Gohlke Holger, Ben-Shalom Ido Y, Kopitz Hannes, Pfeiffer-Marek Stefania, Baringhaus Karl-Heinz
Institute for Pharmaceutical and Medicinal Chemistry, Department of Mathematics and Natural Sciences, Heinrich Heine University Düsseldorf , 40225 Düsseldorf, Germany.
R&D/Pre-Development Sciences, Sanofi-Aventis Deutschland GmbH , Industriepark Höchst, 65926 Frankfurt am Main, Germany.
J Chem Theory Comput. 2017 Apr 11;13(4):1495-1502. doi: 10.1021/acs.jctc.7b00014. Epub 2017 Apr 3.
We introduce a computationally efficient approximation of vibrational entropy changes (ΔS) upon binding to biomolecules based on rigidity theory. From constraint network representations of the binding partners, ΔS is estimated from changes in the number of low frequency ("spongy") modes with respect to changes in the networks' coordination number. Compared to ΔS computed by normal-mode analysis (NMA), our approach yields significant and good to fair correlations for data sets of protein-protein and protein-ligand complexes. Our approach could be a valuable alternative to NMA-based ΔS computation in end-point (free) energy methods.
我们基于刚性理论引入了一种计算效率高的方法，用于近似计算与生物分子结合时的振动熵变（ΔS）。从结合伙伴的约束网络表示出发，根据低频（“海绵状”）模式数量相对于网络配位数变化的情况来估计ΔS。与通过正常模式分析（NMA）计算的ΔS相比，我们的方法对于蛋白质 - 蛋白质和蛋白质 - 配体复合物数据集产生了显著且良好到中等的相关性。在端点（自由）能量方法中，我们的方法可能是基于NMA计算ΔS的一种有价值的替代方法。
