  Antitubercular activity of 5-nitrofuran-2-yl Derivatives series were
subjected to Quantitative Structure Activity Relationship (QSAR) Analysis with
an effort to derive and understand a correlation between the biological
activity as response variable and different molecular descriptors as
independent variables. QSAR models are built using 40 molecular descriptor
dataset. Different statistical regression expressions were got using Partial
Least Squares (PLS),Multiple Linear Regression (MLR) and Principal Component
Regression (PCR) techniques. The among these technique, Partial Least Square
Regression (PLS) technique has shown very promising result as compared to MLR
technique A QSAR model was build by a training set of 30 molecules with
correlation coefficient ($r^2$) of 0.8484, significant cross validated
correlation coefficient ($q^2$) is 0.0939, F test is 48.5187, ($r^2$) for
external test set (pred$_r^2$) is -0.5604, coefficient of correlation of
predicted data set (pred$_r^2se$) is 0.7252 and degree of freedom is 26 by
Partial Least Squares Regression technique.
