Mendelman Netanel, Zerbetto Mirco, Buck Matthias, Meirovitch Eva
The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 52900 Israel.
Department of Chemical Sciences, University of Padova, Padova 35131, Italy.
J Phys Chem B. 2020 Oct 22;124(42):9323-9334. doi: 10.1021/acs.jpcb.0c05846. Epub 2020 Oct 13.
A new method for determining conformational entropy in proteins is reported. Proteins prevail as conformational ensembles, ∝ exp(-). By selecting a bond vector (e.g., N-H) as a conformation representative, molecular dynamics simulations can provide (relative to a reference structure) as approximate Boltzmann probability density and as 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 by . 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, , with ≤ 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.
报道了一种测定蛋白质构象熵的新方法。蛋白质以构象集合体的形式存在,∝ exp(-)。通过选择一个键向量(如N-H)作为构象代表,分子动力学模拟可以提供(相对于参考结构)作为近似玻尔兹曼概率密度,以及作为N-H平均力势(POMF)。后者与力场所暗示的一样准确,但具有统计性质;这限制了它所能提供的见解及其应用。构象熵仅由给出。从POMF推导它使其准确但具有统计性质。此前,我们设计了由维格纳函数组成的显式(即解析但不精确)势,,其中≤ 4,其形式与相应的POMF非常相似;因此,它们在精度上也接近后者。这种势可以根据组成、对称性和相关序参量进行有益的表征/比较。在本研究中,我们开发了一种从它们推导构象熵的方法,该方法也具有上述优点。所开发的方法应用于丛状蛋白B1的Rho GTPase结合结构域的二聚化。获得了对局部有序性、熵补偿和变构特征的见解。在之前的工作中,我们开发了缓慢弛豫局部结构(SRLS)方法,用于分析蛋白质中受限键向量运动的NMR弛豫。SRLS包括这里开发的那种显式(限制)势。它还包括描述局部运动和局部几何相关特征的扩散张量。完整模型拟合实验数据。在未来的工作中,这里开发的显式势将原封不动地插入基于SRLS的数据拟合中,从而改善结构动力学的图景。鉴于SRLS在具有能够在精度上紧密接近相应POMF的势方面是独一无二的,本研究是通过NMR弛豫普遍改善蛋白质动力学的重要一步。