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Multi-Target QSAR and Docking Study of Steroids Binding to Corticosteroid-Binding Globulin and Sex Hormone-Binding Globulin

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The QSAR and docking studies were performed on fifty seven steroids with binding affinities for corticosteroid-binding globulin (CBG) and eighty four steroids with binding affinities for sex hormone-binding globulin (SHBG). Since the steroidal compounds have binding affinity for both CBG and SHBG, multi-target QSAR approach was employed to establish a unique QSAR method for simultaneous evaluation of the CBG and SHBG binding affinities. The constitutional, geometrical, physico-chemical and electronic descriptors were computed for the examined structures by use of the Chem3D Ultra 7.0.0, the Dragon 6.0, the MOPAC2009, and the Chemical Descriptors Library (CDL) program. Partial least squares regression (PLSR) has been applied for selection of the most relevant molecular descriptors and QSAR models building. The QSAR (SHGB) model, QSAR model (CBG), and multi-target QSAR model (CBG, SHBG) were created. The multi-target QSAR model (CBG and SHBG) was found to be more effective in describing the CBG and SHBG affinity of steroids in comparison to the one target models (QSAR (SHGB) model, QSAR model (CBG)). The multi-target QSAR study indicated the importance of the electronic descriptor (Mor16v), steric/symmetry descriptors (Eig06_EA(ed)), 2D autocorrelation descriptor (GATS4m), distance distribution descriptor (RDF045m), and atom type fingerprint descriptor (CDL-ATFP 253) in describing the CBG and SHBG affinity of steroidal compounds. Results of the created multi-target QSAR model were in accordance with the performed docking studies. The theoretical study defined physicochemical, electronic and structural requirements for selective and effective binding of steroids to the CBG and SHBG active sites.
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Keywords: Multi-target QSAR; actives sites; corticosteroid-binding globulin; distribution; docking; molecular descriptors; pharmacodynamic; sex-hormone-binding globulin; steroid-protein interaction; target models

Document Type: Research Article

Publication date: December 1, 2012

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  • Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.
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