Conformational Entropy from Mobile Bond Vectors in Proteins: A Viewpoint that Unifies NMR Relaxation Theory and Molecular Dynamics Simulation Approaches.
Conformational Entropy from Mobile Bond Vectors in Proteins: A Viewpoint that Unifies NMR Relaxation Theory and Molecular Dynamics Simulation Approaches.
复制标题
蛋白质中移动键向量的构象熵：统一 NMR 弛豫理论和分子动力学模拟方法的观点。
DOI：
10.1021/acs.jpcb.0c05846
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Meirovitch,Eva
中科院分区：
文献类型：
--
作者：
Mendelman,Netanel;Zerbetto,Mirco;Buck,Matthias;Meirovitch,Eva
A new method for determining conformational entropy in proteins is reported. Proteins prevail as conformational ensembles,p∝ exp(−u). By selecting a bond vector (e.g., N–H) as a conformation representative, molecular dynamics simulations can provide (relative to a reference structure)pas approximate Boltzmann probability density anduas N–H potential of mean force (POMF). The latter is as accurate as implied by the force field but statistical in character; this limits the insights it can provide and its utilization. Conformational entropy is given exclusively byu. Deriving it from POMFs renders it accurate but statistical in character. Previously, we devised explicit (i.e., analytical but not exact) potentials made of Wigner functions,D0KL, withL≤ 4, which closely resemble the corresponding POMFs in form; hence, they also approach the latter in accuracy. Such potentials can be beneficially characterized/compared in terms of composition, symmetry, and associated order parameters. In this study, we develop a method for deriving conformational entropy from them, which also features the benefits specified above. The method developed is applied to the dimerization of the Rho GTPase-binding domain of plexin-B1. Insights into local ordering, entropy compensation, and features of allostery are gained. In previous work, we developed the slowly relaxing local structure (SRLS) approach for the analysis of NMR relaxation from restricted bond vector motion in proteins. SRLS comprises explicit (restricting) potentials of the kind developed here. It also comprises diffusion tensors describing the local motion and related features of local geometry. The complete model fits experimental data. In future work, the explicit potentials developed here will be inserted unchanged in SRLS-based data fitting, thereby improving the picture of structural dynamics. Given that SRLS is unique in featuring potentials that can closely approach the corresponding POMFs in accuracy, the present study is an important step toward generally improving protein dynamics by NMR relaxation.
