Induced-Fit Docking Enables Accurate Free Energy Perturbation Calculations in Homology Models

15 April 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Homology models have been used for virtual screening and to understand the binding mode of a known active, however rare-ly have the models been shown to be of sufficient accuracy, comparable to crystal structures, to support free-energy perturba-tion (FEP) calculations. We demonstrate here that the use of an advanced induced-fit docking methodology reliably enables predictive FEP calculations on congeneric series across homology models ≥ 30% sequence identity. Further, we show that retrospective FEP calculations on a congeneric series of drug-like ligands is sufficient to discriminate between predicted binding modes. Results are presented for a total of 29 homology models for 14 protein targets, showing FEP results compa-rable to those obtained using experimentally determined crystal structures for 86% of homology models with template struc-ture sequence identities ranging from 30% to 50%. Implications for the use and validation of homology models in drug dis-covery projects are discussed, including the use of AlphaFold2 de novo structures.

Keywords

IFD
Induced Fit Docking
Structure Prediction
Free Energy Perturbation
Drug Discovery
Structure-Based Drug Discovery
SBDD
Homology Modeling

Supplementary materials

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Description
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Supplementary Material
Description
Detailed results for each homology modeling case and the in-dividual poses generated by IFD-MD and GlideSP, parameter values for the composite scoring function, congeneric subse-ries selected for PDE10A validation (PDF)
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Coordinates of public retrospective predictions (ZIP)
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PDB format files for predictions originating from rigid receptor docking or induced fit docking for the public data set
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