Classification models of structure - P-glycoprotein activity of drugs


1. Institute of Physiologically Active Compounds, Russian Academy of Science, Chernogolovka, Russia
Type: Bioinformatics/Proteomics
DOI: 10.18097/PBMC20166202173      UDK: 541.69+519.25+518.5      PubMed Id: 27143376
Year: 2016 vol: 62  issue:2  pages: 173-179
Abstract: Thirty three classification models of substrate specificity of 177 drugs to P-glycoprotein have been created using of the linear discriminant analysis, random forest and support vector machine methods. QSAR modeling was carried out using 2 strategies. The first strategy consisted in search of all possible combinations from 1¸5 descriptors on the basis of 7 most significant molecular descriptors with clear physico-chemical interpretation. In the second case forward selection procedure up to 5 descriptors, starting from the best single descriptor was used. This strategy was applied to a set of 387 DRAGON descriptors. It was found that only one of 33 models has necessary statistical parameters. This model was designed by means of the linear discriminant analysis on the basis of a single descriptor of H-bond (SCad). The model has good statistical characteristics as evidenced by results to both internal cross-validation, and external validation with application of 44 new chemicals. This confirms an important role of hydrogen bond in the processes connected with penetration of chemical compounds through a blood-brain barrier
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Reference: Grigorev V.Yu., Solodova S.L., Polianczyk D.E., Raevsky O.A., Classification models of structure - P-glycoprotein activity of drugs, Biomeditsinskaya khimiya, 2016, vol: 62(2), 173-179.
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