Volume 83, Issue 8 pp. 1375-1384
Article

Allosteric sites can be identified based on the residue–residue interaction energy difference

Xiaomin Ma

Xiaomin Ma

Center for Quantitative Biology, Peking University, Beijing, 100871 China

Xiaomin Ma and Yifei Qi contributed equally to this work.

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Yifei Qi

Yifei Qi

Center for Quantitative Biology, Peking University, Beijing, 100871 China

Xiaomin Ma and Yifei Qi contributed equally to this work.

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Luhua Lai

Corresponding Author

Luhua Lai

Center for Quantitative Biology, Peking University, Beijing, 100871 China

BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, and Peking-Tsinghua Center for Life Sciences at College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871 China

Correspondence to: Luhua Lai, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China. E-mail: [email protected]Search for more papers by this author
First published: 03 September 2014
Citations: 16

ABSTRACT

Allosteric drugs act at a distance to regulate protein functions. They have several advantages over conventional orthosteric drugs, including diverse regulation types and fewer side effects. However, the rational design of allosteric ligands remains a challenge, especially when it comes to the identification allosteric binding sites. As the binding of allosteric ligands may induce changes in the pattern of residue–residue interactions, we calculated the residue–residue interaction energies within the allosteric site based on the molecular mechanics generalized Born surface area energy decomposition scheme. Using a dataset of 17 allosteric proteins with structural data for both the apo and the ligand-bound state available, we used conformational ensembles generated by molecular dynamics simulations to compute the differences in the residue–residue interaction energies in known allosteric sites from both states. For all the known sites, distinct interaction energy differences (>25%) were observed. We then used CAVITY, a binding site detection program to identify novel putative allosteric sites in the same proteins. This yielded a total of 31 “druggable binding sites,” of which 21 exhibited >25% difference in residue interaction energies, and were hence predicted as novel allosteric sites. Three of the predicted allosteric sites were supported by recent experimental studies. All the predicted sites may serve as novel allosteric sites for allosteric ligand design. Our study provides a computational method for identifying novel allosteric sites for allosteric drug design. Proteins 2015; 83:1375–1384. © 2014 Wiley Periodicals, Inc.

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