Improving Docking Accuracy through Molecular Mechanics Generalized Born Optimization and Scoring.

Docking methods are typically used within the biopharmaceutical industry for the challenging purposes of suggesting putative binding modes of new chemotypes and for virtual screening. When attempting to satisfy the far more simplistic yet fundamentally important goal of reproducing and identifying the correct binding mode from a cocrystal, all docking methods fail at a rather significant rate, demonstrating room for further improvement in docking methodology. We report a hierarchical method that yields results comparable to the industry-leading docking packages GOLD, Glide, and Surflex. By first using a fast, simple, well-established method, UCSF DOCK 4.0, to rigidly dock conformational ensembles, we successfully generate the correct binding mode in all but 4 of a standard, publicly available set of 79 cocrystals from the PDB. Among these 4 failures (1glq, 1tmn, 1rds, and 8gch), all are highly flexible, highly charged, and not druglike. Subsequently, all resultant docking poses were optimized and scored in the protein with molecular mechanics, using a standard MMGB energy function. In total, this hierarchical method identified the correct binding in 71 of 79 cases (90%), an unprecedented level of accuracy on this highly benchmarked test set. Furthermore, the publicly available energy functions employ only physically based force fields without parameter fitting from this or any other docking test sets.