Ensemble-Based Replica Exchange Alchemical Free Energy Methods: The Effect of Protein Mutations on Inhibitor Binding
Agastya P. Bhati, Shunzhou Wan, and Peter V. Coveney
Journal of Chemical Theory and Computation (2018) DOI: 10.1021/acs.jctc.8b01118
Mutations enable proteins to tailor molecular recognition with small-molecule ligands and other macromolecules, and can have a major impact on drug efficacy. Some protein mutations may fortuitously bring therapeutic benefit to some patients who use a specific drug treatment, while others may impair the ability of a drug to bind with the protein, one of the reasons for the target proteins developing drug resistance. The accurate prediction of the binding affinity changes of drugs caused by protein mutations is a major goal in both drug development and personalized medicine.
We have developed an ensemble-based free energy approach called thermodynamic integration with enhanced sampling (TIES), which yields accurate, precise, and reproducible binding affinities. TIES has been shown to perform well for predictions of free energy differences of congeneric ligands to a wide range of target proteins. In our previous publications, we have introduced variants of TIES, which incorporate the enhanced sampling technique REST2 (replica exchange with solute tempering) and the free energy estimator MBAR (Bennett acceptance ratio). In the current study we further extend the TIES methodology to study relative binding affinities caused by protein mutations when bound to a ligand, a variant which we call TIES-PM. We apply TIES-PM to fibroblast growth factor receptor 3 (FGFR3) to investigate binding free energy changes upon protein mutations.
We have investigated two challenging cases of protein mutations in this study: one is a gatekeeper mutation located in the binding site, which induces a large conformational change within one of the inhibitors; another is the mutations remote from the binding site which do not have significant impact on the stability of the protein yet have an influence on inhibitor binding. The results show that TIES-PM with REST2 successfully captures the large conformational change and generates correct free energy differences caused by the gatekeeper mutation. Simulations without REST2 fail to overcome the energy barrier between the conformations, and hence the results are highly sensitive to the initial structures. For remote mutations, however, the TIES-PM with REST2 could not improve the binding free energy predictions. This is not surprising given that the mutations are far away from the bound inhibitors and affect the binding through an allosteric mechanism of which the length and/or time scales are greater than standard atomistic molecular simulations can access.
On the basis of the observation in this study, we formulate some caveats and recommendations concerning the application of the REST2 technique in general for free energy predictions. One requires some preliminary knowledge of the topological and physical properties of the protein−ligand systems for appropriate setup of the REST2 simulations. Blind application of enhanced sampling approaches with the hope to improve sampling is not wise and may lead to deteriorated free energy predictions.