title: 3D-QSAR studies on fluroquinolones derivatives as inhibitors for tuberculosis.
abstract: A quantitative structure activity relationship (QSAR) study was performed on the fluroquinolones known to have anti-tuberculosis activity. The 3D-QSAR models were generated using stepwise variable selection of the four methods - multiple regression (MR), partial least square regression (PLSR), principal component regression (PCR) and artificial neural networks (kNN-MFA). The statistical result showed a significant correlation coefficient q(2) (90%) for MR model and an external test set of (pred_r(2)) -1.7535, though the external predictivity showed to improve using kNN-MFA method with pred_r(2) of -0.4644. Contour maps showed that steric effects dominantly determine the binding affinities. The QSAR models may lead to a better understanding of the structural requirements of anti-tuberculosis compounds and also help in the design of novel molecules.
authors.affiliation: Department of Biotechnology and Bioinformatics, North Eastern Hill University, Permanent campus, Shillong-793022, India. atanubioinfo@gmail.com
authors.forename: Atanu
authors.initials: A
authors.lastname: Bhattacharjee
authors.forename: Baphilinia Jones
authors.initials: BJ
authors.lastname: Mylliemngap
authors.forename: Devadasan
authors.initials: D
authors.lastname: Velmurugan