Department of Computer Science, Penn State Harrisburg, Middletown, PA 17057, United States of America.
Department and Mathematics and Computer Sceince, Westmont College, Santa Barbara, CA 93108, United States of America.
Phys Biol. 2023 May 30;20(4). doi: 10.1088/1478-3975/acd6cd.
Classical normal mode analysis (cNMA) is a standard method for studying the equilibrium vibrations of macromolecules. A major limitation of cNMA is that it requires a cumbersome step of energy minimization that also alters the input structure significantly. Variants of normal mode analysis (NMA) exist that perform NMA directly on PDB structures without energy minimization, while maintaining most of the accuracy of cNMA. Spring-based NMA (sbNMA) is such a model. sbNMA uses an all-atom force field as cNMA does, which includes bonded terms such as bond stretching, bond angle bending, torsional, improper, and non-bonded terms such as van der Waals interactions. Electrostatics was not included in sbNMA because it introduced negative spring constants. In this work, we present a way to incorporate most of the electrostatic contributions in normal mode computations, which marks another significant step toward a free-energy-based elastic network model (ENM) for NMA. The vast majority of ENMs are entropy models. One significance of having a free energy-based model for NMA is that it allows one to study the contributions of both entropy and enthalpy. As an application, we apply this model to study the binding stability between SARS-COV2 and angiotensin converting enzyme 2 (or ACE2). Our results show that the stability at the binding interface is contributed nearly equally by hydrophobic interactions and hydrogen bonds.
经典正则模态分析（cNMA）是研究大分子平衡振动的标准方法。cNMA 的一个主要限制是它需要进行繁琐的能量最小化步骤，这也会显著改变输入结构。存在一些正则模态分析（NMA）的变体，可以直接在 PDB 结构上进行 NMA，而无需能量最小化，同时保持 cNMA 的大部分准确性。基于弹簧的 NMA（sbNMA）就是这样一种模型。sbNMA 像 cNMA 一样使用全原子力场，其中包括键伸缩、键角弯曲、扭转、非规范和非键相互作用，如范德华相互作用。静电相互作用没有包含在 sbNMA 中，因为它引入了负的弹簧常数。在这项工作中，我们提出了一种在正则模态计算中纳入大部分静电贡献的方法，这标志着朝着基于自由能的弹性网络模型（ENM）进行 NMA 的又一个重要步骤。绝大多数 ENM 都是熵模型。对于 NMA 具有基于自由能的模型的一个重要意义是，它允许研究熵和焓的贡献。作为应用，我们将该模型应用于研究 SARS-COV2 与血管紧张素转化酶 2（或 ACE2）之间的结合稳定性。我们的结果表明，结合界面的稳定性几乎由疏水力和氢键相等地贡献。
