The maximal and current accuracy of rigorous protein-ligand binding free energy calculations

Computational techniques can speed up the identification of hits and accelerate the development of candidate molecules for drug discovery. Among techniques for predicting relative binding affinities, the most consistently accurate is free energy perturbation (FEP), a class of rigorous physics-based methods. However, uncertainty remains about how accurate FEP is and can ever be. Here, we present what we believe to be the largest publicly available dataset of proteins and congeneric series of small molecules, and assess the accuracy of the leading FEP workflow. To ascertain the limit of achievable accuracy, we also survey the reproducibility of experimental relative affinity measurements. We find a wide variability in experimental accuracy and a correspondence between binding and functional assays. When careful preparation of protein and ligand structures is undertaken, FEP can achieve accuracy comparable to experimental reproducibility. Throughout, we highlight reliable protocols that can help maximize the accuracy of FEP in prospective studies. Free energy perturbation (FEP) is a well-recognized computational technique to predict the relative affinities of protein-ligand interactions, however, the exact accuracy of FEP prediction remains uncertain. Here, the authors assess the current accuracy of the leading FEP workflow by assembling a benchmark dataset, and highlight reliable protocols to maximize the accuracy of FEP in prospective studies.

Automated summary

The accuracy of the leading FEP workflow is assessed by assembling a benchmark dataset, and reliable protocols are highlighted to maximize the accuracy of FEP in prospective studies.