Jacquelyne A. Read, Tyler E. Ball, Beck R. Miller, Eric N. Jacobsen, Matthew S. Sigman
{"title":"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","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":"{\"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}","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}
Computational Library Enables Pattern Recognition of Noncovalent Interactions and Application as a Modern Linear Free Energy Relationship
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.
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.