Computational assembly of a human Cytomegalovirus vaccine upon experimental epitope legacy


Background: Human Cytomegalovirus (HCMV) is a ubiquitous herpesvirus affecting approximately 90% of the world population. HCMV causes disease in immunologically naive and immunosuppressed patients. The prevention, diagnosis and therapy of HCMV infection are thus crucial to public health. The availability of effective prophylactic and therapeutic treatments remain a significant challenge and no vaccine is currently available. Here, we sought to define an epitope-based vaccine against HCMV, eliciting B and T cell responses, from experimentally defined HCMV-specific epitopes. Results: We selected 398 and 790 experimentally validated HCMV-specific B and T cell epitopes, respectively, from available epitope resources and apply a knowledge-based approach in combination with immunoinformatic predictions to ensemble a universal vaccine against HCMV. The T cell component consists of 6 CD8 and 6 CD4 T cell epitopes that are conserved among HCMV strains. All CD8 T cell epitopes were reported to induce cytotoxic activity, are derived from early expressed genes and are predicted to provide population protection coverage over 97%. The CD4 T cell epitopes are derived from HCMV structural proteins and provide a population protection coverage over 92%. The B cell component consists of just 3 B cell epitopes from the ectodomain of glycoproteins L and H that are highly flexible and exposed to the solvent. Conclusions: We have defined a multiantigenic epitope vaccine ensemble against the HCMV that should elicit T and B cell responses in the entire population. Importantly, although we arrived to this epitope ensemble with the help of computational predictions, the actual epitopes are not predicted but are known to be immunogenic.

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Divisions: College of Health & Life Sciences > Aston Pharmacy School
College of Health & Life Sciences
College of Health & Life Sciences > Chronic and Communicable Conditions
Funding Information: We wish to thank the Spanish Department of Science at MINECO for continuous support of the research of the Immunomedicine group through grants SAF2006:07879, SAF2009:08301 & BIO2014:54164-R to PAR. The work was supported by grant BIO2014:54164-R from Span
Additional Information: © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated
Uncontrolled Keywords: Epitopes,HCMV,Prediction,Vaccine,Structural Biology,Biochemistry,Molecular Biology,Computer Science Applications,Applied Mathematics
Publication ISSN: 1471-2407
Last Modified: 08 Dec 2023 11:24
Date Deposited: 06 Jan 2020 09:20
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://bmcbioi ... 2859-019-3052-6 (Publisher URL)
PURE Output Type: Article
Published Date: 2019-12-10
Accepted Date: 2019-08-23
Authors: Quinzo, Monica J.
Lafuente, Esther M.
Zuluaga, Pilar
Flower, Darren R. (ORCID Profile 0000-0002-8542-7067)
Reche, Pedro A.



Version: Published Version

License: Creative Commons Attribution

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