Credential Role of van der Waal Volumes and Atomic Masses in Modeling Hepatitis C Virus NS5B Polymerase Inhibition by Tetrahydrobenzo- Thiophenes Using SVM and MLR Aided QSAR Studies

Chronic hepatitis C virus (HCV) infections are a significant health problem worldwide. The NS5B Polymerase of HCV plays a central role in virus replication and is a prime target for the discovery of new treatment options. The urgent need to develop novel anti-HCV agents has provided an impetus for understanding the structure-activity relationship of novel Hepatitis C virus (HCV) NS5B polymerase inhibitors. Towards this objective, multiple linear regression (MLR) and support vector machine (SVM) were used to develop quantitative structure-activity relationship (QSAR) models for a dataset of 34 Tetrahydrobenzothiophene derivatives. The statistical analysis showed that the models derived from both SVM (R2 = 0.9784, SE=0.2982, R2cv = 0.92) and MLR (R2=0.9684, SE=0.1171, R2cv= 0.955) have a good internal predictivity. The models were also validated using external test set validation and Y-scrambling, the results demonstrated that MLR has a significant predictive ability for the external dataset as compared to SVM. Also the model is found to yield reliable clues for further optimization of Tetrahydrobenzothiophene derivatives in the data set.