Literature DB >> 28983727

Binding pose and affinity prediction in the 2016 D3R Grand Challenge 2 using the Wilma-SIE method.

Hervé Hogues1, Traian Sulea1, Francis Gaudreault1, Christopher R Corbeil1, Enrico O Purisima2.   

Abstract

The Farnesoid X receptor (FXR) exhibits significant backbone movement in response to the binding of various ligands and can be a challenge for pose prediction algorithms. As part of the D3R Grand Challenge 2, we tested Wilma-SIE, a rigid-protein docking method, on a set of 36 FXR ligands for which the crystal structures had originally been blinded. These ligands covered several classes of compounds. To overcome the rigid protein limitations of the method, we used an ensemble of publicly available structures for FXR from the PDB. The use of the ensemble allowed Wilma-SIE to predict poses with average and median RMSDs of 2.3 and 1.4 Å, respectively. It was quite clear, however, that had we used a single structure for the receptor the success rate would have been much lower. The most successful predictions were obtained on chemical classes for which one or more crystal structures of the receptor bound to a molecule of the same class was available. In the absence of a crystal structure for the class, observing a consensus binding mode for the ligands of the class using one or more receptor structures of other classes seemed to be indicative of a reasonable pose prediction. Affinity prediction proved to be more challenging with generally poor correlation with experimental IC50s (Kendall tau ~ 0.3). Even when the 36 crystal structures were used the accuracy of the predicted affinities was not appreciably improved. A possible cause of difficulty is the internal energy strain arising from conformational differences in the receptor across complexes, which may need to be properly estimated and incorporated into the SIE scoring function.

Entities:  

Keywords:  Protein flexibility; Protein-ligand docking; SIE; Wilma

Mesh:

Substances:

Year:  2017        PMID: 28983727     DOI: 10.1007/s10822-017-0071-0

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


  21 in total

1.  Evaluation of the Wilma-SIE Virtual Screening Method in Community Structure-Activity Resource 2013 and 2014 Blind Challenges.

Authors:  Hervé Hogues; Traian Sulea; Enrico O Purisima
Journal:  J Chem Inf Model       Date:  2015-08-24       Impact factor: 4.956

Review 2.  Flexible ligand docking to multiple receptor conformations: a practical alternative.

Authors:  Maxim Totrov; Ruben Abagyan
Journal:  Curr Opin Struct Biol       Date:  2008-02-25       Impact factor: 6.809

Review 3.  Receptor-ligand molecular docking.

Authors:  Isabella A Guedes; Camila S de Magalhães; Laurent E Dardenne
Journal:  Biophys Rev       Date:  2013-12-21

Review 4.  Software for molecular docking: a review.

Authors:  Nataraj S Pagadala; Khajamohiddin Syed; Jack Tuszynski
Journal:  Biophys Rev       Date:  2017-01-16

5.  Exhaustive docking and solvated interaction energy scoring: lessons learned from the SAMPL4 challenge.

Authors:  Hervé Hogues; Traian Sulea; Enrico O Purisima
Journal:  J Comput Aided Mol Des       Date:  2014-01-29       Impact factor: 3.686

6.  D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions.

Authors:  Symon Gathiaka; Shuai Liu; Michael Chiu; Huanwang Yang; Jeanne A Stuckey; You Na Kang; Jim Delproposto; Ginger Kubish; James B Dunbar; Heather A Carlson; Stephen K Burley; W Patrick Walters; Rommie E Amaro; Victoria A Feher; Michael K Gilson
Journal:  J Comput Aided Mol Des       Date:  2016-09-30       Impact factor: 3.686

7.  Lessons Learned over Four Benchmark Exercises from the Community Structure-Activity Resource.

Authors:  Heather A Carlson
Journal:  J Chem Inf Model       Date:  2016-06-27       Impact factor: 4.956

Review 8.  Overview of the SAMPL5 host-guest challenge: Are we doing better?

Authors:  Jian Yin; Niel M Henriksen; David R Slochower; Michael R Shirts; Michael W Chiu; David L Mobley; Michael K Gilson
Journal:  J Comput Aided Mol Des       Date:  2016-09-22       Impact factor: 3.686

9.  Identification of a minimal subset of receptor conformations for improved multiple conformation docking and two-step scoring.

Authors:  Sukjoon Yoon; William J Welsh
Journal:  J Chem Inf Comput Sci       Date:  2004 Jan-Feb

10.  Systematic exploitation of multiple receptor conformations for virtual ligand screening.

Authors:  Giovanni Bottegoni; Walter Rocchia; Manuel Rueda; Ruben Abagyan; Andrea Cavalli
Journal:  PLoS One       Date:  2011-05-17       Impact factor: 3.240

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  2 in total

Review 1.  Improving small molecule virtual screening strategies for the next generation of therapeutics.

Authors:  Bentley M Wingert; Carlos J Camacho
Journal:  Curr Opin Chem Biol       Date:  2018-06-17       Impact factor: 8.822

2.  D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.

Authors:  Conor D Parks; Zied Gaieb; Michael Chiu; Huanwang Yang; Chenghua Shao; W Patrick Walters; Johanna M Jansen; Georgia McGaughey; Richard A Lewis; Scott D Bembenek; Michael K Ameriks; Tara Mirzadegan; Stephen K Burley; Rommie E Amaro; Michael K Gilson
Journal:  J Comput Aided Mol Des       Date:  2020-01-23       Impact factor: 3.686

  2 in total

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