Literature DB >> 10584214

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

C W Murray1, C A Baxter, A D Frenkel.   

Abstract

This paper describes the application of PRO_LEADS to the flexible docking of ligands into crystallographically derived enzyme structures that are assumed to be rigid. PRO_LEADS uses a Tabu search methodology to perform the flexible search and an empirically derived estimate of the binding affinity to drive the docking process. The paper tests the extent to which the assumption of a rigid enzyme compromises the accuracy of the results. All-pairs docking experiments are performed for three enzymes (thrombin, thermolysin and influenza virus neuraminidase) based on six or more ligand-enzyme crystal structures for each enzyme. In 76% of the cases, PRO_LEADS can successfully identify the correct ligand conformation as the lowest energy configuration when the enzyme structure is derived from that ligand's crystal structure, but the methodology only docks 49% of the cases successfully when the ligand is docked against enzyme crystal structures derived from other ligands. Small movements in the enzyme structure lead to an under-prediction in the energy of the correct binding mode by up to 14 kJ/mol and in some cases this under-prediction can lead to the native mode not being recognised as the lowest energy solution. The type of movements responsible for mis-docking are: the movement of sidechains as a result of changes in C alpha position; the movement of sidechains without changes in C alpha position; the movement of flexible portions of main chains to facilitate the formation of hydrogen bonds; and the movement of metal atoms bound to the enzyme active site. The work illustrates that the assumption of a rigid active site can lead to errors in identification of the correct binding mode and the assessment of binding affinity, even for enzymes which show relatively small shift in atomic positions from one ligand to the next. A good docking code, such as PRO_LEADS, can usually dock successfully if there is induced fit in relatively rigid enzymes but there remains the need to develop improved strategies for dealing with enzyme flexibility. The work implies that treatments of enzyme flexibility which focus only on sidechain rotations will not deal with the critical shifts responsible for mis-docking of ligands in thrombin, thermolysin and neuraminidase. The paper demonstrates the utility of all pairs docking experiments as a method of assessing the effectiveness of docking methodologies in dealing with enzyme flexibility.

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Year:  1999        PMID: 10584214     DOI: 10.1023/a:1008015827877

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  26 in total

Review 1.  Ligand-protein docking and rational drug design.

Authors:  T P Lybrand
Journal:  Curr Opin Struct Biol       Date:  1995-04       Impact factor: 6.809

2.  Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes.

Authors:  M D Eldridge; C W Murray; T R Auton; G V Paolini; R P Mee
Journal:  J Comput Aided Mol Des       Date:  1997-09       Impact factor: 3.686

3.  Distributed automated docking of flexible ligands to proteins: parallel applications of AutoDock 2.4.

Authors:  G M Morris; D S Goodsell; R Huey; A J Olson
Journal:  J Comput Aided Mol Des       Date:  1996-08       Impact factor: 3.686

4.  Hammerhead: fast, fully automated docking of flexible ligands to protein binding sites.

Authors:  W Welch; J Ruppert; A N Jain
Journal:  Chem Biol       Date:  1996-06

5.  A comparison of heuristic search algorithms for molecular docking.

Authors:  D R Westhead; D E Clark; C W Murray
Journal:  J Comput Aided Mol Des       Date:  1997-05       Impact factor: 3.686

6.  Development and validation of a genetic algorithm for flexible docking.

Authors:  G Jones; P Willett; R C Glen; A R Leach; R Taylor
Journal:  J Mol Biol       Date:  1997-04-04       Impact factor: 5.469

7.  Flexible ligand docking using a genetic algorithm.

Authors:  C M Oshiro; I D Kuntz; J S Dixon
Journal:  J Comput Aided Mol Des       Date:  1995-04       Impact factor: 3.686

8.  Ligand docking to proteins with discrete side-chain flexibility.

Authors:  A R Leach
Journal:  J Mol Biol       Date:  1994-01-07       Impact factor: 5.469

9.  Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation.

Authors:  G Jones; P Willett; R C Glen
Journal:  J Mol Biol       Date:  1995-01-06       Impact factor: 5.469

10.  The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure.

Authors:  H J Böhm
Journal:  J Comput Aided Mol Des       Date:  1994-06       Impact factor: 3.686

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  35 in total

Review 1.  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

2.  Peroxisome proliferator-activated receptors target family landscape: a chemometrical approach to ligand selectivity based on protein binding site analysis.

Authors:  Bernard Pirard
Journal:  J Comput Aided Mol Des       Date:  2003-11       Impact factor: 3.686

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Authors:  Alvaro Cortés-Cabrera; Federico Gago; Antonio Morreale
Journal:  J Comput Aided Mol Des       Date:  2012-03-07       Impact factor: 3.686

4.  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

5.  Biased retrieval of chemical series in receptor-based virtual screening.

Authors:  Natasja Brooijmans; Jason B Cross; Christine Humblet
Journal:  J Comput Aided Mol Des       Date:  2010-10-30       Impact factor: 3.686

Review 6.  Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.

Authors:  N Moitessier; P Englebienne; D Lee; J Lawandi; C R Corbeil
Journal:  Br J Pharmacol       Date:  2007-11-26       Impact factor: 8.739

Review 7.  Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection--what can we learn from earlier mistakes?

Authors:  Johannes Kirchmair; Patrick Markt; Simona Distinto; Gerhard Wolber; Thierry Langer
Journal:  J Comput Aided Mol Des       Date:  2008-01-15       Impact factor: 3.686

8.  Assessment of programs for ligand binding affinity prediction.

Authors:  Ryangguk Kim; Jeffrey Skolnick
Journal:  J Comput Chem       Date:  2008-06       Impact factor: 3.376

9.  VSDMIP: virtual screening data management on an integrated platform.

Authors:  Rubén Gil-Redondo; Jorge Estrada; Antonio Morreale; Fernando Herranz; Javier Sancho; Angel R Ortiz
Journal:  J Comput Aided Mol Des       Date:  2008-10-22       Impact factor: 3.686

10.  Drotaverine Inhibitor of PDE4: Reverses the Streptozotocin Induced Alzheimer's Disease in Mice.

Authors:  Samra Nazir; Fareeha Anwar; Uzma Saleem; Bashir Ahmad; Zohaib Raza; Maham Sanawar; Artta Ur Rehman; Tariq Ismail
Journal:  Neurochem Res       Date:  2021-04-20       Impact factor: 3.996

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