Facilitating Transition State Search with Minimal Conformational Sampling Using Reaction Graph.

IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Journal of Chemical Theory and Computation Pub Date : 2025-03-11 Epub Date: 2025-02-25 DOI:10.1021/acs.jctc.4c01692
Kyunghoon Lee, Jinwon Lee, Shinyoung Park, Woo Youn Kim
{"title":"Facilitating Transition State Search with Minimal Conformational Sampling Using Reaction Graph.","authors":"Kyunghoon Lee, Jinwon Lee, Shinyoung Park, Woo Youn Kim","doi":"10.1021/acs.jctc.4c01692","DOIUrl":null,"url":null,"abstract":"<p><p>Elucidating transition states (TSs) is crucial for understanding chemical reactions. The reliability of traditional TS search approaches depends on input conformations that require significant effort to prepare. Previous automated methods for generating input reaction conformations typically involve extensive exploration of a large conformational space. Such exhaustive search can be complicated by the rapid growth of the conformational space, especially for reactions involving many rotatable bonds, multiple reacting molecules, and numerous bond formations and dissociations. To address this problem, we propose a new approach that generates reaction conformations for TS searches with minimal reliance on sampling. This method constructs a pseudo-TS structure based on a reaction graph containing bond formation and dissociation information and modifies it to produce reactant and product conformations. Tested on three different benchmarks, our method consistently generated suitable conformations without necessitating extensive sampling, demonstrating its potential to significantly improve the applicability of automated TS searches. This approach offers a valuable tool for a broad range of applications such as reaction mechanism analysis and network exploration.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"2487-2500"},"PeriodicalIF":5.5000,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","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.4c01692","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/25 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Elucidating transition states (TSs) is crucial for understanding chemical reactions. The reliability of traditional TS search approaches depends on input conformations that require significant effort to prepare. Previous automated methods for generating input reaction conformations typically involve extensive exploration of a large conformational space. Such exhaustive search can be complicated by the rapid growth of the conformational space, especially for reactions involving many rotatable bonds, multiple reacting molecules, and numerous bond formations and dissociations. To address this problem, we propose a new approach that generates reaction conformations for TS searches with minimal reliance on sampling. This method constructs a pseudo-TS structure based on a reaction graph containing bond formation and dissociation information and modifies it to produce reactant and product conformations. Tested on three different benchmarks, our method consistently generated suitable conformations without necessitating extensive sampling, demonstrating its potential to significantly improve the applicability of automated TS searches. This approach offers a valuable tool for a broad range of applications such as reaction mechanism analysis and network exploration.

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
利用反应图简化最小构象抽样的过渡态搜索。
阐明过渡态(TSs)对于理解化学反应至关重要。传统TS搜索方法的可靠性取决于输入构象,这需要大量的准备工作。以前生成输入反应构象的自动化方法通常涉及对大构象空间的广泛探索。由于构象空间的快速增长,特别是对于涉及许多可旋转键、多个反应分子以及许多键形成和解离的反应,这种详尽的搜索可能会变得复杂。为了解决这个问题,我们提出了一种新的方法,在最小依赖采样的情况下为TS搜索生成反应构象。该方法基于包含键形成和解离信息的反应图构建伪ts结构,并对其进行修改以产生反应物和生成物的构象。在三个不同的基准测试中,我们的方法一致地生成了合适的构象,而不需要大量的采样,这表明它有潜力显著提高自动TS搜索的适用性。这种方法为反应机理分析和网络探测等广泛应用提供了有价值的工具。
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
Thermodynamic Activation Parameters for Chemical Reactions in Enzymes and Solution from Computer Simulations at a Single Temperature. Automatic Refinement of Force Fields Based on Phase Diagrams. Using Weighted and Chopped Rectangular Collocation Methods with Tensor-Product Contracted Bases To Compute Vibrational Spectra: Avoiding Quadrature Precessional Dynamics of Octahedra in CsPbBr3 Markov State Models for Tracking Reaction Dynamics on Catalytic Nanoparticles
×
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