Combined chemical feature-based assessment and Bayesian model studies to identify potential inhibitors for Factor Xa

Abstract

In our study, we have described chemical feature-based 3D QSAR pharmacophore models with help of known inhibitors of Factor Xa (FXa). The best model, Hypo1, has validated by various techniques to prove its robustness and statistical significance. The well validated Hypo1 was used as 3D query in the virtual screening to retrieve potential leads for FXa inhibition. The hit molecules were sort out by applying drug-like filters and molecular docking. Bayesian model was developed using training set compounds which provides molecular feature that are favoring or not favoring for FXa inhibition.

DOI: 10.1007/s00044-011-9936-2

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@article{Chandrasekaran2011CombinedCF, title={Combined chemical feature-based assessment and Bayesian model studies to identify potential inhibitors for Factor Xa}, author={Meganathan Chandrasekaran and Sugunadevi Sakkiah and Keun Woo Lee}, journal={Medicinal Chemistry Research}, year={2011}, volume={21}, pages={4083-4099} }