Using AlphaFold and Experimental Structures for the Prediction of the Structure and Binding Affinities of GPCR Complexes via Induced Fit Docking and Free Energy Perturbation

Abstract

Free energy perturbation (FEP) remains an indispensable method for computationally assaying prospective compounds in advance of synthesis. But before FEP can be deployed prospectively, it must demonstrate retrospective recapitulation of known experimental data where the subtle details of the atomic ligand-receptor model are consequential. An open question is whether AlphaFold models can serve as useful initial models for FEP in the regime where there exists a congeneric series of known chemical matter but where no experimental structures are available either of the target or of close homologues. As AlphaFold structures are provided without a ligand bound, we employ induced-fit docking to refine the AlphaFold models in the presence of one or more congeneric ligands. In this work, we first validate the performance of our latest induced-fit docking technology, IFD-MD on a retrospective set of public experimental GPCR structures with 95% of crossdocks produc-ing a pose with a ligand RMSD ≤ 2.5 Å in the top 2 predictions. We then apply IFD-MD and FEP on AlphaFold models of the somatostatin receptor family of GPCRs. We use AlphaFold models produced prior to the availability of any experi-mental structure from within this family. We arrive at FEP-validated models for SSTR2, SSTR4, and SSTR5, with RMSE around 1 kcal/mol and explore the challenges of model validation under scenarios of limited ligand-data, ample ligand data, and categorical data.