CoMFA -3D QSAR approach in drug design.
Loading...
Date
2012-10
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Progress in medicinal chemistry and in drug design depends on our ability to understand the interactions of drugs with
their biological targets. Classical QSAR studies describe biological activity in terms of physicochemical properties of substituents in
certain positions of the drug molecules. The detailed discussion of the present state of the art should enable scientists to further
develop and improve these powerful new tools. Comparative Molecular Field Analysis (CoMFA) is a mainstream and down-toearth
3D QSAR technique in the coverage of drug discovery and development. Even though CoMFA is remarkable for high
predictive capacity, the intrinsic data-dependent characteristic still makes this methodology certainly be handicapped by noise. It's
well known that the default settings in CoMFA can bring about predictive QSAR models, in the meanwhile optimized parameters
was proven to provide more predictive results. Accordingly, so far numerous endeavors have been accomplished to ameliorate the
CoMFA model’s robustness and predictive accuracy by considering various factors, including molecular conformation and
alignment, field descriptors and grid spacing. In the present article we are going to discuss the basic approaches of CoMFA in
drug design.
Description
Keywords
CoMFA, Conformation, Alignment, Fields, Grid Spacing
Citation
Sen Sandip, Farooqui N A, Easwari T S, Roy Bishwabara. CoMFA -3D QSAR approach in drug design. International Journal of Research and Development in Pharmacy and Life Sciences. 2012 Oct-Nov; 1(4): 167-175.