{"title":"通过生成式化学信息学和配体-蛋白质结构进行分子调整,促进合理药物开发。","authors":"Ashwini K Nangia","doi":"10.1016/j.bioorg.2024.107920","DOIUrl":null,"url":null,"abstract":"<p><p>The purpose of this review is two-fold: (1) to summarize artificial intelligence and machine learning approaches and document the role of ligand-protein structures in directing drug discovery; (2) to present examples of drugs from the recent literature (past decade) of case studies where such strategies have been applied to accelerate the discovery pipeline. Compared to 50 years ago when drug discovery was largely a synthetic chemist driven research exercise, today a holistic approach needs to be adopted with seamless integration between synthetic and medicinal chemistry, supramolecular complexes, computations, artificial intelligence, machine learning, structural biology, chemical biology, diffraction analytical tools, drugs databases, and pharmacology. The urgency for an integrated and collaborative platform to accelerate drug discovery in an academic setting is emphasized.</p>","PeriodicalId":257,"journal":{"name":"Bioorganic Chemistry","volume":"153 ","pages":"107920"},"PeriodicalIF":4.5000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Molecular tweaking by generative cheminformatics and ligand-protein structures for rational drug discovery.\",\"authors\":\"Ashwini K Nangia\",\"doi\":\"10.1016/j.bioorg.2024.107920\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The purpose of this review is two-fold: (1) to summarize artificial intelligence and machine learning approaches and document the role of ligand-protein structures in directing drug discovery; (2) to present examples of drugs from the recent literature (past decade) of case studies where such strategies have been applied to accelerate the discovery pipeline. Compared to 50 years ago when drug discovery was largely a synthetic chemist driven research exercise, today a holistic approach needs to be adopted with seamless integration between synthetic and medicinal chemistry, supramolecular complexes, computations, artificial intelligence, machine learning, structural biology, chemical biology, diffraction analytical tools, drugs databases, and pharmacology. The urgency for an integrated and collaborative platform to accelerate drug discovery in an academic setting is emphasized.</p>\",\"PeriodicalId\":257,\"journal\":{\"name\":\"Bioorganic Chemistry\",\"volume\":\"153 \",\"pages\":\"107920\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bioorganic Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1016/j.bioorg.2024.107920\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioorganic Chemistry","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1016/j.bioorg.2024.107920","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/28 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Molecular tweaking by generative cheminformatics and ligand-protein structures for rational drug discovery.
The purpose of this review is two-fold: (1) to summarize artificial intelligence and machine learning approaches and document the role of ligand-protein structures in directing drug discovery; (2) to present examples of drugs from the recent literature (past decade) of case studies where such strategies have been applied to accelerate the discovery pipeline. Compared to 50 years ago when drug discovery was largely a synthetic chemist driven research exercise, today a holistic approach needs to be adopted with seamless integration between synthetic and medicinal chemistry, supramolecular complexes, computations, artificial intelligence, machine learning, structural biology, chemical biology, diffraction analytical tools, drugs databases, and pharmacology. The urgency for an integrated and collaborative platform to accelerate drug discovery in an academic setting is emphasized.
期刊介绍:
Bioorganic Chemistry publishes research that addresses biological questions at the molecular level, using organic chemistry and principles of physical organic chemistry. The scope of the journal covers a range of topics at the organic chemistry-biology interface, including: enzyme catalysis, biotransformation and enzyme inhibition; nucleic acids chemistry; medicinal chemistry; natural product chemistry, natural product synthesis and natural product biosynthesis; antimicrobial agents; lipid and peptide chemistry; biophysical chemistry; biological probes; bio-orthogonal chemistry and biomimetic chemistry.
For manuscripts dealing with synthetic bioactive compounds, the Journal requires that the molecular target of the compounds described must be known, and must be demonstrated experimentally in the manuscript. For studies involving natural products, if the molecular target is unknown, some data beyond simple cell-based toxicity studies to provide insight into the mechanism of action is required. Studies supported by molecular docking are welcome, but must be supported by experimental data. The Journal does not consider manuscripts that are purely theoretical or computational in nature.
The Journal publishes regular articles, short communications and reviews. Reviews are normally invited by Editors or Editorial Board members. Authors of unsolicited reviews should first contact an Editor or Editorial Board member to determine whether the proposed article is within the scope of the Journal.