Three-dimensional quantitative structure-activity relationships from tuned molecular quantum similarity measures: prediction of the corticosteroid-binding globulin binding affinity for a steroid family.
Predictive models based on tuned molecular quantum similarity measures and their application to obtain quantitative structure-activity relationships (QSAR) are described. In the present paper, the corticosteroid-binding globulin binding affinity of a 31 steroid family is studied by means of a multilinear regression using molecular descriptors derived from mixed steric-electrostatic quantum similarity matrixes as parameters, obtaining satisfactory predictions. A systematic procedure to treat outliers by using triple-density quantum similarity measures is also presented. This method depicts an alternative to the grid-based QSAR techniques, providing a consistent approach that avoids problematic result dependency on the grid parameters.
Robert
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Institute of Computational Chemistry, University of Girona, Catalonia, Spain.
Amat
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Carbó-Dorca
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D066298:In Vitro Techniques; D008956:Models, Chemical; D011789:Quantum Theory; D012044:Regression Analysis; D015203:Reproducibility of Results; D055672:Static Electricity; D013256:Steroids / Q000737:chemistry* / Q000378:metabolism*; D013329:Structure-Activity Relationship; D014156:Transcortin / Q000378:metabolism*
D013256:Steroids; D014156:Transcortin