Effect of automation on the accuracy of alchemical free energy calculation protocols over a set of ACK1 inhibitors

Hit-to-lead virtual screening frequently relies on a cascade of computational methods that starts with rapid calculations applied to a large number of compounds and ends with more expensive computations restricted to a subset of compounds that passed initial filters. This work focuses on protocols for alchemical free energy (AFE) scoring in the context of a Docking - MM/PBSA - AFE cascade. A dataset of 15 congeneric inhibitors of the ACK1 protein was used to evaluate the performance of AFE protocols that varied in the steps taken to prepare input files (fully automated from previously docked and scored poses, manual selection of poses, manual placement of binding site water molecules). The main finding is that use of knowledge derived from X-ray structures to model binding modes, together with the manual placement of a bridging water molecule, improves the R2 from 0.45 +/- 0.06 to 0.76 +/- 0.02 and decreases the mean unsigned error from 2.11 +/- 0.08 to 1.24 +/- 0.04 kcal mol-1. By contrast a brute force automated protocol that increased the sampling time ten-fold lead to little improvements in accuracy.