Methods for Computer-Aided Chemical Biology

Abstract

Computational drug design and discovery methods have traditionally put much emphasis on the identification of novel active compounds and the optimization of their potency. For chemical genetics and genomics applications, an important task is the identification of small molecules that are selective against target families, subfamilies, or individual targets and can be used as molecular probes for specific functions. In order to develop or tune computational methods for such applications, there is a need for molecular benchmark systems that focus on compound selectivity, rather than qualitative biological activity or potency.<br /> Two selectivity-oriented test systems have been designed that consist of several compound selectivity sets for individual targets belonging to distinct protein families. Compound selectivity sets were characterized by structural diversity, chemical scaffold, and selectivity range analysis. These compound systems were especially designed for selectivity studies. Thus far, computational methods have had only little impact on the search for selective compounds. This is in part due to the fact that selectivity is more difficult to study than activity because selectivity analysis requires the evaluation of compounds binding to multiple targets.<br /> Here, we have investigated the ability of state-of-the-art 2D molecular fingerprints and a mapping algorithm to detect compounds having different selectivity profiles. The results of systematic similarity search calculations revealed that these computational methods are capable of identifying compounds having different selectivity against closely related target proteins, although they were originally not developed for such applications.<br /> Finally, we have successfully applied these methodologies to introduce in <i>silico selectivity searching</i> for the identification of cathepsin K inhibitors. On the basis of computational analysis, 16 candidate molecules taken from 3.7 million database compounds were tested and two inhibitors identified that showed a clear selective tendency for cathepsin K over cathepsin S and L. One of these inhibitors represents a previously unobserved chemotype.