Center for Computational Biology and Bioinformatics, Koc University, Istanbul Turkey.
PLoS One. 2011 Jan 25;6(1):e16474. doi: 10.1371/journal.pone.0016474.
The nonlocal nature of the protein-ligand binding problem is investigated via the Gaussian Network Model with which the residues lying along interaction pathways in a protein and the residues at the binding site are predicted. The predictions of the binding site residues are verified by using several benchmark systems where the topology of the unbound protein and the bound protein-ligand complex are known. Predictions are made on the unbound protein. Agreement of results with the bound complexes indicates that the information for binding resides in the unbound protein. Cliques that consist of three or more residues that are far apart along the primary structure but are in contact in the folded structure are shown to be important determinants of the binding problem. Comparison with known structures shows that the predictive capability of the method is significant.
通过高斯网络模型研究蛋白质-配体结合问题的非局部性质，该模型可以预测蛋白质中沿相互作用途径的残基和结合部位的残基。通过使用几个已知未结合蛋白质和结合蛋白质-配体复合物拓扑结构的基准系统来验证结合部位残基的预测。在未结合的蛋白质上进行预测。与结合复合物的结果一致表明，结合信息存在于未结合的蛋白质中。沿着一级结构相距很远但在折叠结构中接触的包含三个或更多残基的团簇被证明是结合问题的重要决定因素。与已知结构的比较表明，该方法具有显著的预测能力。
