A Modular and Extensible CHARMM-Compatible Model for All-Atom Simulation of Polypeptoids

Alex Berlaga, Kaylyn Torkelson, Aniruddha Seal, Jim Pfaendtner, Andrew L. Ferguson
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Abstract

Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single peptoid chains and their self-assembly into diverse morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General ForceField has demonstrated success in enabling accurate all-atom molecular modeling of the structure and thermodynamic behavior of peptoids. Extension of this force field to new peptoid side chain chemistries has historically required parameterization of new side chain bonded interactions against ab initio and/or experimental data. This fitting protocol improves the accuracy of the force field but is also burdensome and time consuming, and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations wherein arbitrary side chain chemistries within the large family of substituted methyl groups (i.e., -CH3, -CH2R, -CHRR' -CRR'R'') are directly ported from CGenFF without any additional reparameterization. We validate this approach against ab initio calculations and experimental data to to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly-used synthetic side chains, and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.
模块化、可扩展、与 CHARMM 兼容的多肽全原子模拟模型
蛋白胨(N-取代甘氨酸)是一类序列明确的合成拟肽聚合物,其应用领域包括药物输送、催化和生物仿生。经典分子模拟已被用于预测和理解单个蛋白胨链的构象动力学及其组装成片状、管状、球状和纤维状等不同形态的过程。基于 CHARMM 通用力场的 CGenFF-NTOID 模型已成功实现了类蛋白胨结构和热力学行为的精确全原子分子建模。要将该力场扩展到新的蛋白胨侧链化学成分中,历来需要根据 ab initio 和/或实验数据对新的侧链键合相互作用进行参数化。这种拟合规程提高了力场的准确性,但也很费事费时,而且无法将模型扩展到任意的类肽链序列。在这项工作中,我们开发并演示了模块化侧链 CGenFF-NTOID(MoSiC-CGenFF-NTOID),它是 CGenFF-NTOID 的扩展,采用了肽类骨架和侧链参数化的模块化分解,其中取代甲基(即 -CH3、-CH2R、-CHRR' -CRR'R'')大家族中的任意侧链化学结构都直接从 CGenFF 移植而来,无需任何额外参数化。我们根据 ab initio 计算和实验数据验证了这种方法,从而为全部 20 种天然氨基酸侧链和 13 种常用合成侧链建立了 MoSiC-CGenFF-NTOID 模型,并提出了一种可扩展的范式,以有效确定是否可以将新的侧链直接纳入模型,或者是否需要重新拟合 CGenFF 参数。我们向社区免费提供该模型以及自动生成初始结构的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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