Beijing National Laboratory for Molecular Sciences, Institute of Theoretical and Computational Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China.
J Chem Inf Model. 2021 Oct 25;61(10):5212-5222. doi: 10.1021/acs.jcim.1c00844. Epub 2021 Sep 27.
Biomacromolecules often undergo significant conformational rearrangements during function. In proteins, these motions typically consist in nontrivial, concerted rearrangement of multiple flexible regions. Mechanistic, thermodynamics, and kinetic predictions can be obtained via molecular dynamics simulations, provided that the simulation time is at least comparable to the relevant time scale of the process of interest. Because of the substantial computational cost, however, plain MD simulations often have difficulty in obtaining sufficient statistics for converged estimates, requiring the use of more-advanced techniques. Central in many enhanced sampling methods is the definition of a small set of relevant degrees of freedom (collective variables) that are able to describe the transitions between different metastable states of the system. The harmonic linear discriminant analysis (HLDA) has been shown to be useful for constructing low-dimensional collective variables in various complex systems. Here, we apply HLDA to study the free-energy landscape of a monomeric protein around its native state. More precisely, we study the K-Ras protein bound to GTP, focusing on two flexible loops and on the region associated with oncogenic mutations. We perform microsecond-long biased simulations on the wild type and on G12C, G12D, G12 V mutants, describe the resulting free-energy landscapes, and compare our predictions with previous experimental and computational studies. The fast interconversion between open and closed macroscopic states and their similar thermodynamic stabilities are observed. The mutation-induced effects include the alternations of the relative stabilities of different conformational states and the introduction of many microscopic metastable states. Together, our results demonstrate the applicability of the HLDA-based protocol for the conformational sampling of multiple flexible regions in folded proteins.
生物大分子在功能过程中经常经历显著的构象重排。在蛋白质中，这些运动通常由多个柔性区域的非平凡、协调的重排组成。通过分子动力学模拟可以获得机制、热力学和动力学预测，前提是模拟时间至少与感兴趣过程的相关时间尺度相当。然而，由于计算成本高，普通 MD 模拟通常难以获得收敛估计所需的足够统计数据，需要使用更先进的技术。许多增强采样方法的核心是定义一组能够描述系统不同亚稳态之间跃迁的相关自由度（集合变量）。谐波线性判别分析（HLDA）已被证明在各种复杂系统中构建低维集合变量非常有用。在这里，我们应用 HLDA 研究单体蛋白质在其天然状态附近的自由能景观。更准确地说，我们研究了与 GTP 结合的 K-Ras 蛋白，重点研究了两个柔性环和与致癌突变相关的区域。我们对野生型和 G12C、G12D、G12V 突变体进行了微秒长的有偏模拟，描述了由此产生的自由能景观，并将我们的预测与以前的实验和计算研究进行了比较。观察到开放和闭合宏观状态之间的快速相互转换及其相似的热力学稳定性。突变诱导的影响包括不同构象状态的相对稳定性的改变和许多微观亚稳态的引入。总之，我们的结果证明了基于 HLDA 的协议在折叠蛋白质中多个柔性区域构象采样中的适用性。
