Department of Medicinal Chemistry, College of Pharmacy , University of Michigan , 428 Church Street , Ann Arbor , Michigan 48109-1065 , United States.
J Chem Inf Model. 2019 May 28;59(5):2035-2045. doi: 10.1021/acs.jcim.8b00925. Epub 2019 May 2.
In our recent efforts to map protein surfaces using mixed-solvent molecular dynamics (MixMD) (Ghanakota, P.; Carlson, H. A. Moving Beyond Active-Site Detection: MixMD Applied to Allosteric Systems. J. Phys. Chem. B 2016, 120, 8685-8695), we were able to successfully capture active sites and allosteric sites within the top-four most occupied hotspots. In this study, we describe our approach for estimating the thermodynamic profile of the binding sites identified by MixMD. First, we establish a framework for calculating free energies from MixMD simulations, and we compare our approach to alternative methods. Second, we present a means to obtain a relative ranking of the binding sites by their configurational entropy. The theoretical maximum and minimum free energy and entropy values achievable under such a framework along with the limitations of the techniques are discussed. Using this approach, the free energy and relative entropy ranking of the top-four MixMD binding sites were computed and analyzed across our allosteric protein targets: Abl Kinase, Androgen Receptor, Pdk1 Kinase, Farnesyl Pyrophosphate Synthase, Chk1 Kinase, Glucokinase, and Protein Tyrosine Phosphatase 1B.
在我们最近使用混合溶剂分子动力学 (MixMD) 绘制蛋白质表面图的努力中(Ghanakota,P.;Carlson,H. A.超越活性位点检测:MixMD 应用于变构系统。J. Phys. Chem. B 2016,120,8685-8695),我们成功地捕获了前四个最常占据的热点中的活性位点和变构位点。在这项研究中,我们描述了我们用于估计 MixMD 识别的结合位点热力学分布的方法。首先,我们建立了一种从 MixMD 模拟计算自由能的框架,并比较了我们的方法与替代方法。其次,我们提出了一种通过构象熵对结合位点进行相对排序的方法。讨论了在这种框架下,理论上最大和最小自由能以及熵值的可达性以及技术的局限性。使用这种方法,我们计算并分析了前四个 MixMD 结合位点在我们的变构蛋白靶标中的自由能和相对熵排序:Abl 激酶、雄激素受体、Pdk1 激酶、法呢基焦磷酸合酶、Chk1 激酶、葡萄糖激酶和蛋白酪氨酸磷酸酶 1B。