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A Reliable and Accurate Solution to the Induced Fit Docking Problem for Protein-Ligand Binding

preprint
submitted on 13.03.2020 and posted on 17.03.2020 by Edward Miller, Robert Murphy, Daniel Sindhikara, Ken Borrelli, Matthew Grisewood, Fabio Ranalli, Steven Dixon, Steven Jerome, Nicholas Boyles, Tyler Day, Phani Ghanakota, Sayan Mondal, Salma B. Rafi, Dawn M. Troast, Robert Abel, Richard Friesner
We present a reliable and accurate solution to the induced fit docking problem for protein-ligand binding by combining ligand-based pharmacophore docking (Phase), rigid receptor docking (Glide), and protein structure prediction (Prime) with explicit solvent molecular dynamics simulations. We provide an in-depth description of our novel methodology and present results for 41 targets consisting of 415 cross-docking cases divided amongst a training and test set. For both the training and test-set, we compute binding modes with a ligand-heavy atom RMSD to within 2.5 Å or better in over 90% of cross-docking cases compared to less than 70% of cross-docking cases using our previously published induced-fit docking algorithm and less than 41% using rigid receptor docking. Applications of the predicted ligand-receptor structure in free energy perturbation calculations is demonstrated for both public data and in active drug discovery projects, both retrospectively and prospectively.

History

Email Address of Submitting Author

ed.miller@schrodinger.com

Institution

Schrodinger, LLC

Country

United States

ORCID For Submitting Author

0000-0003-1590-5788

Declaration of Conflict of Interest

R.A.F. has a significant financial stake in Schrödinger, Inc., is a consultant to Schrödinger, Inc., and is on the Scientific Advisory Board of Schrödinger, Inc.

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