Literature DB >> 8289255

Ligand docking to proteins with discrete side-chain flexibility.

A R Leach1.   

Abstract

An algorithm is described that explores the conformational degrees of freedom of the amino acid side-chains and of the ligand when docking a putative ligand into a receptor site. For a given orientation of the ligand relative to the protein, the method can find the lowest energy combination of amino acid side-chains and ligand conformations as well as all other combinations in order of increasing energy within a specified energy cutoff. The amino acid side-chains and the ligand are restricted to discrete low-energy conformations, determined for the former by analysing high-resolution protein structures and in the latter case from a conformational analysis. Coupled to an algorithm for exploring the six degrees of orientational freedom of the ligand with respect to the receptor, the method can be used to perform conformationally flexible ligand docking. A combination of two search methods is employed to explore the conformational degrees of freedom: Dead End Elimination and the A* algorithm. When no ligand is present the approach can be used to predict the lowest energy combinations of side-chain conformations for a given protein backbone structure. The approach is employed to illustrate how such a procedure can be used to estimate the conformational entropy change that accompanies the formation of an intermolecular complex between a protein and a ligand and to demonstrate that the protein's conformational entropy may in some cases increase on binding the ligand. This is due to a modification of the protein's energy hypersurface that makes more conformational states accessible. Our results highlight the need for appropriate methods to estimate the strength of binding.

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Year:  1994        PMID: 8289255     DOI: 10.1016/s0022-2836(05)80038-5

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  59 in total

1.  The sensitivity of the results of molecular docking to induced fit effects: application to thrombin, thermolysin and neuraminidase.

Authors:  C W Murray; C A Baxter; A D Frenkel
Journal:  J Comput Aided Mol Des       Date:  1999-11       Impact factor: 3.686

2.  Deciphering common failures in molecular docking of ligand-protein complexes.

Authors:  G M Verkhivker; D Bouzida; D K Gehlhaar; P A Rejto; S Arthurs; A B Colson; S T Freer; V Larson; B A Luty; T Marrone; P W Rose
Journal:  J Comput Aided Mol Des       Date:  2000-11       Impact factor: 3.686

3.  DOCK 4.0: search strategies for automated molecular docking of flexible molecule databases.

Authors:  T J Ewing; S Makino; A G Skillman; I D Kuntz
Journal:  J Comput Aided Mol Des       Date:  2001-05       Impact factor: 3.686

Review 4.  A review of protein-small molecule docking methods.

Authors:  R D Taylor; P J Jewsbury; J W Essex
Journal:  J Comput Aided Mol Des       Date:  2002-03       Impact factor: 3.686

5.  GEM: a Gaussian Evolutionary Method for predicting protein side-chain conformations.

Authors:  Jinn-Moon Yang; Chi-Hung Tsai; Ming-Jing Hwang; Huai-Kuang Tsai; Jenn-Kang Hwang; Cheng-Yan Kao
Journal:  Protein Sci       Date:  2002-08       Impact factor: 6.725

6.  Development and testing of a de novo drug-design algorithm.

Authors:  Eric Pellegrini; Martin J Field
Journal:  J Comput Aided Mol Des       Date:  2003-10       Impact factor: 3.686

7.  Comparative study of several algorithms for flexible ligand docking.

Authors:  Badry D Bursulaya; Maxim Totrov; Ruben Abagyan; Charles L Brooks
Journal:  J Comput Aided Mol Des       Date:  2003-11       Impact factor: 3.686

8.  Soft docking and multiple receptor conformations in virtual screening.

Authors:  Anna Maria Ferrari; Binqing Q Wei; Luca Costantino; Brian K Shoichet
Journal:  J Med Chem       Date:  2004-10-07       Impact factor: 7.446

9.  Chemical space sampling by different scoring functions and crystal structures.

Authors:  Natasja Brooijmans; Christine Humblet
Journal:  J Comput Aided Mol Des       Date:  2010-04-18       Impact factor: 3.686

10.  Molecular modelling prediction of ligand binding site flexibility.

Authors:  Ami Yi-Ching Yang; Per Källblad; Ricardo L Mancera
Journal:  J Comput Aided Mol Des       Date:  2004-04       Impact factor: 3.686

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