{"title":"Rescoring ligand docking poses.","authors":"Shijun Zhong, Youping Zhang, Zhilong Xiu","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>The ranking of ligand docking poses according to certain scoring systems to identify the best fit is the most important step in virtual database screening for drug discovery. By focusing on method development strategy, this review provides possibilities for constructing rescoring approaches based on an overview of recent developments in the field. These developments can be classified into three categories. The first category involves a scaling approach that employs a factor to scale the primary scoring function. These scaling factors are defined with respect to the geometrical match between the location of a ligand and the target binding site, or defined according to a molecular weight distribution consistent with the empirical range of molecular weights of drug-like compounds. The second category involves consensus scoring approaches that use multiple scoring functions to rank the ligand poses retained in a docking procedure, based on the preliminary ranking according to a primary scoring function. The final category involves the addition of selected accuracy-oriented energy terms, such as the solvent effect and quantum mechanics/molecular mechanics treatments.</p>","PeriodicalId":10809,"journal":{"name":"Current opinion in drug discovery & development","volume":"13 3","pages":"326-34"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current opinion in drug discovery & development","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The ranking of ligand docking poses according to certain scoring systems to identify the best fit is the most important step in virtual database screening for drug discovery. By focusing on method development strategy, this review provides possibilities for constructing rescoring approaches based on an overview of recent developments in the field. These developments can be classified into three categories. The first category involves a scaling approach that employs a factor to scale the primary scoring function. These scaling factors are defined with respect to the geometrical match between the location of a ligand and the target binding site, or defined according to a molecular weight distribution consistent with the empirical range of molecular weights of drug-like compounds. The second category involves consensus scoring approaches that use multiple scoring functions to rank the ligand poses retained in a docking procedure, based on the preliminary ranking according to a primary scoring function. The final category involves the addition of selected accuracy-oriented energy terms, such as the solvent effect and quantum mechanics/molecular mechanics treatments.