Performance of Relative Binding Free Energy Calculations on an Automatically Generated Dataset of Halogen–Deshalogen Matched Molecular Pairs

In
this study, we generated a matched molecular pair dataset of
halogen/deshalogen compounds with reliable binding affinity data and
structural binding mode information from public databases. The workflow
includes automated system preparation and setup of free energy perturbation
relative binding free energy calculations. We demonstrate the suitability
of these datasets to investigate the performance of molecular mechanics
force fields and molecular simulation algorithms for the purpose of
in silico affinity predictions in lead optimization. Our datasets
of a total of 115 matched molecular pairs show highly accurate binding
free energy predictions with an average error of <1 kcal/mol despite
the semi-automated calculation scheme. We quantify the accuracy of
the optimized potential for liquid simulations (OPLS) force field
to predict the effect of halogen addition to compounds, a commonly
employed chemical modification in the design of drug-like molecules.