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Journal of Productivity and Development
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El Hefnawi, M., Hasan, M., Mahmoud, A., El-Absawy, E., Hemeida, A., Khidr, Y. (2017). In Silico DISCOVERY OF NOVEL HEPATITIS C VIRUS P7-TRANSACTIVATED PROTEIN1INHIBITOR BY USING STRUCTURE-BASED VIRTUAL SCREENING. Journal of Productivity and Development, 22(1), 103-119. doi: 10.21608/jpd.2017.41709
Mahmoud El Hefnawi; Mohamed Hasan; Amal Mahmoud; El-Sayed El-Absawy; Alaa Hemeida; Yahia Khidr. "In Silico DISCOVERY OF NOVEL HEPATITIS C VIRUS P7-TRANSACTIVATED PROTEIN1INHIBITOR BY USING STRUCTURE-BASED VIRTUAL SCREENING". Journal of Productivity and Development, 22, 1, 2017, 103-119. doi: 10.21608/jpd.2017.41709
El Hefnawi, M., Hasan, M., Mahmoud, A., El-Absawy, E., Hemeida, A., Khidr, Y. (2017). 'In Silico DISCOVERY OF NOVEL HEPATITIS C VIRUS P7-TRANSACTIVATED PROTEIN1INHIBITOR BY USING STRUCTURE-BASED VIRTUAL SCREENING', Journal of Productivity and Development, 22(1), pp. 103-119. doi: 10.21608/jpd.2017.41709
El Hefnawi, M., Hasan, M., Mahmoud, A., El-Absawy, E., Hemeida, A., Khidr, Y. In Silico DISCOVERY OF NOVEL HEPATITIS C VIRUS P7-TRANSACTIVATED PROTEIN1INHIBITOR BY USING STRUCTURE-BASED VIRTUAL SCREENING. Journal of Productivity and Development, 2017; 22(1): 103-119. doi: 10.21608/jpd.2017.41709

In Silico DISCOVERY OF NOVEL HEPATITIS C VIRUS P7-TRANSACTIVATED PROTEIN1INHIBITOR BY USING STRUCTURE-BASED VIRTUAL SCREENING

Article 7, Volume 22, Issue 1, January 2017, Page 103-119  XML PDF (547.77 K)
Document Type: Original Article
DOI: 10.21608/jpd.2017.41709
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Authors
Mahmoud El Hefnawi* 1; Mohamed Hasan2; Amal Mahmoud2; El-Sayed El-Absawy2; Alaa Hemeida2; Yahia Khidr3
1Informatics and Systems Department, Division of Engineering Research Sciences, the National Research Centre, Egypt :mahef@aucegypt.edu
2Bioinformatics Department, Genetic Engineering and Biotechnology Research Institute, Sadat City University, Egypt
3Plant Biotechnology Department, Genetic Engineering and Biotechnology Research Institute, Sadat City University, Egypt
Abstract
Hepatitis C Virus (HCV) infection is a serious cause of chronic liver disease worldwide with more than 170 million infected individuals at a risk of developing significant morbidity and mortality. Till date there is no effective drug for the treatment or vaccine to prevent this infection. The present study aims in discovering novel inhibitors which target an allosteric binding site of P7-transactivated Protein1 of HCV. Virtual screening uses computer-based methods to discover new ligands on the basis of biological structures.  A structure based virtual screening of Zinc database by computational docking and the post docking analysis of energy calculations and interactions followed by ADMET studies were conducted. The approach adopted was receptor-based.
 Docking screens, guided with contact pharmacophores and neural-network activity prediction models on all allosteric binding sites and MD simulations, constituted our analysis workflow for identification of potential hits. Steps included: 1) Using two phases docking screen with moe and Glide Xp programs,  2) Ranking based on scores, and important H interactions. From the final hits, we selected best 10 compounds for further anti-HCV activity and cellular cytotoxicity assay. All 10 compounds have more potential to be considered as lead compoundsto inhibit ion channel activity of p7 with docking score and binding energy (E_score) values ranging from -16.5087 to -15.8089 and all these compounds displayed no cellular cytotoxicity. Finally, 10 hit compounds of different scaffolds having interactions with important active site residues were predicted as lead candidates. These candidates having unique scaffolds have a strong likelihood to act as further starting points in the optimization and development of novel and potent p7 ion channel inhibitors.
 
 
Keywords
In SilicoDiscovery; Novel Hepatitis C Virus P7-Transactivated Protein1inhibitor; Using Structure-Based; Virtual Screening
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