A computational methods for identifying allosteric binding sites in kinases

There are 518 protein kinases encoded within the human genome [1] that control cellular signal transduction and play a major role in almost all cellular events. Aberrant kinase activity is linked to pathological conditions including cancer, inflammation, diabetes and many others, making them a tractable target for drug discovery research [2-5]. To date, most of the current medicinal chemistry efforts target the ATP binding site, which is highly conserved amongst the kinase family, and many compounds suffer from cross-activity leading to undesirable side effects and toxicity. The ability to target allosteric sites on the catalytic domain of kinases, which are less conserved compared to ATP binding sites, would therefore provide an avenue for greater selectivity. Here we propose a computational approach to identify allosteric sites in target kinases. We use a combination of molecular dynamics (MD) simulations to explore the critical structural and dynamic conformational changes of the enzymes and simple intrasequence differences (SID) analysis which identifies the major interfaces in the enzyme that may be involved in allosteric modulation. This computational approach provides not only a new method of identifying allosteric sites but also a better understanding of the mechanisms of allosteric modulation of target kinases and the structural basis for the design and development of more selective and specific small molecules inhibitors as therapeutic agents.

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