QSAR Study in Modeling Substituted Pyrimidines as HCV Replication Inhibitors Using 3D Morse and 2D-Autocorrelation Parameter
Shailendra Agarwal, Neha Singhal, K. Anita · 2013
The present study deals with the investigation of HCV replication inhibitory activity of 60 compounds. Quantitative structure activity relationship (QSAR) was developed using a multiple linear regression (MLR) model. For this model, the squared correlation coefficient (R 2 ) is 0.81, the leave-one-out cross-validation correlation coefficient (QLOO) is 3.012. The multiple linear regression (MLR) shows that the best model is obtained using a 6 parametric model, containing GATS3e, Mor16m, Mor32u, RDF020e, RDF040u and RDF085v. These parameters are likely to influence the biological activity of these compounds. This study will pave the way for the further design, structural modification, and development of substituted pyrimidine derivatives as potent HCV NS5B inhibitors. This model has been tested using cross validation methods. The core finding of the work is given in the following research highlights- 2D- QSAR studies of pyrimidine derivatives using 3D and auto-correlation parameters. Statistical analysis using a multiple linear regression method. Cross validation is done using Leave One Out method. Non colinearity and fidelity of the parameters are further checked by plotting VIF plots which confirm our results.