TY - JOUR T1 - Using Multiple Microenvironments to Find Similar Ligand-Binding Sites: Application to Kinase Inhibitor Binding A1 - Liu, Tianyun A1 - Altman, Russ B. Y1 - 2011/12/29 N2 - Author Summary Small molecule drugs may interact with many proteins. Some of these interactions may cause unexpected effects, including side effects or potentially useful therapeutic effects. One way to predict these effects is to analyze the three-dimensional structure of target proteins, and identify new binding sites for small molecule drugs. Several methods have been proposed for predicting new binding sites, relying on geometric and functional complementarity of the sites and the small molecules. In this paper, we report on a new method for identifying novel protein-drug interactions by analyzing the similarity between binding sites in proteins. The method has relatively weak geometric requirements and allows for conformational change or dynamics in both the ligand and protein. Our results show that geometric flexibility is useful for effectively comparing sites. We have applied the method to evolutionarily distant kinases, and find unexpected shared inhibitor binding. Our results may be valuable for drug repurposing in order to find novel uses for existing kinase inhibitors. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 7 IS - 12 UR - https://doi.org/10.1371/journal.pcbi.1002326 SP - e1002326 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002326 ER -