Abstract—Hepatitis C Virus (HCV) is a fatal disease, which causes liver inflammation, fibroses and at the last stage, severe liver cirrhosis. Over 130 million of world’s population is affected by this disease. Patients infected with HCV are benefitting with treatments like interferon (IFN) and ribavirin but these therapies have its own side-effects. Current research is going on to find out an orally taken small molecule drug which can provide the same or better therapeutic result as compared to IFN. Our current study aims to the Pharmacophore based drug development of a specific small molecule anti-viral drug for Hepatitis C Virus (HCV). Drug designing using lab experimentation is not only costly but also it takes a lot of time to conduct such experimentation. Instead in this in silico study we have used computer-aided techniques to propose a Pharmacophore-based anti-viral drug specific for the protein domains of the polyprotein present in the Hepatitis C Virus. In this study, we have used homology modeling and ab initio modeling for protein 3D structure generation followed by pocket identification in the proteins. Drug-able ligands for the pockets were designed using de novo drug design method. For ligand design, pocket geometry is taken into account. Out of several generated ligands, a new Pharmacophore is proposed, specific for each of the protein domains of HCV. Keywords—Pharmacophore, anti-viral drug, in-silico drug design, ab initio drug design, HCV I. INTRODUCTION epatitis C Virus (HCV) is a blood-borne disease, which causes serious damages to human liver. HCV chronically infects 170 million people worldwide [1]-[3]. HCV is classified as the class member of Hepacivirus within the family Flaviviridae [4]. HCV has shown much diversity within its genome sequence and until now its 7 different genotypes Romasa Qasim is with the Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh (e-mail: its.romi@gmail.com). G. M. Sayedur Rahman, is with Department of Pharmaceutical Sciences, North South University, Dhaka, Bangladesh, Dhaka-1229 (phone: +880-2- 55668200, Ext: 1956; Cellular: +8801703225634; Fax+880-2-55668202; email: sayedur.rahman@northsouth.edu) Nahid Hasan is with the Department of Pharmaceutical Sciences, North South University, Dhaka, Bangladesh (e-mail: nahid.hasan@northsouth.edu). Shazzad Hossain is with the Department Electrical and Computer Engineering, North South University, Dhaka, Bangladesh (e-mail: shazzad.hossain@northsouth.edu). types, with several sub-types each, have been found [5]. Despite the truth that Hepacivirus was discovered 15 years ago but a little is known about it because it can’t be grown in vitro; i.e. in cell cultures. Therefore, until now, no single drug can claim to completely overcome the disease; firstly because it can’t be grown in the cell cultures and also because drug designing in lab is a lengthy process. However, in recent years, computer-aided in-silico methods are reducing the time consumption for drug design. Due to the unavailability of the vaccine against HCV numbers of deaths are accelerating ever year. The existing therapy consists of pegylated α-interferon (PEG-IFN) and ribavirin. Yet 50% of the patients are irresponsive to the therapy [6]. Therefore, in recent years the search for antiviral drugs against HCV has drawn the attention of many researchers all over the world, and in this growing context computer aided drug designing (CADD) approaches have played a vital role. Researchers are currently working to find an orally active small molecule drug(s) targeting any particular protein of HCV. An important study has very recently reported for the Discovery of Novel Hepatitis C Virus NS5B Polymerase Inhibitors by Combining Random Forest, Multiple e- Pharmacophore Modeling and Docking [7]. In the study employing a virtual screening (VS) approach, which is based on random forest (RB-VS), e-pharmacophore (PB-VS), and docking (DB-VS) methods were described for the discovery of novel potent HCV NS5B polymerase inhibitors. Another promising study was focused on 3D-QSAR and molecular docking studies on designing inhibitors of the hepatitis C virus NS5B polymerase [8]. Thus, a combined three-dimensional quantitative structure activity relationship (QSAR) modeling was accomplished to profoundly understand the structure activity correlation of indole-based inhibitors of the HCV NS5B polymerase against HCV. The optimum model exhibited statistically significant results: the cross-validated correlation coefficient q2 was 0.627 and non-cross-validated r2 value was 0.943. In addition, the results of internal validations of bootstrapping and Y-randomization confirmed the rationality and good predictive ability of the model, as well as external validation (the external predictive correlation coefficient r2ext = 0.629). The satisfactory results from this study may lay a reliable theoretical base for drug development of hepatitis C virus NS5B polymerase inhibitors. The authors further extended the study to develop a satisfactory model providing a reliable prediction based on 4-hydroxyamino a- pyranone carboxamide analogues as anti-HCV (hepatitis C virus) inhibitors [9]. Furthermore, analysis of the contour maps helped to provide guidelines for finding structural requirement. Therefore, the satisfactory results from this study An In-Silico Pharmacophore Based Anti-viral Drug development for Hepatitis C Virus Romasa Qasim, G. M. Sayedur Rahman, Nahid Hasan, M. Shazzad Hossain H