Computational Library Enables Pattern Recognition of Noncovalent Interactions and Application as a Modern Linear Free Energy Relationship

IF 3.3 2区 化学 Q1 CHEMISTRY, ORGANIC The Journal of Organic Chemistry Pub Date : 2024-11-24 DOI:10.1021/acs.joc.4c01790
Jacquelyne A. Read, Tyler E. Ball, Beck R. Miller, Eric N. Jacobsen, Matthew S. Sigman
{"title":"Computational Library Enables Pattern Recognition of Noncovalent Interactions and Application as a Modern Linear Free Energy Relationship","authors":"Jacquelyne A. Read, Tyler E. Ball, Beck R. Miller, Eric N. Jacobsen, Matthew S. Sigman","doi":"10.1021/acs.joc.4c01790","DOIUrl":null,"url":null,"abstract":"A quantitative and predictive understanding of how attractive noncovalent interactions (NCIs) influence functional outcomes is a long-standing goal in mechanistic chemistry. In that context, better comprehension of how substituent effects influence NCI strengths, and the origin of those effects, is still needed. We sought to build a resource capable of elucidating fundamental origins of substituent effects in NCIs and diagnosing NCIs in chemical systems. To accomplish this, a library of 893 NCI energies was calculated encompassing cation−π, anion−π, CH−π, and π–π interactions across 60 different arenes and heteroarenes. The interaction energies (IEs) were calculated using symmetry-adapted perturbation theory (SAPT), which identifies electrostatic, inductive, exchange-repulsive, and dispersive contributions to total IE. This descriptor library provides a comprehensive platform for evaluating substituent effect trends beyond traditional molecular descriptors such as Hammett values, frontier molecular orbital energies, and electrostatic potential, thereby expanding the tools available to analyze modern chemical processes that involve NCIs. To demonstrate the application of this library, three case studies in asymmetric catalysis and supramolecular chemistry are presented. These case studies informed the development of an automated NCI analysis tool, which employs statistical analyses to diagnose a particular NCI in a chemical system of interest.","PeriodicalId":57,"journal":{"name":"The Journal of Organic Chemistry","volume":"67 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Organic Chemistry","FirstCategoryId":"1","ListUrlMain":"https://doi.org/10.1021/acs.joc.4c01790","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ORGANIC","Score":null,"Total":0}
引用次数: 0

Abstract

A quantitative and predictive understanding of how attractive noncovalent interactions (NCIs) influence functional outcomes is a long-standing goal in mechanistic chemistry. In that context, better comprehension of how substituent effects influence NCI strengths, and the origin of those effects, is still needed. We sought to build a resource capable of elucidating fundamental origins of substituent effects in NCIs and diagnosing NCIs in chemical systems. To accomplish this, a library of 893 NCI energies was calculated encompassing cation−π, anion−π, CH−π, and π–π interactions across 60 different arenes and heteroarenes. The interaction energies (IEs) were calculated using symmetry-adapted perturbation theory (SAPT), which identifies electrostatic, inductive, exchange-repulsive, and dispersive contributions to total IE. This descriptor library provides a comprehensive platform for evaluating substituent effect trends beyond traditional molecular descriptors such as Hammett values, frontier molecular orbital energies, and electrostatic potential, thereby expanding the tools available to analyze modern chemical processes that involve NCIs. To demonstrate the application of this library, three case studies in asymmetric catalysis and supramolecular chemistry are presented. These case studies informed the development of an automated NCI analysis tool, which employs statistical analyses to diagnose a particular NCI in a chemical system of interest.

Abstract Image

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
计算库实现了非共价相互作用的模式识别以及现代线性自由能关系的应用
定量和预测性地了解有吸引力的非共价相互作用(NCI)如何影响功能结果是机理化学的一个长期目标。在此背景下,我们仍然需要更好地理解取代基效应如何影响 NCI 强度,以及这些效应的起源。我们试图建立一种资源,能够从根本上阐明 NCI 中取代基效应的起源,并诊断化学体系中的 NCI。为了实现这一目标,我们计算了一个包含 893 种 NCI 能量的资料库,其中包括 60 种不同芳邻和杂芳邻的阳离子-π、阴离子-π、CH-π 和 π-π 相互作用。相互作用能(IEs)是通过对称适配扰动理论(SAPT)计算得出的,该理论可确定总 IE 中的静电、感应、交换排斥和色散贡献。该描述符库为评估取代基效应趋势提供了一个全面的平台,超越了传统的分子描述符(如哈米特值、前沿分子轨道能和静电位),从而扩展了用于分析涉及 NCIs 的现代化学过程的工具。为了展示该库的应用,介绍了不对称催化和超分子化学中的三个案例研究。这些案例研究为自动 NCI 分析工具的开发提供了信息,该工具利用统计分析来诊断相关化学体系中的特定 NCI。
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
The Journal of Organic Chemistry
The Journal of Organic Chemistry 化学-有机化学
CiteScore
6.20
自引率
11.10%
发文量
1467
审稿时长
2 months
期刊介绍: The Journal of Organic Chemistry welcomes original contributions of fundamental research in all branches of the theory and practice of organic chemistry. In selecting manuscripts for publication, the editors place emphasis on the quality and novelty of the work, as well as the breadth of interest to the organic chemistry community.
期刊最新文献
Computational Library Enables Pattern Recognition of Noncovalent Interactions and Application as a Modern Linear Free Energy Relationship Direct Synthesis of Sulfinylated Phenanthrenes via BF3-Promoted Annulation of 2-Alkynyl Biaryls with Arylsulfinic Acids Copper-Catalyzed Three-Component Tandem Cyclization for One-Pot Synthesis of Indole-Benzofuran Bis-Heterocycles Photocatalytic Consecutive Photoinduced Electron Transfer-Enabled C(sp3)–H Pyridylation of Dihydroquinoxalin-2-ones Asymmetric Synthesis of Taiwaniaquinone H via a Late-Stage Oxidative Decarboxylation
×
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:481959085
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