@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 {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 {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.}
}
