Literature DB >> 18302984

Flexible ligand docking to multiple receptor conformations: a practical alternative.

Maxim Totrov1, Ruben Abagyan.   

Abstract

State of the art docking algorithms predict an incorrect binding pose for about 50-70% of all ligands when only a single fixed receptor conformation is considered. In many more cases, lack of receptor flexibility results in meaningless ligand binding scores, even when the correct pose is obtained. Incorporating conformational rearrangements of the receptor binding pocket into predictions of both ligand binding pose and binding score is crucial for improving structure-based drug design and virtual ligand screening methodologies. However, direct modeling of protein binding site flexibility remains challenging because of the large conformational space that must be sampled, and difficulties remain in constructing a suitably accurate energy function. Here we show that using multiple fixed receptor conformations, either experimentally determined by crystallography or NMR, or computationally generated, is a practical shortcut that may improve docking calculations. In several cases, such an approach has led to experimentally validated predictions.

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Year:  2008        PMID: 18302984      PMCID: PMC2396190          DOI: 10.1016/j.sbi.2008.01.004

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  32 in total

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Journal:  J Med Chem       Date:  2003-07-03       Impact factor: 7.446

Review 3.  Conformational flexibility models for the receptor in structure based drug design.

Authors:  M L Teodoro; L E Kavraki
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4.  Modeling correlated main-chain motions in proteins for flexible molecular recognition.

Authors:  Maria I Zavodszky; Ming Lei; M F Thorpe; Anthony R Day; Leslie A Kuhn
Journal:  Proteins       Date:  2004-11-01

5.  Testing a flexible-receptor docking algorithm in a model binding site.

Authors:  Binqing Q Wei; Larry H Weaver; Anna M Ferrari; Brian W Matthews; Brian K Shoichet
Journal:  J Mol Biol       Date:  2004-04-09       Impact factor: 5.469

6.  Protein flexibility in ligand docking and virtual screening to protein kinases.

Authors:  Claudio N Cavasotto; Ruben A Abagyan
Journal:  J Mol Biol       Date:  2004-03-12       Impact factor: 5.469

7.  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

8.  A flexible approach to induced fit docking.

Authors:  Sander B Nabuurs; Markus Wagener; Jacob de Vlieg
Journal:  J Med Chem       Date:  2007-11-22       Impact factor: 7.446

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Journal:  Proteins       Date:  2007-08-15

Review 10.  Imatinib: a selective tyrosine kinase inhibitor.

Authors:  P W Manley; S W Cowan-Jacob; E Buchdunger; D Fabbro; G Fendrich; P Furet; T Meyer; J Zimmermann
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  149 in total

1.  Improved docking, screening and selectivity prediction for small molecule nuclear receptor modulators using conformational ensembles.

Authors:  So-Jung Park; Irina Kufareva; Ruben Abagyan
Journal:  J Comput Aided Mol Des       Date:  2010-05-09       Impact factor: 3.686

2.  Utilizing experimental data for reducing ensemble size in flexible-protein docking.

Authors:  Mengang Xu; Markus A Lill
Journal:  J Chem Inf Model       Date:  2011-12-19       Impact factor: 4.956

3.  Molecular mechanism of serotonin transporter inhibition elucidated by a new flexible docking protocol.

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Journal:  Eur J Med Chem       Date:  2011-10-20       Impact factor: 6.514

4.  Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge.

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Journal:  J Comput Aided Mol Des       Date:  2012-01-15       Impact factor: 3.686

Review 5.  Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approaches.

Authors:  Pierre Tuffery; Philippe Derreumaux
Journal:  J R Soc Interface       Date:  2011-10-12       Impact factor: 4.118

6.  Vaccinia virus virulence factor N1L is a novel promising target for antiviral therapeutic intervention.

Authors:  Anton V Cheltsov; Mika Aoyagi; Alexander Aleshin; Eric Chi-Wang Yu; Taylor Gilliland; Dayong Zhai; Andrey A Bobkov; John C Reed; Robert C Liddington; Ruben Abagyan
Journal:  J Med Chem       Date:  2010-05-27       Impact factor: 7.446

Review 7.  Virtual screening: an endless staircase?

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Journal:  Nat Rev Drug Discov       Date:  2010-04       Impact factor: 84.694

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Authors:  Elodie Laine; Christophe Goncalves; Johanna C Karst; Aurélien Lesnard; Sylvain Rault; Wei-Jen Tang; Thérèse E Malliavin; Daniel Ladant; Arnaud Blondel
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-07       Impact factor: 11.205

9.  Improved ligand-protein binding affinity predictions using multiple binding modes.

Authors:  Eva Stjernschantz; Chris Oostenbrink
Journal:  Biophys J       Date:  2010-06-02       Impact factor: 4.033

10.  Gating function of isoleucine-116 in TM-3 (position III:16/3.40) for the activity state of the CC-chemokine receptor 5 (CCR5).

Authors:  A Steen; A H Sparre-Ulrich; S Thiele; D Guo; T M Frimurer; M M Rosenkilde
Journal:  Br J Pharmacol       Date:  2014-03       Impact factor: 8.739

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