TY - JOUR T1 - Is structure based drug design ready for selectivity optimization? JF - bioRxiv DO - 10.1101/2020.07.02.185132 SP - 2020.07.02.185132 AU - Steven K. Albanese AU - John D. Chodera AU - Andrea Volkamer AU - Simon Keng AU - Robert Abel AU - Lingle Wang Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/09/22/2020.07.02.185132.abstract N2 - Alchemical free energy calculations are now widely used to drive or maintain potency in small molecule lead optimization with a roughly 1 kcal/mol accuracy. Despite this, the potential to use free energy calculations to drive optimization of compound selectivity among two similar targets has been relatively unexplored in published studies. In the most optimistic scenario, the similarity of binding sites might lead to a fortuitous cancellation of errors and allow selectivity to be predicted more accurately than affinity. Here, we assess the accuracy with which selectivity can be predicted in the context of small molecule kinase inhibitors, considering the very similar binding sites of human kinases CDK2 and CDK9, as well as another series of ligands attempting to achieve selectivity between the more distantly related kinases CDK2 and ERK2. Using a Bayesian analysis approach, we separate systematic from statistical error and quantify the correlation in systematic errors between selectivity targets. We find that, in the CDK2/CDK9 case, a high correlation in systematic errors suggests free energy calculations can have significant impact in aiding chemists in achieving selectivity, while in more distantly related kinases (CDK2/ERK2), the correlation in systematic error suggests fortuitous cancellation may even occur between systems that are not as closely related. In both cases, the correlation in systematic error suggests that longer simulations are beneficial to properly balance statistical error with systematic error to take full advantage of the increase in apparent free energy calculation accuracy in selectivity prediction.Competing Interest StatementJDC was a member of the Scientific Advisory Board for Schrodinger, LLC during part of this study. JDC is a current member of the Scientific Advisory Board of OpenEye Scientific Software and a consultant for Foresite Labs. The Chodera laboratory receives or has received funding from multiple sources, including the National Institutes of Health, the National Science Foundation, the Parker Institute for Cancer Immunotherapy, Relay Therapeutics, Bayer, Entasis Therapeutics, Silicon Therapeutics, EMD Serono (Merck KGaA), AstraZeneca, XtalPi, the Molecular Sciences Software Institute, the Starr Cancer Consortium, the Open systematic Consortium, Cycle for Survival, a Louis V. Gerstner Young Investigator Award, and the Sloan Kettering Institute. A complete funding history for the Chodera lab can be found at http://choderalab.org/funding ER -