Are predicted protein structures of any value for binding site prediction and virtual ligand screening?
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Jeffrey Skolnick | Mu Gao | Hongyi Zhou | J. Skolnick | Hongyi Zhou | M. Gao | Mu Gao
[1] Michal Brylinski,et al. Comparison of structure‐based and threading‐based approaches to protein functional annotation , 2010, Proteins.
[2] Philip E. Bourne,et al. SMAP-WS: a parallel web service for structural proteome-wide ligand-binding site comparison , 2010, Nucleic Acids Res..
[3] M. Ondrechen,et al. THEMATICS: A simple computational predictor of enzyme function from structure , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[4] R. Russell,et al. Protein complexes: structure prediction challenges for the 21st century. , 2005, Current opinion in structural biology.
[5] R. Kroemer. Structure-based drug design: docking and scoring. , 2007, Current protein & peptide science.
[6] Ruben Abagyan,et al. ICM—A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation , 1994, J. Comput. Chem..
[7] M Hendlich,et al. LIGSITE: automatic and efficient detection of potential small molecule-binding sites in proteins. , 1997, Journal of molecular graphics & modelling.
[8] Satoshi Niijima,et al. GLIDA: GPCR—ligand database for chemical genomics drug discovery—database and tools update , 2007, Nucleic Acids Res..
[9] J. Skolnick,et al. A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation , 2008, Proceedings of the National Academy of Sciences.
[10] Jeffrey Skolnick,et al. Template‐based protein structure modeling using TASSERVMT , 2012, Proteins.
[11] B. Shoichet,et al. Information decay in molecular docking screens against holo, apo, and modeled conformations of enzymes. , 2003, Journal of medicinal chemistry.
[12] J. J. Díaz-Mejía,et al. Network-based function prediction and interactomics: the case for metabolic enzymes. , 2011, Metabolic engineering.
[13] Ajay N. Jain. Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine. , 2003, Journal of medicinal chemistry.
[14] Shankaracharya,et al. Tools for predicting metal binding sites in protein: A Review , 2011 .
[15] Philip E. Bourne,et al. A Multidimensional Strategy to Detect Polypharmacological Targets in the Absence of Structural and Sequence Homology , 2010, PLoS Comput. Biol..
[16] Michal Brylinski,et al. FINDSITELHM: A Threading-Based Approach to Ligand Homology Modeling , 2009, PLoS Comput. Biol..
[17] Yongbo Hu,et al. Comparison of Several Molecular Docking Programs: Pose Prediction and Virtual Screening Accuracy , 2009, J. Chem. Inf. Model..
[18] Yang Zhang,et al. Recognizing protein-ligand binding sites by global structural alignment and local geometry refinement. , 2012, Structure.
[19] J. Skolnick,et al. Cross-reactivity virtual profiling of the human kinome by X-react(KIN): a chemical systems biology approach. , 2010, Molecular pharmaceutics.
[20] Jeffrey Skolnick,et al. Assessment of programs for ligand binding affinity prediction , 2008, J. Comput. Chem..
[21] Yang Zhang,et al. COFACTOR: an accurate comparative algorithm for structure-based protein function annotation , 2012, Nucleic Acids Res..
[22] I. Kuntz,et al. DOCK 6: combining techniques to model RNA-small molecule complexes. , 2009, RNA.
[23] David S Wishart,et al. DrugBank and its relevance to pharmacogenomics. , 2008, Pharmacogenomics.
[24] Yang Zhang,et al. BSP‐SLIM: A blind low‐resolution ligand‐protein docking approach using predicted protein structures , 2012, Proteins.
[25] Angela D. Wilkins,et al. Evolutionary trace for prediction and redesign of protein functional sites. , 2012, Methods in molecular biology.
[26] Krzysztof Fidelis,et al. CASP9 results compared to those of previous casp experiments , 2011, Proteins.
[27] Jeffrey Skolnick,et al. FINDSITE(X): a structure-based, small molecule virtual screening approach with application to all identified human GPCRs. , 2012, Molecular pharmaceutics.
[28] Motonori Ota,et al. PSCDB: a database for protein structural change upon ligand binding , 2011, Nucleic Acids Res..
[29] Lincoln Stein,et al. Reactome: a database of reactions, pathways and biological processes , 2010, Nucleic Acids Res..
[30] Richard A. Lewis,et al. Lessons in molecular recognition: the effects of ligand and protein flexibility on molecular docking accuracy. , 2004, Journal of medicinal chemistry.
[31] Ajay N. Jain. Surflex-Dock 2.1: Robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search , 2007, J. Comput. Aided Mol. Des..
[32] Michael J E Sternberg,et al. The proteome: structure, function and evolution , 2006, Philosophical Transactions of the Royal Society B: Biological Sciences.
[33] Ben M. Webb,et al. Comparative Protein Structure Modeling Using Modeller , 2006, Current protocols in bioinformatics.
[34] Angela D. Wilkins,et al. Evolution: a guide to perturb protein function and networks. , 2010, Current opinion in structural biology.
[35] Yu Li,et al. Identification of cavities on protein surface using multiple computational approaches for drug binding site prediction , 2011, Bioinform..
[36] Oliver Fiehn,et al. Extending Biochemical Databases by Metabolomic Surveys* , 2011, The Journal of Biological Chemistry.
[37] Yang Zhang,et al. Automated protein structure modeling in CASP9 by I‐TASSER pipeline combined with QUARK‐based ab initio folding and FG‐MD‐based structure refinement , 2011, Proteins.
[38] M. Schroeder,et al. LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation , 2006, BMC Structural Biology.
[39] Michal Brylinski,et al. Comprehensive Structural and Functional Characterization of the Human Kinome by Protein Structure Modeling and Ligand Virtual Screening , 2010, J. Chem. Inf. Model..
[40] Andrei L Osterman,et al. Ligand binding-induced conformational changes in riboflavin kinase: structural basis for the ordered mechanism. , 2003, Biochemistry.
[41] Markus Fischer,et al. MarkUs: a server to navigate sequence–structure–function space , 2011, Nucleic Acids Res..
[42] Michal Brylinski,et al. FINDSITE: a combined evolution/structure-based approach to protein function prediction , 2009, Briefings Bioinform..
[43] Wayne A Hendrickson,et al. What is 'current opinion' in structural biology? , 2011, Current opinion in structural biology.
[44] Arthur J. Olson,et al. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading , 2009, J. Comput. Chem..
[45] S. Erdin,et al. Evolutionary trace annotation of protein function in the structural proteome. , 2010, Journal of molecular biology.
[46] Thomas Lengauer,et al. Evaluation of the FLEXX incremental construction algorithm for protein–ligand docking , 1999, Proteins.
[47] A. Elcock. Prediction of functionally important residues based solely on the computed energetics of protein structure. , 2001, Journal of molecular biology.
[48] J. Irwin,et al. Benchmarking sets for molecular docking. , 2006, Journal of medicinal chemistry.
[49] M. Sternberg,et al. Automated structure-based prediction of functional sites in proteins: applications to assessing the validity of inheriting protein function from homology in genome annotation and to protein docking. , 2001, Journal of molecular biology.
[50] Michael J. E. Sternberg,et al. 3DLigandSite: predicting ligand-binding sites using similar structures , 2010, Nucleic Acids Res..
[51] Lei Xie,et al. Structure-based systems biology for analyzing off-target binding. , 2011, Current opinion in structural biology.
[52] J. Irwin,et al. ZINC ? A Free Database of Commercially Available Compounds for Virtual Screening. , 2005 .
[53] Matthew P. Repasky,et al. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. , 2004, Journal of medicinal chemistry.
[54] Ajay N. Jain,et al. Parameter estimation for scoring protein-ligand interactions using negative training data. , 2006, Journal of medicinal chemistry.
[55] David S. Wishart,et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets , 2007, Nucleic Acids Res..
[56] J. Skolnick,et al. Automated structure prediction of weakly homologous proteins on a genomic scale. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[57] M. L. Connolly. Analytical molecular surface calculation , 1983 .
[58] Michal Brylinski,et al. Q‐DockLHM: Low‐resolution refinement for ligand comparative modeling , 2009, J. Comput. Chem..
[59] Neil Swainston,et al. Further developments towards a genome-scale metabolic model of yeast , 2010, BMC Systems Biology.
[60] M. Sternberg,et al. Automated prediction of protein function and detection of functional sites from structure. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[61] Hongyi Zhou,et al. FINDSITEcomb: A Threading/Structure-Based, Proteomic-Scale Virtual Ligand Screening Approach , 2013, J. Chem. Inf. Model..
[62] Jens Meiler,et al. ROSETTALIGAND: Protein–small molecule docking with full side‐chain flexibility , 2006, Proteins.
[63] J. Thornton,et al. A method for localizing ligand binding pockets in protein structures , 2005, Proteins.
[64] Anna Vulpetti,et al. Assessment of Docking Poses: Interactions-Based Accuracy Classification (IBAC) versus Crystal Structure Deviations. , 2004 .
[65] J. Skolnick,et al. What is the relationship between the global structures of apo and holo proteins? , 2007, Proteins.
[66] Michal Brylinski,et al. The utility of geometrical and chemical restraint information extracted from predicted ligand-binding sites in protein structure refinement. , 2011, Journal of structural biology.
[67] J. Skolnick,et al. FINDSITE‐metal: Integrating evolutionary information and machine learning for structure‐based metal‐binding site prediction at the proteome level , 2011, Proteins.
[68] Michal Brylinski,et al. Q‐Dock: Low‐resolution flexible ligand docking with pocket‐specific threading restraints , 2008, J. Comput. Chem..