{"title":"Compound-Transporter Interaction Studies using Canonical Correlation Analysis","authors":"M. Kitajima, Yohsuke Minowa, H. Matsuda, Y. Okuno","doi":"10.1273/CBIJ.7.24","DOIUrl":null,"url":null,"abstract":"The efficient screening of lead compounds or drug candidates for efficacy and safety is critically important during the early stage of drug development. Compounds are usually screened from a diverse ‘chemical space’ based only on its pharmacological effects, but this screening is not enough to guarantee drug safety. To solve this problem, we devised a chemical space that takes into account interaction information with proteins such as drug transporters. We also created and evaluated a mathematical model for predicting compound-transporter interactions. This was achieved by first generating an interaction correlation matrix based on drug transporters and their corresponding inhibitor compounds. To implement a screening scheme that takes into account interaction with drug transporters, we created a model using Canonical Correlation Analysis (CCA) that makes use of the known information on interaction between drug transporters and their corresponding inhibitors. Cross-validation of the model gave satisfactory test results and a physiologically relevant chemical space was constructed based on the model.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chem-Bio Informatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1273/CBIJ.7.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The efficient screening of lead compounds or drug candidates for efficacy and safety is critically important during the early stage of drug development. Compounds are usually screened from a diverse ‘chemical space’ based only on its pharmacological effects, but this screening is not enough to guarantee drug safety. To solve this problem, we devised a chemical space that takes into account interaction information with proteins such as drug transporters. We also created and evaluated a mathematical model for predicting compound-transporter interactions. This was achieved by first generating an interaction correlation matrix based on drug transporters and their corresponding inhibitor compounds. To implement a screening scheme that takes into account interaction with drug transporters, we created a model using Canonical Correlation Analysis (CCA) that makes use of the known information on interaction between drug transporters and their corresponding inhibitors. Cross-validation of the model gave satisfactory test results and a physiologically relevant chemical space was constructed based on the model.