Hepatitis C is an inflammatory infectious disease of the liver caused by the Hepatitis C Virus (HCV). It is a global pandemic, chronically inflicting 150 million people worldwide, with millions of new infections arising annually. The standard therapy of HCV is expensive, associated with severe side effects, and has variable success rates. Thus far, no HCV vaccine has been developed, owing to the challenges that faced and still face its development. Despite these challenges, several attempts have been taken to develop a vaccine, some of which have progressed to phase II clinical trials. Most of these attempts, however, have focused on HCV genotypes 1 and 2 as vaccine targets, and almost no attention has been given to HCV genotype 4 (HCV-4), the viral genotype most prevalent in the Middle East and Central Africa. In an attempt to fill this gap in HCV-4 vaccine research, this project describes the in silico identification of a group of highly conserved and immunogenic T-cell epitopes from the HCV-4 proteome, using the iVAX immunoinformatics toolkit (EpiVax Inc., RI, USA), as a first step towards the development of an epitope-driven vaccine against the viral genotype. Furthermore, it puts forth a fast and inexpensive method for the validation of the results retrospectively using the repository of empirical HCV immune epitope data on the Immune Epitope Database (IEDB). 90 HLA class I and 14 HLA class II epitopes were identified. From those, 20 HLA class I epitopes were found to be previously uncharacterized, while the in silico HLA binding predictions for 27 others (class I and class II) have been retrospectively validated. The retrospective validation results for 4 of the identified HLA class II epitopes were confirmed by a pilot HLA class II binding assay. Furthermore, an investigation of the conservancy of a selected set of the identified epitopes in newly re-sequenced HCV strains from the Egyptian population was performed. The identified and retrospectively validated set of epitopes constitutes a good target for further immunogenicity testing and epitope-driven vaccine development against HCV-4.


Biotechnology Program

Degree Name

MS in Biotechnology

Graduation Date


Submission Date

February 2014

First Advisor

Azzazy, Hassan M.E.

Committee Member 1

De Groot, Anne S.

Committee Member 2

Moustafa, Ahmed


136 p.

Document Type

Master's Thesis

Library of Congress Subject Heading 1

Hepatitis C virus.

Library of Congress Subject Heading 2



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I would like to express my sincerest gratitude and appreciation to my advisor, Prof. Hassan Azzazy, who was not only my teacher and mentor through out this journey to attain the Master of Science degree, but also like a father to me. I thank him for the science he taught me, for teaching me how to become a good researcher, for encouraging me to seize every learning opportunity that would boost my future career, and for inspiring me to direct my professiol efforts for the good of mankind. His support and belief in my capabilities motivated me to put my best efforts into completing this project and gave me a promising outlook for my future career. I will forever be privileged to have been one of his students. I would also like to extend my deepest thanks to my co-advisor, Dr. Anne De Groot, whose support and guidance were pivotal in completing this project. I thank her for welcoming me into the University of Rhode Island to attend the 2012 Neglected Tropical Diseases workshop, where I acquired the scientific and technical knowledge that formed the basis for this project, and where I performed part of the project’s empirical alysis. I sincerely thank her for her continuous support and encouragement, and for sparing no effort at providing me with the help I need to complete this project. A special thank you to my teammates at the Novel Diagnostics and Therapeutics research group at the American University in Cairo for their help, support, and encouragement; especially to Marwa Hussein for her great help and technical advice. I would also like to thank my colleague, Ms. hla Hussein, for providing me with very useful technical advice on the optimization of the Polymerase Chain Reaction performed in this project. I would also like to express my gratitude to Frances Terry and Sheila Chandran from Dr. Anne De Groot’s team at EpiVax Inc., who were always there to help me with the immunoinformatics alysis part of this project in spite of their busy schedules. I would also like to thank Andres Gutierrez, Dr. Anne’s graduate student, for assisting me with the immunoinformatics alysis at the start of this project, and Mr. Joe Desrosiers, from Dr. Anne’s team at the Institute for Immunology and Informatics at the University of Rhode Island, for assisting me in performing the empirical validation of part of the results of the immunoinformatics alysis performed in this project. Last but not least, I would like to sincerely thank my family for their guidance and support that lead me to this point; especially my mother, who motivates me to be my best in life, and who has also inspired me to tackle the subject of this project. Special thanks to my sister, La Abdel-Hady, for assisting with the artwork in this project.