info:eu-repo/semantics/article
Cosolvent-Based Protein Pharmacophore for Ligand Enrichment in Virtual Screening
Fecha
2019-08Registro en:
Arcon, Juan Pablo; Defelipe, Lucas Alfredo; Lopez, Elias Daniel; Burastero, Osvaldo; Modenutti, Carlos Pablo; et al.; Cosolvent-Based Protein Pharmacophore for Ligand Enrichment in Virtual Screening; American Chemical Society; Journal of Chemical Information and Modeling; 59; 8; 8-2019; 3572-3583
1549-9596
1520-5142
CONICET Digital
CONICET
Autor
Arcon, Juan Pablo
Defelipe, Lucas Alfredo
Lopez, Elias Daniel
Burastero, Osvaldo
Modenutti, Carlos Pablo
Barril, Xavier
Marti, Marcelo Adrian
Turjanski, Adrian
Resumen
Virtual screening of large compound databases, looking for potential ligands of a target protein, is a major tool in computer-aided drug discovery. Throughout the years, different techniques such as similarity searching, pharmacophore matching, or molecular docking have been applied with the aim of finding hit compounds showing appreciable affinity. Molecular dynamics simulations in mixed solvents have been shown to identify hot spots relevant for protein-drug interaction, and implementations based on this knowledge were developed to improve pharmacophore matching of small molecules, binding free-energy estimations, and docking performance in terms of pose prediction. Here, we proved in a retrospective manner that cosolvent-derived pharmacophores from molecular dynamics (solvent sites) improve the performance of docking-based virtual screening campaigns. We applied a biased docking scheme based on solvent sites to nine relevant target proteins that have a set of known ligands or actives and compounds that are, presumably, nonbinders (decoys). Our results show improvement in virtual screening performance compared to traditional docking programs both at a global level, with up to 35% increase in areas under the receiver operating characteristic curve, and in early stages, with up to a 7-fold increase in enrichment factors at 1%. However, the improvement in pose prediction of actives was less profound. The presented application makes use of the AutoDock Bias method and is the only cosolvent-derived pharmacophore technique that employs its knowledge both in the ligand conformational search algorithm and the final affinity scoring for virtual screening purposes.