Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge

As part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV inte...

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Veröffentlicht in:Journal of computer-aided molecular design 2014-04, Vol.28 (4), p.475-490
Hauptverfasser: Gallicchio, Emilio, Deng, Nanjie, He, Peng, Wickstrom, Lauren, Perryman, Alexander L., Santiago, Daniel N., Forli, Stefano, Olson, Arthur J., Levy, Ronald M.
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container_issue 4
container_start_page 475
container_title Journal of computer-aided molecular design
container_volume 28
creator Gallicchio, Emilio
Deng, Nanjie
He, Peng
Wickstrom, Lauren
Perryman, Alexander L.
Santiago, Daniel N.
Forli, Stefano
Olson, Arthur J.
Levy, Ronald M.
description As part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV integrase protein. The computational protocol leveraged docking and high level atomistic models to improve enrichment. The enrichment factor of our blind predictions ranked best among all of the computational submissions, and second best overall. This work represents to our knowledge the first example of the application of an all-atom physics-based binding free energy model to large scale virtual screening. A total of 285 parallel Hamiltonian replica exchange molecular dynamics absolute protein-ligand binding free energy simulations were conducted starting from docked poses. The setup of the simulations was fully automated, calculations were distributed on multiple computing resources and were completed in a 6-weeks period. The accuracy of the docked poses and the inclusion of intramolecular strain and entropic losses in the binding free energy estimates were the major factors behind the success of the method. Lack of sufficient time and computing resources to investigate additional protonation states of the ligands was a major cause of mispredictions. The experiment demonstrated the applicability of binding free energy modeling to improve hit rates in challenging virtual screening of focused ligand libraries during lead optimization.
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subjects Animal Anatomy
Binders
Binding energy
Biophysics
Chemistry
Chemistry and Materials Science
Computation
Computer Applications in Chemistry
Computer-Aided Design
Drug Design
Enrichment
Free energy
Histology
HIV
HIV - enzymology
HIV Infections - drug therapy
HIV Infections - enzymology
HIV Infections - virology
HIV Integrase - chemistry
HIV Integrase - metabolism
Human immunodeficiency virus
Humans
Inhibitors
Integrase Inhibitors - chemistry
Integrase Inhibitors - pharmacology
Ligands
Mathematical models
Molecular biology
Molecular Docking Simulation
Morphology
Physical Chemistry
Protein Binding
Screening
Software
Thermodynamics
title Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge
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