Literature DB >> 19827144

Q-Dock(LHM): Low-resolution refinement for ligand comparative modeling.

Michal Brylinski1, Jeffrey Skolnick.   

Abstract

The success of ligand docking calculations typically depends on the quality of the receptor structure. Given improvements in protein structure prediction approaches, approximate protein models now can be routinely obtained for the majority of gene products in a given proteome. Structure-based virtual screening of large combinatorial libraries of lead candidates against theoretically modeled receptor structures requires fast and reliable docking techniques capable of dealing with structural inaccuracies in protein models. Here, we present Q-Dock(LHM), a method for low-resolution refinement of binding poses provided by FINDSITE(LHM), a ligand homology modeling approach. We compare its performance to that of classical ligand docking approaches in ligand docking against a representative set of experimental (both holo and apo) as well as theoretically modeled receptor structures. Docking benchmarks reveal that unlike all-atom docking, Q-Dock(LHM) exhibits the desired tolerance to the receptor's structure deformation. Our results suggest that the use of an evolution-based approach to ligand homology modeling followed by fast low-resolution refinement is capable of achieving satisfactory performance in ligand-binding pose prediction with promising applicability to proteome-scale applications. 2009 Wiley Periodicals, Inc.

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Year:  2010        PMID: 19827144      PMCID: PMC2823986          DOI: 10.1002/jcc.21395

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  66 in total

1.  The Protein Data Bank.

Authors:  H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  Protein structure prediction and structural genomics.

Authors:  D Baker; A Sali
Journal:  Science       Date:  2001-10-05       Impact factor: 47.728

3.  Consideration of molecular weight during compound selection in virtual target-based database screening.

Authors:  Yongping Pan; Niu Huang; Sam Cho; Alexander D MacKerell
Journal:  J Chem Inf Comput Sci       Date:  2003 Jan-Feb

4.  Assessing scoring functions for protein-ligand interactions.

Authors:  Philippe Ferrara; Holger Gohlke; Daniel J Price; Gerhard Klebe; Charles L Brooks
Journal:  J Med Chem       Date:  2004-06-03       Impact factor: 7.446

5.  Scoring function for automated assessment of protein structure template quality.

Authors:  Yang Zhang; Jeffrey Skolnick
Journal:  Proteins       Date:  2004-12-01

6.  TASSER: an automated method for the prediction of protein tertiary structures in CASP6.

Authors:  Yang Zhang; Adrian K Arakaki; Jeffrey Skolnick
Journal:  Proteins       Date:  2005

Review 7.  Comparing protein-ligand docking programs is difficult.

Authors:  Jason C Cole; Christopher W Murray; J Willem M Nissink; Richard D Taylor; Robin Taylor
Journal:  Proteins       Date:  2005-08-15

8.  General and targeted statistical potentials for protein-ligand interactions.

Authors:  Wijnand T M Mooij; Marcel L Verdonk
Journal:  Proteins       Date:  2005-11-01

9.  Docking ligands into flexible and solvated macromolecules. 1. Development and validation of FITTED 1.0.

Authors:  Christopher R Corbeil; Pablo Englebienne; Nicolas Moitessier
Journal:  J Chem Inf Model       Date:  2007-02-17       Impact factor: 4.956

10.  A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation.

Authors:  Michal Brylinski; Jeffrey Skolnick
Journal:  Proc Natl Acad Sci U S A       Date:  2007-12-28       Impact factor: 11.205

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  18 in total

Review 1.  Low-resolution structural modeling of protein interactome.

Authors:  Ilya A Vakser
Journal:  Curr Opin Struct Biol       Date:  2013-01-05       Impact factor: 6.809

Review 2.  Are predicted protein structures of any value for binding site prediction and virtual ligand screening?

Authors:  Jeffrey Skolnick; Hongyi Zhou; Mu Gao
Journal:  Curr Opin Struct Biol       Date:  2013-02-14       Impact factor: 6.809

Review 3.  Structure-based systems biology for analyzing off-target binding.

Authors:  Lei Xie; Li Xie; Philip E Bourne
Journal:  Curr Opin Struct Biol       Date:  2011-02-01       Impact factor: 6.809

Review 4.  Implications of the small number of distinct ligand binding pockets in proteins for drug discovery, evolution and biochemical function.

Authors:  Jeffrey Skolnick; Mu Gao; Ambrish Roy; Bharath Srinivasan; Hongyi Zhou
Journal:  Bioorg Med Chem Lett       Date:  2015-02-03       Impact factor: 2.823

5.  Comprehensive structural and functional characterization of the human kinome by protein structure modeling and ligand virtual screening.

Authors:  Michal Brylinski; Jeffrey Skolnick
Journal:  J Chem Inf Model       Date:  2010-10-25       Impact factor: 4.956

6.  The utility of geometrical and chemical restraint information extracted from predicted ligand-binding sites in protein structure refinement.

Authors:  Michal Brylinski; Seung Yup Lee; Hongyi Zhou; Jeffrey Skolnick
Journal:  J Struct Biol       Date:  2010-09-17       Impact factor: 2.867

7.  FINDSITEcomb2.0: A New Approach for Virtual Ligand Screening of Proteins and Virtual Target Screening of Biomolecules.

Authors:  Hongyi Zhou; Hongnan Cao; Jeffrey Skolnick
Journal:  J Chem Inf Model       Date:  2018-10-16       Impact factor: 4.956

8.  3D structural analysis of proteins using electrostatic surfaces based on image segmentation.

Authors:  Dimitrios Vlachakis; Spyridon Champeris Tsaniras; Georgia Tsiliki; Vasileios Megalooikonomou; Sophia Kossida
Journal:  J Mol Biochem       Date:  2014-02-28

9.  Assessing the similarity of ligand binding conformations with the Contact Mode Score.

Authors:  Yun Ding; Ye Fang; Juana Moreno; J Ramanujam; Mark Jarrell; Michal Brylinski
Journal:  Comput Biol Chem       Date:  2016-09-06       Impact factor: 2.877

10.  FINDSITE(comb): a threading/structure-based, proteomic-scale virtual ligand screening approach.

Authors:  Hongyi Zhou; Jeffrey Skolnick
Journal:  J Chem Inf Model       Date:  2012-12-28       Impact factor: 4.956

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