Suppr超能文献

开发用于分子建模的泛硫乙胺力场库。

Development of a Pantetheine Force Field Library for Molecular Modeling.

机构信息

Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, California 92697, United States.

Department of Chemistry, University of California, Irvine, Irvine, California 92697, United States.

出版信息

J Chem Inf Model. 2021 Feb 22;61(2):856-868. doi: 10.1021/acs.jcim.0c01384. Epub 2021 Feb 3.

Abstract

Pantetheine is ubiquitous in nature in various forms of pantetheine-containing ligands (PCLs), including coenzyme A and phosphopantetheine. Lack of scalable force field libraries for PCLs has hampered the computational studies of biological macromolecules containing PCLs. We describe here the development of the first generation Pantetheine Force Field (PFF) library that is compatible with Amber force fields; parameterized using Gasteiger, AM1-BCC, or RESP charging methods combined with and parameter sets. In addition, a "plug-and-play" strategy was employed to enable the systematic charging of computationally expensive molecules sharing common substructural motifs. The validation studies performed on the PFF library showed promising performance where molecular dynamics (MD) simulations results were compared with experimental data of three representative systems. The PFF library represents the first force field library capable of modeling systems containing PCLs and will aid in various applications including protein engineering and drug discovery.

摘要

泛酰巯基乙胺在自然界中以各种形式的含泛酰巯基乙胺配体(PCLs)存在,包括辅酶 A 和磷酸泛酰巯基乙胺。缺乏可扩展的 PCL 力场库阻碍了含 PCL 的生物大分子的计算研究。我们在这里描述了第一代 Pantetheine 力场(PFF)库的开发,该库与 Amber 力场兼容;使用 Gasteiger、AM1-BCC 或 RESP 充电方法以及 和 参数集进行参数化。此外,还采用了“即插即用”策略,以实现共享常见子结构模体的计算昂贵分子的系统充电。对 PFF 库进行的验证研究表明,性能有很大的提升,其中分子动力学(MD)模拟结果与三个代表性系统的实验数据进行了比较。PFF 库代表了第一个能够模拟含 PCL 系统的力场库,将有助于各种应用,包括蛋白质工程和药物发现。

相似文献

1
Development of a Pantetheine Force Field Library for Molecular Modeling.开发用于分子建模的泛硫乙胺力场库。
J Chem Inf Model. 2021 Feb 22;61(2):856-868. doi: 10.1021/acs.jcim.0c01384. Epub 2021 Feb 3.

引用本文的文献

5

本文引用的文献

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验