使用蒙特卡罗采样表征蛋白质质子化微状态

Characterizing Protein Protonation Microstates Using Monte Carlo Sampling.

作者信息

Khaniya Umesh, Mao Junjun, Wei Rongmei Judy, Gunner M R

机构信息

Department of Physics, City College of New York, New York, New York 10031, United States.

Department of Physics, The Graduate Center, City University of New York, New York, New York 10016, United States.

出版信息

J Phys Chem B. 2022 Apr 7;126(13):2476-2485. doi: 10.1021/acs.jpcb.2c00139. Epub 2022 Mar 28.

Abstract

Proteins are polyelectrolytes with acidic and basic amino acids Asp, Glu, Arg, Lys, and His, making up ≈25% of the residues. The protonation state of residues, cofactors, and ligands defines a "protonation microstate". In an ensemble of proteins some residues will be ionized and others neutral, leading to a mixture of protonation microstates rather than in a single one as is often assumed. The microstate distribution changes with pH. The protein environment also modifies residue proton affinity so microstate distributions change in different reaction intermediates or as ligands are bound. Particular protonation microstates may be required for function, while others exist simply because there are many states with similar energy. Here, the protonation microstates generated in Monte Carlo sampling in MCCE are characterized in HEW lysozyme as a function of pH and bacterial photosynthetic reaction centers (RCs) in different reaction intermediates. The lowest energy and highest probability microstates are compared. The Δ, Δ, and Δ between the four protonation states of Glu35 and Asp52 in lysozyme are shown to be calculated with reasonable precision. At pH 7 the lysozyme charge ranges from 6 to 10, with 24 accepted protonation microstates, while RCs have ≈50,000. A weighted Pearson correlation analysis shows coupling between residue protonation states in RCs and how they change when the quinone in the Q site is reduced. Protonation microstates can be used to define input MD parameters and provide insight into the motion of protons coupled to reactions.

摘要

蛋白质是带有酸性和碱性氨基酸(天冬氨酸、谷氨酸、精氨酸、赖氨酸和组氨酸)的聚电解质,这些氨基酸约占氨基酸残基的25%。残基、辅因子和配体的质子化状态定义了一种“质子化微状态”。在一组蛋白质中,一些残基会被电离,而另一些则呈中性,从而导致质子化微状态的混合,而不是像通常所假设的那样处于单一状态。微状态分布会随pH值变化。蛋白质环境也会改变残基质子亲和力,因此微状态分布在不同的反应中间体中或随着配体结合而发生变化。功能可能需要特定的质子化微状态,而其他状态的存在仅仅是因为有许多能量相似的状态。在此,通过MCCE中的蒙特卡罗采样生成的质子化微状态在溶菌酶中作为pH值的函数以及在不同反应中间体中的细菌光合反应中心(RCs)进行了表征。比较了最低能量和最高概率的微状态。溶菌酶中Glu35和Asp52的四种质子化状态之间的ΔG、ΔH和ΔS被证明能够以合理的精度进行计算。在pH 7时,溶菌酶的电荷范围为6至10,有24种可接受的质子化微状态,而反应中心约有50,000种。加权皮尔逊相关分析显示了反应中心中残基质子化状态之间的耦合以及当Q位点中的醌被还原时它们如何变化。质子化微状态可用于定义输入的分子动力学(MD)参数,并深入了解与反应耦合的质子运动。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fd5/8997239/33b197c261af/jp2c00139_0001.jpg

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