Departamento de Química Física, Universidad de Murcia, 30100 Murcia, Spain.
Dipartimento di Scienze Matematiche, Informatiche e Fisiche, Università di Udine, 33100 Udine, Italy.
Phys Chem Chem Phys. 2024 Sep 11;26(35):23213-23227. doi: 10.1039/d4cp02564d.
The characterization of the statistical ensemble of conformations of intrinsically disordered regions (IDRs) is a great challenge both from experimental and computational points of view. In this respect, a number of protocols have been developed using molecular dynamics (MD) simulations to sample the huge conformational space of the molecule. In this work, we consider one of the best methods available, replica exchange solute tempering (REST), as a reference to compare the results obtained using this method with the results obtained using other methods, in terms of experimentally measurable quantities. Along with the methods assessed, we propose here a novel protocol called probabilistic MD chain growth (PMD-CG), which combines the flexible-meccano and hierarchical chain growth methods with the statistical data obtained from tripeptide MD trajectories as the starting point. The system chosen for testing is a 20-residue region from the C-terminal domain of the p53 tumor suppressor protein (p53-CTD). Our results show that PMD-CG provides an ensemble of conformations extremely quickly, after suitable computation of the conformational pool for all peptide triplets of the IDR sequence. The measurable quantities computed on the ensemble of conformations agree well with those based on the REST conformational ensemble.
从实验和计算的角度来看,对无规则区域(IDR)构象的统计集合进行特征描述是一个巨大的挑战。在这方面,已经开发了许多使用分子动力学(MD)模拟来采样分子巨大构象空间的协议。在这项工作中,我们考虑了一种可用的最佳方法,即复制交换溶质调温(REST),作为参考,以根据实验可测量的量,比较使用该方法获得的结果与使用其他方法获得的结果。除了评估的方法外,我们还在这里提出了一种称为概率 MD 链生长(PMD-CG)的新协议,该协议将灵活机械和层次链生长方法与从三肽 MD 轨迹获得的统计数据结合起来作为起点。选择用于测试的系统是 p53 肿瘤抑制蛋白(p53-CTD)C 末端结构域的 20 残基区域。我们的结果表明,PMD-CG 可以在适当地计算 IDR 序列中所有肽三肽的构象池之后,非常快速地提供构象集合。在构象集合上计算的可测量量与基于 REST 构象集合的可测量量非常吻合。