Suppr超能文献

探索pH依赖性的主/客体结合亲和力。

Exploring pH Dependent Host/Guest Binding Affinities.

作者信息

Paul Thomas J, Vilseck Jonah Z, Hayes Ryan L, Brooks Charles L

出版信息

J Phys Chem B. 2020 Jul 30;124(30):6520-6528. doi: 10.1021/acs.jpcb.0c03671. Epub 2020 Jul 22.

Abstract

When the electrostatic environment surrounding binding partners changes between unbound and bound states, the net uptake or release of a proton is possible by either binding partner. This process is pH-dependent in that the free energy required to uptake or release the proton varies with pH. This pH-dependence is typically not considered in conventional free energy methods where the use of fixed protonation states is the norm. In the present paper, we apply a simple two-step approach to calculate the pH-dependent binding free energy of a model cucubit[7]uril host/guest system. By use of λ-dynamics with an enhanced sampling protocol, adaptive landscape flattening, p shifts and reference binding free energies upon complexation were determined. This information enables the construction of pH-dependent binding profiles that accurately capture the p shifts and reproduce binding free energies at the different pH conditions that were observed experimentally. Our calculations illustrate a general framework for computing pH-dependent binding free energies but also point to some issues in modeling the molecular charge distributions within this series of molecules with CGenFF. However, by introducing some minor charge modifications to the CGenFF force field, we saw significant improvement in accuracy of the calculated p shifts.

摘要

当结合配体周围的静电环境在未结合态和结合态之间发生变化时,任何一个结合配体都有可能净吸收或释放一个质子。这个过程依赖于pH,因为吸收或释放质子所需的自由能会随pH变化。在传统的自由能方法中,通常使用固定的质子化状态,所以这种pH依赖性通常不被考虑。在本文中,我们应用一种简单的两步法来计算模型葫芦[7]脲主体/客体系统的pH依赖性结合自由能。通过使用具有增强采样协议的λ动力学、自适应势能面平坦化,确定了络合时的p值变化和参考结合自由能。这些信息使得能够构建pH依赖性结合曲线,该曲线能准确捕捉p值变化,并重现实验观察到的不同pH条件下的结合自由能。我们的计算说明了计算pH依赖性结合自由能的一般框架,但也指出了使用CGenFF对这一系列分子内分子电荷分布进行建模时存在的一些问题。然而,通过对CGenFF力场进行一些微小的电荷修正,我们发现计算得到的p值变化的准确性有了显著提高。

相似文献

1
Exploring pH Dependent Host/Guest Binding Affinities.探索pH依赖性的主/客体结合亲和力。
J Phys Chem B. 2020 Jul 30;124(30):6520-6528. doi: 10.1021/acs.jpcb.0c03671. Epub 2020 Jul 22.

引用本文的文献

1
How to Sample Dozens of Substitutions per Site with λ Dynamics.如何使用 λ 动力学对每个位点进行数十个替换进行抽样。
J Chem Theory Comput. 2024 Jul 23;20(14):6098-6110. doi: 10.1021/acs.jctc.4c00514. Epub 2024 Jul 8.
3
Constant pH molecular dynamics simulations: Current status and recent applications.恒 pH 分子动力学模拟:现状与最新应用。
Curr Opin Struct Biol. 2022 Dec;77:102498. doi: 10.1016/j.sbi.2022.102498. Epub 2022 Nov 18.
6
Facile Fabrication of Protein-Macrocycle Frameworks.蛋白质-大环框架的简易构建。
J Am Chem Soc. 2021 Feb 3;143(4):1896-1907. doi: 10.1021/jacs.0c10697. Epub 2021 Jan 20.

本文引用的文献

3
Cucurbit[7]uril-Dimethyllysine Recognition in a Model Protein.葫芦脲-二甲基赖氨酸在模型蛋白中的识别。
Angew Chem Int Ed Engl. 2018 Jun 11;57(24):7126-7130. doi: 10.1002/anie.201803232. Epub 2018 May 14.

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