Title | Identifying Allosteric Hotspots with Dynamics: Application to Inter- and Intra-species Conservation. |
Publication Type | Journal Article |
Year of Publication | 2016 |
Authors | Clarke, D, Sethi, A, Li, S, Kumar, S, Chang, RWF, Chen, J, Gerstein, M |
Journal | Structure |
Volume | 24 |
Issue | 5 |
Pagination | 826-837 |
Date Published | 2016 05 03 |
ISSN | 1878-4186 |
Keywords | Allosteric Site, Animals, Conserved Sequence, Humans, Proteome, Sequence Analysis, Protein, Software |
Abstract | The rapidly growing volume of data being produced by next-generation sequencing initiatives is enabling more in-depth analyses of conservation than previously possible. Deep sequencing is uncovering disease loci and regions under selective constraint, despite the fact that intuitive biophysical reasons for such constraint are sometimes absent. Allostery may often provide the missing explanatory link. We use models of protein conformational change to identify allosteric residues by finding essential surface pockets and information-flow bottlenecks, and we develop a software tool that enables users to perform this analysis on their own proteins of interest. Though fundamentally 3D-structural in nature, our analysis is computationally fast, thereby allowing us to run it across the PDB and to evaluate general properties of predicted allosteric residues. We find that these tend to be conserved over diverse evolutionary time scales. Finally, we highlight examples of allosteric residues that help explain poorly understood disease-associated variants. |
DOI | 10.1016/j.str.2016.03.008 |
Alternate Journal | Structure |
PubMed ID | 27066750 |
PubMed Central ID | PMC4883016 |
Grant List | UM1 HG006504 / HG / NHGRI NIH HHS / United States UL1 TR001863 / TR / NCATS NIH HHS / United States T32 GM008283 / GM / NIGMS NIH HHS / United States P30 DA018343 / DA / NIDA NIH HHS / United States U54 DA036134 / DA / NIDA NIH HHS / United States |