Virtual screening of the SAMPL4 blinded HIV integrase inhibitors dataset

  • Claire Colas
  • , Bogdan I. Iorga

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Several combinations of docking software and scoring functions were evaluated for their ability to predict the binding of a dataset of potential HIV integrase inhibitors. We found that different docking software were appropriate for each one of the three binding sites considered (LEDGF, Y3 and fragment sites), and the most suitable two docking protocols, involving Glide SP and Gold ChemScore, were selected using a training set of compounds identified from the structural data available. These protocols could successfully predict respectively 20.0 and 23.6 % of the HIV integrase binders, all of them being present in the LEDGF site. When a different analysis of the results was carried out by removing all alternate isomers of binders from the set, our predictions were dramatically improved, with an overall ROC AUC of 0.73 and enrichment factor at 10 % of 2.89 for the prediction obtained using Gold ChemScore. This study highlighted the ability of the selected docking protocols to correctly position in most cases the ortho-alkoxy-carboxylate core functional group of the ligands in the corresponding binding site, but also their difficulties to correctly rank the docking poses.

Original languageEnglish
Pages (from-to)455-462
Number of pages8
JournalJournal of Computer-Aided Molecular Design
Volume28
Issue number4
DOIs
StatePublished - Apr 2014

Keywords

  • Docking
  • HIV integrase inhibitors
  • SAMPL4 blind challenge
  • Scoring function
  • Virtual screening

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