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

From National Research Council Canada

DOIResolve DOI: https://doi.org/10.1007/s10822-017-0071-0
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Name affiliation
  1. National Research Council Canada. Human Health Therapeutics
FormatText
TypeArticle
Journal titleJournal of Computer-Aided Molecular Design
ISSN0920-654X
1573-4951
Pages# of pages: 8
Subjectprotein-ligand docking; protein flexibility; SIE; Wilma
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.
Publication date
PublisherSpringer
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LanguageEnglish
Peer reviewedYes
NPARC number23002487
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Record identifierbf3c9a48-562b-4b43-b6ce-ee2645ebda99
Record created2017-11-16
Record modified2017-11-16
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