Electronic Polarizability Tunes the Function of the Human Bestrophin 1 Cl- Channel.

IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Journal of Chemical Theory and Computation Pub Date : 2025-01-28 Epub Date: 2025-01-03 DOI:10.1021/acs.jctc.4c01039
Linda X Phan, Aaron P Owji, Tingting Yang, Jason Crain, Mark S P Sansom, Stephen J Tucker
{"title":"Electronic Polarizability Tunes the Function of the Human Bestrophin 1 Cl<sup>-</sup> Channel.","authors":"Linda X Phan, Aaron P Owji, Tingting Yang, Jason Crain, Mark S P Sansom, Stephen J Tucker","doi":"10.1021/acs.jctc.4c01039","DOIUrl":null,"url":null,"abstract":"<p><p>Mechanisms of anion permeation within ion channels and nanopores remain poorly understood. Recent cryo-electron microscopy structures of the human bestrophin 1 Cl<sup>-</sup> channel (hBest1) provide an opportunity to evaluate ion interactions predicted by molecular dynamics (MD) simulations against experimental observations. Here, we implement the fully polarizable force field AMOEBA in MD simulations on different conformations of hBest1. This force field models multipole moments up to the quadrupole. Using this approach, we model key biophysical properties of the channel that can only be simulated when electronic polarization is included in the molecular models and show that Cl<sup>-</sup> permeation through the neck of the pore is achieved through hydrophobic solvation concomitant with partial ion dehydration. Furthermore, we demonstrate how such polarizable simulations can help determine the identity of ion-like densities within high-resolution cryo-EM structures and demonstrate that neglecting polarization places Cl<sup>-</sup> at positions that do not correspond to their experimentally resolved location. Overall, our results demonstrate the importance of including electronic polarization in realistic and physically accurate models of biological systems, especially channels and pores that selectively permeate anions.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"933-942"},"PeriodicalIF":5.5000,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11780730/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Theory and Computation","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.jctc.4c01039","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/3 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Mechanisms of anion permeation within ion channels and nanopores remain poorly understood. Recent cryo-electron microscopy structures of the human bestrophin 1 Cl- channel (hBest1) provide an opportunity to evaluate ion interactions predicted by molecular dynamics (MD) simulations against experimental observations. Here, we implement the fully polarizable force field AMOEBA in MD simulations on different conformations of hBest1. This force field models multipole moments up to the quadrupole. Using this approach, we model key biophysical properties of the channel that can only be simulated when electronic polarization is included in the molecular models and show that Cl- permeation through the neck of the pore is achieved through hydrophobic solvation concomitant with partial ion dehydration. Furthermore, we demonstrate how such polarizable simulations can help determine the identity of ion-like densities within high-resolution cryo-EM structures and demonstrate that neglecting polarization places Cl- at positions that do not correspond to their experimentally resolved location. Overall, our results demonstrate the importance of including electronic polarization in realistic and physically accurate models of biological systems, especially channels and pores that selectively permeate anions.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
电子极化率调节人类strophin 1cl -通道的功能。
阴离子在离子通道和纳米孔内渗透的机制仍然知之甚少。最近的人类strophin 1 Cl-通道(hBest1)的低温电子显微镜结构提供了一个机会来评估由分子动力学(MD)模拟预测的离子相互作用与实验观察。在此,我们在不同构象的hBest1上实现了完全极化力场AMOEBA。这个力场模拟了多极矩直到四极矩。使用这种方法,我们模拟了通道的关键生物物理特性,这些特性只有在分子模型中包含电子极化时才能模拟,并表明Cl-通过孔颈部的渗透是通过疏水溶剂化伴随部分离子脱水实现的。此外,我们证明了这种极化模拟如何有助于确定高分辨率低温电镜结构中离子密度的身份,并证明忽略极化将Cl-置于与实验解析位置不对应的位置。总的来说,我们的结果证明了在生物系统的现实和物理精确模型中包括电子极化的重要性,特别是选择性渗透阴离子的通道和孔。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
期刊最新文献
KinCat: Kinetic Monte Carlo Parallel Computations of Surface Kinetics in Heterogeneous Catalysis. Solving the Scaled Schrödinger Equation with SAC-CI and Electrostatic Force Formalism. Ground, Excited, and Ionized States of the Benzene Molecule. Atomistic Modeling of Methane and Carbon Dioxide Structure I Gas Hydrates under Pressure: Guest Effects and Properties. RxnNet: An AI Framework for Reaction Mechanism Discovery─A Case Study of Carbocations. HighRelax: Physics-Based Refinement of Deep Learning Protein Predictions with Noncanonical Amino Acids.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1