromolecular assemblies.}, keywords = {Amino Acid Sequence Cryoelectron Microscopy *Models, Molecular Molecular Sequence Data Plant Viruses/chemistry *Protein Conformation Software Viral Proteins/*chemistry/genetics}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16490207}, author = {Topf, M. and Baker, M. L. and M. A. Marti-Renom and Chiu, W. and Sali, A.} } @article {16423846, title = {Variable gap penalty for protein sequence-structure alignment}, journal = {Protein Eng Des Sel}, volume = {19}, number = {3}, year = {2006}, note = {Madhusudhan, M S Marti-Renom, Marc A Sanchez, Roberto Sali, Andrej DE016274/DE/NIDCR NIH HHS/United States GM54762/GM/NIGMS NIH HHS/United States GM62529/GM/NIGMS NIH HHS/United States Comparative Study Research Support, N.I.H., Extramural England Protein engineering, design \& selection : PEDS Protein Eng Des Sel. 2006 Mar;19(3):129-33. Epub 2006 Jan 19.}, pages = {129-33}, abstract = {The penalty for inserting gaps into an alignment between two protein sequences is a major determinant of the alignment accuracy. Here, we present an algorithm for finding a globally optimal alignment by dynamic programming that can use a variable gap penalty (VGP) function of any form. We also describe a specific function that depends on the structural context of an insertion or deletion. It penalizes gaps that are introduced within regions of regular secondary structure, buried regions, straight segments and also between two spatially distant residues. The parameters of the penalty function were optimized on a set of 240 sequence pairs of known structure, spanning the sequence identity range of 20-40\%. We then tested the algorithm on another set of 238 sequence pairs of known structures. The use of the VGP function increases the number of correctly aligned residues from 81.0 to 84.5\% in comparison with the optimized affine gap penalty function; this difference is statistically significant according to Student{\textquoteright}s t-test. We estimate that the new algorithm allows us to produce comparative models with an additional approximately 7 million accurately modeled residues in the approximately 1.1 million proteins that are detectably related to a known structure.}, keywords = {Algorithms Amino Acid Sequence Models, Amino Acid *Software, Molecular Molecular Sequence Data Proteins/*chemistry Sequence Alignment/*methods Sequence Analysis, Protein/*methods *Sequence Homology}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16423846}, author = {Madhusudhan, M. S. and M. A. Marti-Renom and Sanchez, R. and Sali, A.} } @article {16170324, title = {The C-type lectin fold as an evolutionary solution for massive sequence variation}, journal = {Nat Struct Mol Biol}, volume = {12}, number = {10}, year = {2005}, note = {McMahon, Stephen A Miller, Jason L Lawton, Jeffrey A Kerkow, Donald E Hodes, Asher Marti-Renom, Marc A Doulatov, Sergei Narayanan, Eswar Sali, Andrej Miller, Jeff F Ghosh, Partho F31AI061840/AI/NIAID NIH HHS/United States F32AI49695/AI/NIAID NIH HHS/United States T32GM008326/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, P.H.S. United States Nature structural \& molecular biology Nat Struct Mol Biol. 2005 Oct;12(10):886-92. Epub 2005 Sep 18.}, pages = {886-92}, abstract = {Only few instances are known of protein folds that tolerate massive sequence variation for the sake of binding diversity. The most extensively characterized is the immunoglobulin fold. We now add to this the C-type lectin (CLec) fold, as found in the major tropism determinant (Mtd), a retroelement-encoded receptor-binding protein of Bordetella bacteriophage. Variation in Mtd, with its approximately 10(13) possible sequences, enables phage adaptation to Bordetella spp. Mtd is an intertwined, pyramid-shaped trimer, with variable residues organized by its CLec fold into discrete receptor-binding sites. The CLec fold provides a highly static scaffold for combinatorial display of variable residues, probably reflecting a different evolutionary solution for balancing diversity against stability from that in the immunoglobulin fold. Mtd variants are biased toward the receptor pertactin, and there is evidence that the CLec fold is used broadly for sequence variation by related retroelements.}, keywords = {Amino Acid Sequence Bacterial Outer Membrane Proteins/*chemistry Bacteriophages/*metabolism Bordetella/*virology Evolution, Bordetella/*chemistry, C-Type/*chemistry Molecular Sequence Data Protein Conformation Protein Folding Viral Proteins/*chemistry/*genetics Virulence Factors, Molecular Genetic Variation Genome, Viral Lectins}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16170324}, author = {McMahon, S. A. and Miller, J. L. and Lawton, J. A. and Kerkow, D. E. and Hodes, A. and M. A. Marti-Renom and Doulatov, S. and Narayanan, E. and Sali, A. and Miller, J. F. and Ghosh, P.} } @article {15883372, title = {Detecting remotely related proteins by their interactions and sequence similarity}, journal = {Proc Natl Acad Sci U S A}, volume = {102}, number = {20}, year = {2005}, note = {Espadaler, Jordi Aragues, Ramon Eswar, Narayanan Marti-Renom, Marc A Querol, Enrique Aviles, Francesc X Sali, Andrej Oliva, Baldomero R01 GM54762/GM/NIGMS NIH HHS/United States Comparative Study Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, P.H.S. United States Proceedings of the National Academy of Sciences of the United States of America Proc Natl Acad Sci U S A. 2005 May 17;102(20):7151-6. Epub 2005 May 9.}, pages = {7151-6}, abstract = {The function of an uncharacterized protein is usually inferred either from its homology to, or its interactions with, characterized proteins. Here, we use both sequence similarity and protein interactions to identify relationships between remotely related protein sequences. We rely on the fact that homologous sequences share similar interactions, and, therefore, the set of interacting partners of the partners of a given protein is enriched by its homologs. The approach was bench-marked by assigning the fold and functional family to test sequences of known structure. Specifically, we relied on 1,434 proteins with known folds, as defined in the Structural Classification of Proteins (SCOP) database, and with known interacting partners, as defined in the Database of Interacting Proteins (DIP). For this subset, the specificity of fold assignment was increased from 54\% for position-specific iterative BLAST to 75\% for our approach, with a concomitant increase in sensitivity for a few percentage points. Similarly, the specificity of family assignment at the e-value threshold of 10(-8) was increased from 70\% to 87\%. The proposed method would be a useful tool for large-scale automated discovery of remote relationships between protein sequences, given its unique reliance on sequence similarity and protein-protein interactions.}, keywords = {Amino Acid, Computational Biology Databases, Molecular Protein Conformation Protein Folding Proteins/*genetics/*metabolism Proteomics/*methods *Sequence Homology, Protein *Evolution}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=15883372}, author = {Espadaler, J. and Aragues, R. and Eswar, N. and M. A. Marti-Renom and Querol, E. and Aviles, F. X. and Sali, A. and Oliva, B.} } @article {15044736, title = {Alignment of protein sequences by their profiles}, journal = {Protein Sci}, volume = {13}, number = {4}, year = {2004}, note = {Marti-Renom, Marc A Madhusudhan, M S Sali, Andrej P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, P.H.S. United States Protein science : a publication of the Protein Society Protein Sci. 2004 Apr;13(4):1071-87.}, pages = {1071-87}, abstract = {The accuracy of an alignment between two protein sequences can be improved by including other detectably related sequences in the comparison. We optimize and benchmark such an approach that relies on aligning two multiple sequence alignments, each one including one of the two protein sequences. Thirteen different protocols for creating and comparing profiles corresponding to the multiple sequence alignments are implemented in the SALIGN command of MODELLER. A test set of 200 pairwise, structure-based alignments with sequence identities below 40\% is used to benchmark the 13 protocols as well as a number of previously described sequence alignment methods, including heuristic pairwise sequence alignment by BLAST, pairwise sequence alignment by global dynamic programming with an affine gap penalty function by the ALIGN command of MODELLER, sequence-profile alignment by PSI-BLAST, Hidden Markov Model methods implemented in SAM and LOBSTER, pairwise sequence alignment relying on predicted local structure by SEA, and multiple sequence alignment by CLUSTALW and COMPASS. The alignment accuracies of the best new protocols were significantly better than those of the other tested methods. For example, the fraction of the correctly aligned residues relative to the structure-based alignment by the best protocol is 56\%, which can be compared with the accuracies of 26\%, 42\%, 43\%, 48\%, 50\%, 49\%, 43\%, and 43\% for the other methods, respectively. The new method is currently applied to large-scale comparative protein structure modeling of all known sequences.}, keywords = {*Algorithms Amino Acid Sequence Computational Biology Databases, Protein Markov Chains Molecular Sequence Data *Protein Folding Protein Structure, Tertiary Proteins/*chemistry *Sequence Alignment Sequence Homology *Software}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=15044736}, author = {M. A. Marti-Renom and Madhusudhan, M. S. and Sali, A.} } @article {14681398, title = {MODBASE, a database of annotated comparative protein structure models, and associated resources}, journal = {Nucleic Acids Res}, volume = {32}, number = {Database issue}, year = {2004}, note = {Pieper, Ursula Eswar, Narayanan Braberg, Hannes Madhusudhan, M S Davis, Fred P Stuart, Ashley C Mirkovic, Nebojsa Rossi, Andrea Marti-Renom, Marc A Fiser, Andras Webb, Ben Greenblatt, Daniel Huang, Conrad C Ferrin, Thomas E Sali, Andrej P41 RR01081/RR/NCRR NIH HHS/United States P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM 54762/GM/NIGMS NIH HHS/United States R33 CA84699/CA/NCI NIH HHS/United States Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, P.H.S. England Nucleic acids research Nucleic Acids Res. 2004 Jan 1;32(Database issue):D217-22.}, pages = {D217-22}, abstract = {MODBASE (http://salilab.org/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on the MODELLER package for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE uses the MySQL relational database management system for flexible querying and CHIMERA for viewing the sequences and structures (http://www.cgl.ucsf.edu/chimera/). MODBASE is updated regularly to reflect the growth in protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different data sets. The largest data set contains 1,26,629 models for domains in 659,495 out of 1,182,126 unique protein sequences in the complete Swiss-Prot/TrEMBL database (August 25, 2003); only models based on alignments with significant similarity scores and models assessed to have the correct fold despite insignificant alignments are included. Another model data set supports target selection and structure-based annotation by the New York Structural Genomics Research Consortium; e.g. the 53 new structures produced by the consortium allowed us to characterize structurally 24,113 sequences. MODBASE also contains binding site predictions for small ligands and a set of predicted interactions between pairs of modeled sequences from the same genome. Our other resources associated with MODBASE include a comprehensive database of multiple protein structure alignments (DBALI, http://salilab.org/dbali) as well as web servers for automated comparative modeling with MODPIPE (MODWEB, http://salilab. org/modweb), modeling of loops in protein structures (MODLOOP, http://salilab.org/modloop) and predicting functional consequences of single nucleotide polymorphisms (SNPWEB, http://salilab. org/snpweb).}, keywords = {Amino Acid Sequence Animals Binding Sites *Computational Biology *Databases, Molecular Molecular Sequence Data Polymorphism, Protein Genomics Humans Internet Ligands Models, Single Nucleotide Protein Binding Protein Conformation Proteins/*chemistry/genetics Sequence Alignment Software User-Computer Interface}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=14681398}, author = {Pieper, U. and Eswar, N. and Braberg, H. and Madhusudhan, M. S. and Davis, F. P. and Stuart, A. C. and Mirkovic, N. and Rossi, A. and M. A. Marti-Renom and Fiser, A. and Webb, B. and Greenblatt, D. and Huang, C. C. and Ferrin, T. E. and Sali, A.} } @article {15172985, title = {Structure-based assessment of missense mutations in human BRCA1: implications for breast and ovarian cancer predisposition}, journal = {Cancer Res}, volume = {64}, number = {11}, year = {2004}, note = {Mirkovic, Nebojsa Marti-Renom, Marc A Weber, Barbara L Sali, Andrej Monteiro, Alvaro N A CA92309/CA/NCI NIH HHS/United States GM54762/GM/NIGMS NIH HHS/United States GM61390/GM/NIGMS NIH HHS/United States Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, Non-P.H.S. Research Support, U.S. Gov{\textquoteright}t, P.H.S. United States Cancer research Cancer Res. 2004 Jun 1;64(11):3790-7.}, pages = {3790-7}, abstract = {The BRCA1 gene from individuals at risk of breast and ovarian cancers can be screened for the presence of mutations. However, the cancer association of most alleles carrying missense mutations is unknown, thus creating significant problems for genetic counseling. To increase our ability to identify cancer-associated mutations in BRCA1, we set out to use the principles of protein three-dimensional structure as well as the correlation between the cancer-associated mutations and those that abolish transcriptional activation. Thirty-one of 37 missense mutations of known impact on the transcriptional activation function of BRCA1 are readily rationalized in structural terms. Loss-of-function mutations involve nonconservative changes in the core of the BRCA1 C-terminus (BRCT) fold or are localized in a groove that presumably forms a binding site involved in the transcriptional activation by BRCA1; mutations that do not abolish transcriptional activation are either conservative changes in the core or are on the surface outside of the putative binding site. Next, structure-based rules for predicting functional consequences of a given missense mutation were applied to 57 germ-line BRCA1 variants of unknown cancer association. Such a structure-based approach may be helpful in an integrated effort to identify mutations that predispose individuals to cancer.}, keywords = {BRCA1 Genetic Predisposition to Disease Humans *Mutation, BRCA1 Protein/*chemistry/genetics Breast Neoplasms/*genetics Female *Genes, Missense Ovarian Neoplasms/*genetics Pedigree Protein Conformation Structure-Activity Relationship Transcriptional Activation}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=15172985}, author = {Mirkovic, N. and M. A. Marti-Renom and Weber, B. L. and Sali, A. and Monteiro, A. N.} } @article {12824315, title = {EVA: Evaluation of protein structure prediction servers}, journal = {Nucleic Acids Res}, volume = {31}, number = {13}, year = {2003}, note = {Koh, Ingrid Y Y Eyrich, Volker A Marti-Renom, Marc A Przybylski, Dariusz Madhusudhan, Mallur S Eswar, Narayanan Grana, Osvaldo Pazos, Florencio Valencia, Alfonso Sali, Andrej Rost, Burkhard 1-P50-GM62413-01/GM/NIGMS NIH HHS/United States 5-P20-LM7276/LM/NLM NIH HHS/United States P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States R01-GM63029-01/GM/NIGMS NIH HHS/United States Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, Non-P.H.S. Research Support, U.S. Gov{\textquoteright}t, P.H.S. England Nucleic acids research Nucleic Acids Res. 2003 Jul 1;31(13):3311-5.}, pages = {3311-5}, abstract = {EVA (http://cubic.bioc.columbia.edu/eva/) is a web server for evaluation of the accuracy of automated protein structure prediction methods. The evaluation is updated automatically each week, to cope with the large number of existing prediction servers and the constant changes in the prediction methods. EVA currently assesses servers for secondary structure prediction, contact prediction, comparative protein structure modelling and threading/fold recognition. Every day, sequences of newly available protein structures in the Protein Data Bank (PDB) are sent to the servers and their predictions are collected. The predictions are then compared to the experimental structures once a week; the results are published on the EVA web pages. Over time, EVA has accumulated prediction results for a large number of proteins, ranging from hundreds to thousands, depending on the prediction method. This large sample assures that methods are compared reliably. As a result, EVA provides useful information to developers as well as users of prediction methods.}, keywords = {Automation Databases, Protein, Protein Internet *Protein Conformation Protein Folding Protein Structure, Protein Structural Homology, Secondary Proteins/chemistry Reproducibility of Results *Sequence Analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12824315}, author = {Koh, I. Y. and Eyrich, V. A. and M. A. Marti-Renom and Przybylski, D. and Madhusudhan, M. S. and Eswar, N. and Grana, O. and Pazos, F. and Valencia, A. and Sali, A. and Rost, B.} } @article {12499313, title = {ModView, visualization of multiple protein sequences and structures}, journal = {Bioinformatics}, volume = {19}, number = {1}, year = {2003}, note = {Ilyin, Valentin A Pieper, Ursula Stuart, Ashley C Marti-Renom, Marc A McMahan, Linda Sali, Andrej P50-GM62529/GM/NIGMS NIH HHS/United States Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, P.H.S. England Bioinformatics (Oxford, England) Bioinformatics. 2003 Jan;19(1):165-6.}, pages = {165-6}, abstract = {SUMMARY: We describe ModView, a web application for visualization of multiple protein sequences and structures. ModView integrates a multiple structure viewer, a multiple sequence alignment editor, and a database querying engine. It is possible to interactively manipulate hundreds of proteins, to visualize conservative and variable residues, active and binding sites, fragments, and domains in protein families, as well as to display large macromolecular complexes such as ribosomes or viruses. As a Netscape plug-in, ModView can be included in HTML pages along with text and figures, which makes it useful for teaching and presentations. ModView is also suitable as a graphical interface to various databases because it can be controlled through JavaScript commands and called from CGI scripts. AVAILABILITY: ModView is available at http://guitar.rockefeller.edu/modview.}, keywords = {*Database Management Systems Documentation/methods Imaging, Protein/*methods *User-Computer Interface, Three-Dimensional/methods Protein Conformation Proteins/*chemistry/genetics Sequence Alignment/*methods Sequence Analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12499313}, author = {Ilyin, V. A. and Pieper, U. and Stuart, A. C. and M. A. Marti-Renom and McMahan, L. and Sali, A.} } @article {12824331, title = {Tools for comparative protein structure modeling and analysis}, journal = {Nucleic Acids Res}, volume = {31}, number = {13}, year = {2003}, note = {Eswar, Narayanan John, Bino Mirkovic, Nebojsa Fiser, Andras Ilyin, Valentin A Pieper, Ursula Stuart, Ashley C Marti-Renom, Marc A Madhusudhan, M S Yerkovich, Bozidar Sali, Andrej P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM 54762/GM/NIGMS NIH HHS/United States R33 CA84699/CA/NCI NIH HHS/United States Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, P.H.S. England Nucleic acids research Nucleic Acids Res. 2003 Jul 1;31(13):3375-80.}, pages = {3375-80}, abstract = {The following resources for comparative protein structure modeling and analysis are described (http://salilab.org): MODELLER, a program for comparative modeling by satisfaction of spatial restraints; MODWEB, a web server for automated comparative modeling that relies on PSI-BLAST, IMPALA and MODELLER; MODLOOP, a web server for automated loop modeling that relies on MODELLER; MOULDER, a CPU intensive protocol of MODWEB for building comparative models based on distant known structures; MODBASE, a comprehensive database of annotated comparative models for all sequences detectably related to a known structure; MODVIEW, a Netscape plugin for Linux that integrates viewing of multiple sequences and structures; and SNPWEB, a web server for structure-based prediction of the functional impact of a single amino acid substitution.}, keywords = {Amino Acid *Software *Structural Homology, Internet Models, Molecular Protein Folding Proteins/chemistry Reproducibility of Results Sequence Alignment Sequence Homology, Protein Systems Integration}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12824331}, author = {Eswar, N. and John, B. and Mirkovic, N. and Fiser, A. and Ilyin, V. A. and Pieper, U. and Stuart, A. C. and M. A. Marti-Renom and Madhusudhan, M. S. and Yerkovich, B. and Sali, A.} } @article {12005441, title = {Reliability of assessment of protein structure prediction methods}, journal = {Structure}, volume = {10}, number = {3}, year = {2002}, note = {

Marti-Renom, Marc A Madhusudhan, M S Fiser, Andras Rost, Burkhard Sali, Andrej GM 54762/GM/NIGMS NIH HHS/United States GM62413/GM/NIGMS NIH HHS/United States Comparative Study Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, P.H.S. United States Structure (London, England : 1993) Structure. 2002 Mar;10(3):435-40.

}, pages = {435-40}, abstract = {

The reliability of ranking of protein structure modeling methods is assessed. The assessment is based on the parametric Student{\textquoteright}s t test and the nonparametric Wilcox signed rank test of statistical significance of the difference between paired samples. The approach is applied to the ranking of the comparative modeling methods tested at the fourth meeting on Critical Assessment of Techniques for Protein Structure Prediction (CASP). It is shown that the 14 CASP4 test sequences may not be sufficient to reliably distinguish between the top eight methods, given the model quality differences and their standard deviations. We suggest that CASP needs to be supplemented by an assessment of protein structure prediction methods that is automated, continuous in time, based on several criteria applied to a large number of models, and with quantitative statistical reliability assigned to each characterization.

}, keywords = {*Computer Simulation Humans *Models, Molecular *Protein Conformation Proteins/*chemistry Reproducibility of Results}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12005441}, author = {M. A. Marti-Renom and Madhusudhan, M. S. and Fiser, A. and Rost, B. and Sali, A.} } @article {12471146, title = {Use of single point mutations in domain I of beta 2-glycoprotein I to determine fine antigenic specificity of antiphospholipid autoantibodies}, journal = {J Immunol}, volume = {169}, number = {12}, year = {2002}, note = {Iverson, G Michael Reddel, Stephen Victoria, Edward J Cockerill, Keith A Wang, Ying-Xia Marti-Renom, Marc A Sali, Andrej Marquis, David M Krilis, Steven A Linnik, Matthew D GM54762/GM/NIGMS NIH HHS/United States Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, P.H.S. United States Journal of immunology (Baltimore, Md. : 1950) J Immunol. 2002 Dec 15;169(12):7097-103.}, pages = {7097-103}, abstract = {Autoantibodies against beta(2)-glycoprotein I (beta(2)GPI) appear to be a critical feature of the antiphospholipid syndrome (APS). As determined using domain deletion mutants, human autoantibodies bind to the first of five domains present in beta(2)GPI. In this study the fine detail of the domain I epitope has been examined using 10 selected mutants of whole beta(2)GPI containing single point mutations in the first domain. The binding to beta(2)GPI was significantly affected by a number of single point mutations in domain I, particularly by mutations in the region of aa 40-43. Molecular modeling predicted these mutations to affect the surface shape and electrostatic charge of a facet of domain I. Mutation K19E also had an effect, albeit one less severe and involving fewer patients. Similar results were obtained in two different laboratories using affinity-purified anti-beta(2)GPI in a competitive inhibition ELISA and with whole serum in a direct binding ELISA. This study confirms that anti-beta(2)GPI autoantibodies bind to domain I, and that the charged surface patch defined by residues 40-43 contributes to a dominant target epitope.}, keywords = {Amino Acid Substitution/genetics Antibodies, Antibody/genetics Binding, Antiphospholipid/blood/*metabolism Antibodies, Competitive/genetics/immunology Enzyme-Linked Immunosorbent Assay/methods Epitopes/analysis/*immunology/metabolism Glycine/genetics Glycoproteins/biosynthesis/*genetics/*immunology/isolation \& purification/metabolism Humans Models, Molecular Peptide Fragments/genetics/immunology/isolation \& purification/metabolism *Point Mutation Protein Structure, Monoclonal/blood/metabolism Antiphospholipid Syndrome/immunology Arginine/genetics *Binding Sites, Tertiary/genetics Recombinant Proteins/biosynthesis/immunology/isolation \& purification/metabolism Static Electricity beta 2-Glycoprotein I}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12471146}, author = {Iverson, G. M. and Reddel, S. and Victoria, E. J. and Cockerill, K. A. and Wang, Y. X. and M. A. Marti-Renom and Sali, A. and Marquis, D. M. and Krilis, S. A. and Linnik, M. D.} } @article {11524379, title = {DBAli: a database of protein structure alignments}, journal = {Bioinformatics}, volume = {17}, number = {8}, year = {2001}, note = {Marti-Renom, M A Ilyin, V A Sali, A Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, P.H.S. England Bioinformatics (Oxford, England) Bioinformatics. 2001 Aug;17(8):746-7.}, pages = {746-7}, abstract = {SUMMARY: The DBAli database includes approximately 35000 alignments of pairs of protein structures from SCOP (Lo Conte et al., Nucleic Acids Res., 28, 257-259, 2000) and CE (Shindyalov and Bourne, Protein Eng., 11, 739-747, 1998). DBAli is linked to several resources, including Compare3D (Shindyalov and Bourne, http://www.sdsc.edu/pb/software.htm, 1999) and ModView (Ilyin and Sali, http://guitar.rockefeller.edu/ModView/, 2001) for visualizing sequence alignments and structure superpositions. A flexible search of DBAli by protein sequence and structure properties allows construction of subsets of alignments suitable for a number of applications, such as benchmarking of sequence-sequence and sequence-structure alignment methods under a variety of conditions. AVAILABILITY: http://guitar.rockefeller.edu/DBAli/}, keywords = {Computational Biology *Databases, Protein Proteins/*chemistry/*genetics Sequence Alignment/*statistics \& numerical data Software Software Design}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=11524379}, author = {M. A. Marti-Renom and Ilyin, V. A. and Sali, A.} } @article {11751240, title = {EVA: continuous automatic evaluation of protein structure prediction servers}, journal = {Bioinformatics}, volume = {17}, number = {12}, year = {2001}, note = {Eyrich, V A Marti-Renom, M A Przybylski, D Madhusudhan, M S Fiser, A Pazos, F Valencia, A Sali, A Rost, B England Bioinformatics (Oxford, England) Bioinformatics. 2001 Dec;17(12):1242-3.}, pages = {1242-3}, abstract = {Evaluation of protein structure prediction methods is difficult and time-consuming. Here, we describe EVA, a web server for assessing protein structure prediction methods, in an automated, continuous and large-scale fashion. Currently, EVA evaluates the performance of a variety of prediction methods available through the internet. Every week, the sequences of the latest experimentally determined protein structures are sent to prediction servers, results are collected, performance is evaluated, and a summary is published on the web. EVA has so far collected data for more than 3000 protein chains. These results may provide valuable insight to both developers and users of prediction methods. AVAILABILITY: http://cubic.bioc.columbia.edu/eva. CONTACT: eva@cubic.bioc.columbia.edu}, keywords = {Automation Internet *Protein Conformation Proteins/*analysis *Software}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=11751240}, author = {Eyrich, V. A. and M. A. Marti-Renom and Przybylski, D. and Madhusudhan, M. S. and Fiser, A. and Pazos, F. and Valencia, A. and Sali, A. and Rost, B.} }