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.
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)
Coordinates of public retrospective predictions (ZIP)
PDB format files for predictions originating from rigid receptor docking or induced fit docking for the public data set