{"title":"Cluster based PSO in target prediction","authors":"E. Nagarajan, Sujitha George","doi":"10.1109/ICCIC.2015.7435668","DOIUrl":null,"url":null,"abstract":"Predicting the binding site for a target molecule is very crucial in modern drug discovery. Drugs are small molecules which interact with receptors by bonding. Traditionally drugs were designed for known and unknown protein target. Structure-based drug design is used for known and structure-activity relationships for unknown protein target. This paper proposed a new method to predict the binding site. Drug molecules are clustered based on functional groups, physiochemical properties etc. Each molecule in the cluster contains molecular descriptors which predicts the better accurate binding site for target Biologically inspired computation approach particle swarm optimization (PSO) is applied in forming clusters to derive to predict the optimized target for the binding site of the molecules.","PeriodicalId":276894,"journal":{"name":"2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIC.2015.7435668","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
Predicting the binding site for a target molecule is very crucial in modern drug discovery. Drugs are small molecules which interact with receptors by bonding. Traditionally drugs were designed for known and unknown protein target. Structure-based drug design is used for known and structure-activity relationships for unknown protein target. This paper proposed a new method to predict the binding site. Drug molecules are clustered based on functional groups, physiochemical properties etc. Each molecule in the cluster contains molecular descriptors which predicts the better accurate binding site for target Biologically inspired computation approach particle swarm optimization (PSO) is applied in forming clusters to derive to predict the optimized target for the binding site of the molecules.