QSAR studies were performed on a set of 39 analogs of fluoroquinolone using MDS vlife science QSAR plus module by using. Multiple Linear Regression (MLR), Principal Component Regression (PCR) and Partial Least Squares (PLS) Regression methods. Among these, MLR method has shown a very promising result as compared to other two methods and a QSAR model was generated by a training set of 28 molecules with correlation coefficient (r2) of 0.9412, significant cross validated correlation coefficient (q2) of 0.9213 and F test of 38.8480. In the selected descriptors, estate contribution, chi, path cluster and alignment independent descriptors were the most important descriptors in predicting anti-
tubercular inhibitory activity.
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