A Tool Set to Map Dynamic Allosteric Networks through the NMR Chemical Shift Covariance Analysis (CHESCA)

Abstract

Allostery is an essential regulatory mechanism of biological function and allosteric sites are also pharmacologically relevant, as they are typically targeted with higher selectivity than orthosteric sites. However, obtaining a comprehensive map of allosteric sites poses experimental challenges because allostery is driven not only by structural changes, but also by modulations in dynamics that often remain elusive to classical structure determination methods. An avenue to overcome these challenges is provided by the covariance analysis of NMR chemical shift [1, 2], which are exquisitely sensitive to redistributions in dynamic conformational ensembles. Here, we propose a set of complementary algorithms for the NMR chemical shift covariance analysis (CHESCA) designed to reliably detect allosteric networks with minimal occurrences of false positives or negatives. The proposed CHESCA toolset was tested for two allosteric proteins (Protein Kinase A, PKA, and the Exchange Protein directly Activated by cAMP, EPAC) and is expected to complement traditional comparative structural analyses in the comprehensive identification of functionally relevant allosteric sites, including those in otherwise elusive partially unstructured regions.[1] Signaling through dynamic linkers as revealed by PKA. Akimoto M, Selvaratnam R, McNicholl ET, Verma G, Taylor SS, Melacini G. Proc Natl Acad Sci U S A. 2013;110(35):14231-6.[2] Mapping allostery through the covariance analysis of NMR chemical shifts. Selvaratnam R, Chowdhury S, VanSchouwen B, Melacini G. Proc Natl Acad Sci U S A. 2011;108(15):6133-8.