Welcome to CorrSite, a server for the prediction of allosteric sites on protein structures.
Allostery is the phenomenon in which a ligand binding at one site affects other sites in the same macromolecule. Allostery has important roles in many biological processes, such as enzyme catalysis, signal transduction, and gene regulation. Allosteric drugs have several advantages compared with traditional orthosteric drugs, including fewer side effects and easier up- or down-regulation of target activity. Theoretically, all nonfibrous proteins are potentially allosteric. Given an nonfibrous protein structure, it is important to identify the location of allosteric sites before doing structure-based allosteric drug design on it.
CorrSite Server is a freely accessed web-server designed to identify potential protein allosteric sites. Here, we describe the CorrSite algorithm briefly. First, the program imports the coordinates of protein atoms from a PDB file and its orthosteric site information. Then, the program detects the potential protein binding sites by using CAVITY . The calculated cavities with greater than 75% overlapping residues with the orthosteric site are excluded. After that, the program calculates correlations between these potential ligand-binding sites and corresponding orthosteric sites using a Gaussian network model (GNM). If the normalized correlation of one cavity is more than 0.5, this cavity is identified as a potential allosteric site.
To use CorrSite Server, please provide information of the protein of your interest and its orthosteric site in the Computing page. The job information as well as the structures of submitted molecules is invisible between different users. Here is a CorrSite V1.0 software . You can download and install it in your Linux system.
1. Xiaomin Ma, Hu Meng, Luhua Lai. Motions of Allosteric and Orthosteric Ligand-Binding Sites in Proteins are Highly Correlated. J. Chem. Inf. Model., 2016, 56 (9), 1725-1733.
2. Yaxia Yuan, Jianfeng Pei, Luhua Lai. Binding site detection and druggability prediction of protein targets for structure-based drug design. Current pharmaceutical design 19.12 (2013): 2326-2333.