Quantitative structure-activity relationships of cyclin-dependent kinase 1 inhibitors
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A new approach for quantitative structure-activity relationships based on MNA descriptors, fuzzy gradation method and self-consistent regression has been proposed. This approach has been realized in the computer program GUSAR (General Unrestricted Structure Activity Relationships). The method has been validated using inhibitors of cyclin-dependent kinase 1 (CDK). Prediction accuracy is comparable with that of 3D QSAR: CoMFA and CoMSIA. However, in contrast to CoMFA and CoMSIA, GUSAR approach does not require information about 3D structure of an enzyme and a ligand. Application of GUSAR method for heterogeneous training sets containing chemical compounds from different chemical classes has been shown.
Key wordsCDK1 inhibitors QSAR self-consistent regression computer prediction
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