{"title":"化学优化的逻辑","authors":"David C. Kombo, and , Matthew J. LaMarche*, ","doi":"10.1021/acs.jmedchem.5c0044510.1021/acs.jmedchem.5c00445","DOIUrl":null,"url":null,"abstract":"<p >During multiparameter chemical optimization, molecular capabilities increase as hits evolve into leads and development candidates. Like retrosynthetic analysis, where target molecules are transformed into structurally simplified starting materials, we introduce retro-optimization analysis, transforming sophisticated development candidates into less capable leads and hits. To retrospectively understand the logic of optimization in discovery campaigns, we enumerated a matched molecular pair network and compared the actual route of optimization taken to alternative theoretical routes of optimization. We noted differences in the network and properties of the lead molecule compared to those of alternatives. We identified substructures of the evolving ligand, named “optimizons,” and tracked their emphasis and discovery. While we initially defined and illustrated these methods for a single project, our expansion to three additional discovery projects and three external data sets proved consistent. We retrospectively define the logic of optimization at the project, molecular, and submolecular levels to prospectively guide current and future optimization campaigns.</p>","PeriodicalId":46,"journal":{"name":"Journal of Medicinal Chemistry","volume":"68 11","pages":"11572–11585 11572–11585"},"PeriodicalIF":6.8000,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Logic of Chemical Optimization\",\"authors\":\"David C. Kombo, and , Matthew J. LaMarche*, \",\"doi\":\"10.1021/acs.jmedchem.5c0044510.1021/acs.jmedchem.5c00445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >During multiparameter chemical optimization, molecular capabilities increase as hits evolve into leads and development candidates. Like retrosynthetic analysis, where target molecules are transformed into structurally simplified starting materials, we introduce retro-optimization analysis, transforming sophisticated development candidates into less capable leads and hits. To retrospectively understand the logic of optimization in discovery campaigns, we enumerated a matched molecular pair network and compared the actual route of optimization taken to alternative theoretical routes of optimization. We noted differences in the network and properties of the lead molecule compared to those of alternatives. We identified substructures of the evolving ligand, named “optimizons,” and tracked their emphasis and discovery. While we initially defined and illustrated these methods for a single project, our expansion to three additional discovery projects and three external data sets proved consistent. We retrospectively define the logic of optimization at the project, molecular, and submolecular levels to prospectively guide current and future optimization campaigns.</p>\",\"PeriodicalId\":46,\"journal\":{\"name\":\"Journal of Medicinal Chemistry\",\"volume\":\"68 11\",\"pages\":\"11572–11585 11572–11585\"},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2025-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Medicinal Chemistry\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.jmedchem.5c00445\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medicinal Chemistry","FirstCategoryId":"3","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jmedchem.5c00445","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
During multiparameter chemical optimization, molecular capabilities increase as hits evolve into leads and development candidates. Like retrosynthetic analysis, where target molecules are transformed into structurally simplified starting materials, we introduce retro-optimization analysis, transforming sophisticated development candidates into less capable leads and hits. To retrospectively understand the logic of optimization in discovery campaigns, we enumerated a matched molecular pair network and compared the actual route of optimization taken to alternative theoretical routes of optimization. We noted differences in the network and properties of the lead molecule compared to those of alternatives. We identified substructures of the evolving ligand, named “optimizons,” and tracked their emphasis and discovery. While we initially defined and illustrated these methods for a single project, our expansion to three additional discovery projects and three external data sets proved consistent. We retrospectively define the logic of optimization at the project, molecular, and submolecular levels to prospectively guide current and future optimization campaigns.
期刊介绍:
The Journal of Medicinal Chemistry is a prestigious biweekly peer-reviewed publication that focuses on the multifaceted field of medicinal chemistry. Since its inception in 1959 as the Journal of Medicinal and Pharmaceutical Chemistry, it has evolved to become a cornerstone in the dissemination of research findings related to the design, synthesis, and development of therapeutic agents.
The Journal of Medicinal Chemistry is recognized for its significant impact in the scientific community, as evidenced by its 2022 impact factor of 7.3. This metric reflects the journal's influence and the importance of its content in shaping the future of drug discovery and development. The journal serves as a vital resource for chemists, pharmacologists, and other researchers interested in the molecular mechanisms of drug action and the optimization of therapeutic compounds.