{"title":"3D-Quantitative Structure Activity Relationships of Biphenyl Carboxylic Acid MMP-3 Inhibitors: Exploring Automated Docking as Alignment Method","authors":"I. Muegge, B. Podlogar","doi":"10.1002/1521-3838(200110)20:3<215::AID-QSAR215>3.0.CO;2-9","DOIUrl":null,"url":null,"abstract":"A series of CoMFA models have been derived from docking-based and atom-based alignments. The statistics of these approaches has been compared to determine whether a docking approach can be employed as an automated alignment tool for the development of 3D-QSAR models. Using a well-characterized training set of 51 biphenyl carboxylic acid MMP-3 inhibitors, the docking-based alignment provided by a DOCK4/PMF-scoring protocol has yielded statistically significant, cross-validated CoMFA models comparable to those derived with a traditional atom-based alignment technique. Field fit minimization has been applied to refine the atom-based and docking-based alignments. The refinement appears to be beneficial for the docking-based approach. For the atom-based alignment, however, field-fit refinement has not resulted in improved CoMFA models. The statistically best CoMFA model has been created by the atom-based alignment that has been found, however, to be inconsistent with the stromelysin crystal structure. The docking alignment refined by field-fit alignment has resulted in a final alignment that is consistent with the crystal structure and only slightly statistically inferior to the atom-based aligned CoMFA model. The results show␣the ability of an automated docking/field-fit alignment technique to provide self-consistent CoMFA alignments.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":"23 1","pages":"215-222"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative Structure-activity Relationships","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/1521-3838(200110)20:3<215::AID-QSAR215>3.0.CO;2-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
A series of CoMFA models have been derived from docking-based and atom-based alignments. The statistics of these approaches has been compared to determine whether a docking approach can be employed as an automated alignment tool for the development of 3D-QSAR models. Using a well-characterized training set of 51 biphenyl carboxylic acid MMP-3 inhibitors, the docking-based alignment provided by a DOCK4/PMF-scoring protocol has yielded statistically significant, cross-validated CoMFA models comparable to those derived with a traditional atom-based alignment technique. Field fit minimization has been applied to refine the atom-based and docking-based alignments. The refinement appears to be beneficial for the docking-based approach. For the atom-based alignment, however, field-fit refinement has not resulted in improved CoMFA models. The statistically best CoMFA model has been created by the atom-based alignment that has been found, however, to be inconsistent with the stromelysin crystal structure. The docking alignment refined by field-fit alignment has resulted in a final alignment that is consistent with the crystal structure and only slightly statistically inferior to the atom-based aligned CoMFA model. The results show␣the ability of an automated docking/field-fit alignment technique to provide self-consistent CoMFA alignments.