论文标题

Martinize2和苦艾酒:拓扑生成的统一框架

Martinize2 and Vermouth: Unified Framework for Topology Generation

论文作者

Kroon, Peter C., Grünewald, Fabian, Barnoud, Jonathan, van Tilburg, Marco, Brasnett, Chris, Souza, Paulo C. T., Wassenaar, Tsjerk A., Marrink, Siewert-Jan

论文摘要

力场和计算机硬件开发的持续进展使得能够使用分子动力学(MD)模拟日益复杂的系统,以达到细胞复杂性的最终目标。同时,高通量(HT)模拟的理性设计是MD的另一个前沿。在这些领域,马提尼酒的粗粒磁场,尤其是最新版本(即V3),因为它提供了增强的时空分辨率,因此正在积极探索。但是,与先前版本相伴的马提尼族力场制备模拟的自动化工具并不是针对复杂蜂窝系统的HT模拟或研究。因此,它们成为主要限制因素。为了解决这些缺点,我们介绍了开源的苦艾酒图书馆。 Vermouth旨在成为开发程序的统一框架,这些程序准备,运行和分析了Martini模拟复杂系统的模拟。为了展示苦艾酒库的力量,将Martinize2程序显示为Martinize脚本的概括,最初旨在设置蛋白质的模拟。与以前的版本相反,Martinize2自动处理蛋白质和翻译后修饰中的质子化状态,为弹性网络(EN)等微调结构偏见提供了更多选择,并可以转换非蛋白质分子,例如配体。最后,Martinize2用于两个高复杂的基准测试。整个I-Tasser蛋白模板数据库以及从Alphafold蛋白结构数据库中的200,000个结构的子集转换为CG分辨率,我们说明了输入结构质量的检查如何保护高通量应用程序。

Ongoing advances in force field and computer hardware development enable the use of molecular dynamics (MD) to simulate increasingly complex systems with the ultimate goal of reaching cellular complexity. At the same time, rational design by high-throughput (HT) simulations is another forefront of MD. In these areas, the Martini coarse-grained force field, especially the latest version (i.e. v3), is being actively explored because it offers an enhanced spatial-temporal resolution. However, the automation tools for preparing simulations with the Martini force field, accompanying the previous version, were not designed for HT simulations or studies of complex cellular systems. Therefore, they become a major limiting factor. To address these shortcomings, we present the open-source Vermouth python library. Vermouth is designed to become the unified framework for developing programs, which prepare, run, and analyze Martini simulations of complex systems. To demonstrate the power of the Vermouth library, the Martinize2 program is showcased as a generalization of the martinize script, originally aimed to set up simulations of proteins. In contrast to the previous version, Martinize2 automatically handles protonation states in proteins and post-translation modifications, offers more options to fine-tune structural biases such as the elastic network (EN), and can convert non-protein molecules such as ligands. Finally, Martinize2 is used in two high-complexity benchmarks. The entire I-TASSER protein template database as well as a subset of 200,000 structures from the AlphaFold Protein Structure Database are converted to CG resolution and we illustrate how the checks on input structure quality can safeguard high-throughput applications.

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