Computational Method to Evaluate Progress in Lead Optimization.

Abstract

In medicinal chemistry, lead optimization is a critically important task and a highly empirical process, largely driven by chemical knowledge and intuition. Only very few approaches are available to guide and evaluate optimization efforts. It is often very difficult to understand when a compound series is exhausted and the generation of additional analogs unlikely to yield further progress toward potent and efficacious candidates. Rationalizing lead optimization remains an essentially unsolved problem. Herein, we introduce a new computational method to aid in evaluating whether sufficient numbers of analogs have been made and further progress is unlikely. The approach integrates the assessment of chemical saturation and structure-activity relationship progression of compound series. Easy-to-calculate scores characterize evolving analog series and identify candidates with high or low priority for further chemical exploration.