Druggable exosites of the human kinopocketome Small molecules binding at any of the multiple regulatory sites on the molecular surface of a protein kinase may stabilize or disrupt the corresponding interaction, leading to consequent modulation of the kinase cellular activity. As such, each of these sites represents a potential drug target. Even targeting sites outside the immediate ATP site, the socalled exosites, may cause desirable biological effects through an allosteric mechanism. Targeting exosites can alleviate adverse effects and toxicity that is common when ATPsite compounds bind promiscuously to many other types of kinases. In this study we have identified, catalogued, and annotated all potentially druggable exosites on the protein kinase domains within the existing structural human kinome. We then priorityranked these exosites by those most amenable to drug design. In order to identify pockets that are either consistent across the kinome, or unique and specific to a particular structure, we have also implemented a normalized representation of all pockets, and displayed these graphically. Finally, we have built a database and designed a webbased interface for users interested in accessing the 3dimensional representations of these pockets. We envision this information will assist drug discovery efforts searching for untargeted binding pockets in the human kinome.

Evaluating Precisicon and Recall through the Utility of msTALI via an Active Site Study on Fold Families Proteins execute various activities required by biological cells. Further, they structurally support and promote important biochemical reactions which functionally are sparked by activesites. Activesites are regions where reactions and binding events take place directly; they foster protein purpose. Describing functional relationships depends on factors that incorporate sequence, structure, and the biochemical properties of amino acids that form proteins. Our approach to activesite description is computational, and many other approaches utilizing available protein data fall short of ideal. Successful recognition of functional interactions is crucial to advancements in protein annotation and the bioinformatics field at large. This research outlines our Multiple Structure Torsion Angle Alignment (msTALI) as a suitable strategy for addressing activesite identification by comparing results to other existing methods. Specifically, we address the precision of msTALI across three protein families. Our target proteins are PDBIDs 1A2B, 1B4V, 1B8S, 1COY, 1CXZ, 3COX, 1D7E, 1DPF, 1F9I, 1FTN, 1IJH, 1KOU, 1NWZ, 2PHY, and 1SIC.