{"title":"Multidimensional QSAR: Moving from three‐ to five‐dimensional concepts","authors":"A. Vedani, M. Dobler","doi":"10.1002/1521-3838(200210)21:4<382::AID-QSAR382>3.0.CO;2-L","DOIUrl":null,"url":null,"abstract":"Quantitative structure-activity relationships (QSAR) is an area of computational research which correlates structural features and quantities such as the binding affinity, toxic potential, or pharmacokinetic properties of an existing or a hypothetical molecule. This correlation may be obtained by analyzing topology and fields of the molecules of interest or by simulating their spatial interactions with biological receptors or models thereof. While 3D-QSAR simulations allow for a specific interaction scheme with the virtual receptor, they presume the knowledge of the bioactive conformation of the ligand molecules and require a sophisticated guess about manifestation and magnitude of the associated induced fit – the adaptation of the receptor binding pocket to the individual ligand topology.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2002-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative Structure-activity Relationships","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/1521-3838(200210)21:4<382::AID-QSAR382>3.0.CO;2-L","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 35
Abstract
Quantitative structure-activity relationships (QSAR) is an area of computational research which correlates structural features and quantities such as the binding affinity, toxic potential, or pharmacokinetic properties of an existing or a hypothetical molecule. This correlation may be obtained by analyzing topology and fields of the molecules of interest or by simulating their spatial interactions with biological receptors or models thereof. While 3D-QSAR simulations allow for a specific interaction scheme with the virtual receptor, they presume the knowledge of the bioactive conformation of the ligand molecules and require a sophisticated guess about manifestation and magnitude of the associated induced fit – the adaptation of the receptor binding pocket to the individual ligand topology.