Literature DB >> 18034309

Protein-ligand docking with multiple flexible side chains.

Yong Zhao1, Michel F Sanner.   

Abstract

In this work, we validate and analyze the results of previously published cross docking experiments and classify failed dockings based on the conformational changes observed in the receptors. We show that a majority of failed experiments (i.e. 25 out of 33, involving four different receptors: cAPK, CDK2, Ricin and HIVp) are due to conformational changes in side chains near the active site. For these cases, we identify the side chains to be made flexible during docking calculation by superimposing receptors and analyzing steric overlap between various ligands and receptor side chains. We demonstrate that allowing these side chains to assume rotameric conformations enables the successful cross docking of 19 complexes (ligand all atom RMSD < 2.0 A) using our docking software FLIPDock. The number of side receptor side chains interacting with a ligand can vary according to the ligand's size and shape. Hence, when starting from a complex with a particular ligand one might have to extend the region of potential interacting side chains beyond the ones interacting with the known ligand. We discuss distance-based methods for selecting additional side chains in the neighborhood of the known active site. We show that while using the molecular surface to grow the neighborhood is more efficient than Euclidian-distance selection, the number of side chains selected by these methods often remains too large and additional methods for reducing their count are needed. Despite these difficulties, using geometric constraints obtained from the network of bonded and non-bonded interactions to rank residues and allowing the top ranked side chains to be flexible during docking makes 22 out of 25 complexes successful.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 18034309      PMCID: PMC4828239          DOI: 10.1007/s10822-007-9148-5

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


  14 in total

1.  Side-chain flexibility in proteins upon ligand binding.

Authors:  R Najmanovich; J Kuttner; V Sobolev; M Edelman
Journal:  Proteins       Date:  2000-05-15

2.  Efficient conformational sampling of local side-chain flexibility.

Authors:  Per Källblad; Philip M Dean
Journal:  J Mol Biol       Date:  2003-03-07       Impact factor: 5.469

3.  A component-based software environment for visualizing large macromolecular assemblies.

Authors:  Michel F Sanner
Journal:  Structure       Date:  2005-03       Impact factor: 5.006

4.  A semiempirical free energy force field with charge-based desolvation.

Authors:  Ruth Huey; Garrett M Morris; Arthur J Olson; David S Goodsell
Journal:  J Comput Chem       Date:  2007-04-30       Impact factor: 3.376

5.  Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking.

Authors:  Sheng-You Huang; Xiaoqin Zou
Journal:  Proteins       Date:  2007-02-01

6.  Hierarchical and multi-resolution representation of protein flexibility.

Authors:  Yong Zhao; Daniel Stoffler; Michel Sanner
Journal:  Bioinformatics       Date:  2006-09-18       Impact factor: 6.937

7.  FLIPDock: docking flexible ligands into flexible receptors.

Authors:  Yong Zhao; Michel F Sanner
Journal:  Proteins       Date:  2007-08-15

8.  Molecular recognition of cyclic urea HIV-1 protease inhibitors.

Authors:  P J Ala; R J DeLoskey; E E Huston; P K Jadhav; P Y Lam; C J Eyermann; C N Hodge; M C Schadt; F A Lewandowski; P C Weber; D D McCabe; J L Duke; C H Chang
Journal:  J Biol Chem       Date:  1998-05-15       Impact factor: 5.157

9.  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

10.  Ligand-induced conformational changes: improved predictions of ligand binding conformations and affinities.

Authors:  Thomas M Frimurer; Günther H Peters; Lars F Iversen; Henrik S Andersen; Niels Peter H Møller; Ole H Olsen
Journal:  Biophys J       Date:  2003-04       Impact factor: 4.033

View more
  12 in total

1.  BP-Dock: a flexible docking scheme for exploring protein-ligand interactions based on unbound structures.

Authors:  Ashini Bolia; Z Nevin Gerek; S Banu Ozkan
Journal:  J Chem Inf Model       Date:  2014-03-04       Impact factor: 4.956

2.  The measured and calculated affinity of methyl- and methoxy-substituted benzoquinones for the Q(A) site of bacterial reaction centers.

Authors:  Zhong Zheng; P Leslie Dutton; M R Gunner
Journal:  Proteins       Date:  2010-09

3.  Protein flexibility in virtual screening: the BACE-1 case study.

Authors:  Sandro Cosconati; Luciana Marinelli; Francesco Saverio Di Leva; Valeria La Pietra; Angela De Simone; Francesca Mancini; Vincenza Andrisano; Ettore Novellino; David S Goodsell; Arthur J Olson
Journal:  J Chem Inf Model       Date:  2012-10-08       Impact factor: 4.956

4.  AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility.

Authors:  Garrett M Morris; Ruth Huey; William Lindstrom; Michel F Sanner; Richard K Belew; David S Goodsell; Arthur J Olson
Journal:  J Comput Chem       Date:  2009-12       Impact factor: 3.376

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

Authors:  Michal Brylinski; Jeffrey Skolnick
Journal:  J Comput Chem       Date:  2010-04-15       Impact factor: 3.376

Review 6.  Protein flexibility in docking and surface mapping.

Authors:  Katrina W Lexa; Heather A Carlson
Journal:  Q Rev Biophys       Date:  2012-05-09       Impact factor: 5.318

7.  The AutoDock suite at 30.

Authors:  David S Goodsell; Michel F Sanner; Arthur J Olson; Stefano Forli
Journal:  Protein Sci       Date:  2020-09-12       Impact factor: 6.725

8.  Drug design for ever, from hype to hope.

Authors:  G Seddon; V Lounnas; R McGuire; T van den Bergh; R P Bywater; L Oliveira; G Vriend
Journal:  J Comput Aided Mol Des       Date:  2012-01-18       Impact factor: 3.686

9.  AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility.

Authors:  Pradeep Anand Ravindranath; Stefano Forli; David S Goodsell; Arthur J Olson; Michel F Sanner
Journal:  PLoS Comput Biol       Date:  2015-12-02       Impact factor: 4.475

10.  GNINA 1.0: molecular docking with deep learning.

Authors:  Andrew T McNutt; Paul Francoeur; Rishal Aggarwal; Tomohide Masuda; Rocco Meli; Matthew Ragoza; Jocelyn Sunseri; David Ryan Koes
Journal:  J Cheminform       Date:  2021-06-09       Impact factor: 5.514

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.