Computational design of peptide-based vaccine candidates for protoparvoviruses

Summary

Advanced next generation sequencing (NGS) and metagenomics analysis with diverse bioinformatics pipeline have revolutionized the discovery of novel viruses. In recent years, three novel protoparvoviruses have been discovered in humans: bufavirus (BuV) in 2012, tusavirus (TuV) in 2014, and cutavirus (CuV) in 2016 [1-3]. BuV has since been studied the most, disclosing three genotypes that also represent serotypes. According to both geno- and seroprevalences, BuV appears to be the most common of the three novel protoparvoviruses, whereas TuV DNA has been found in only a single fecal sample, with antibody detection being equally rare [4]. Interestingly, CuV has also been detected in skin biopsies of patients with cutaneous T-cell lymphoma and a patient with melanoma, while all other skin samples have tested PCR negative [3]. Even if preliminary disease associations exist, their clinical impacts beyond the first disease associations are just beginning to emerge, thus little is known about their infection kinetics and immunobiology. The conventional ways of developing vaccine, which involves attenuated agents might take up 10-15 years of development. On the other hand, development of Machine Learning (ML) based Bioinformatics’ tools has made it possible to define vaccine candidates by in silico predictions [5]. Combining these Bioinformatics approaches, along with the advances in recombinant DNA technology (rDNA), knowledge on the host immune response and the genetic background of the pathogen, vaccine development time can be reduced significantly. Shukla Lab at the Personalised Medicine Centre, School of Medicine, Ulster University, has designed peptide-based vaccine candidates for SARS-CoV-2 [6] and currently working on multiple viruses including protoparvoviruses.

Objectives of the research

The overall aim of this project is to predict immunogenic residues located on the structural proteins (e.g. VP1) of protoparvoviruses, which will help in the development of peptide-based vaccines.

Project objectives are:

1. CD8 specific epitope prediction for BuV, TuV, and CuV.

2. CD4 specific epitope prediction for BuV, TuV, and CuV.

3. Investigate epitope conservation based on final putative targets across BuV, TuV, and CuV.

4. Antigenicity, allergencity, auto-immunity, immunogenicity, population coverage and conservation analysis of shortlisted peptide candidates.

5. Molecular docking and molecular dynamics simulation of shortlisted peptide candidates against HLA proteins.

6. 3D-rendering of docked HLA-epitope complexes.

Methods to be used

Immunoinformatics and Bioinformatics databases and software.

Skills required of applicant

The project will be entirely computational. Thus, we are seeking a student having a strong interest in computational approaches evidenced by good programming skills (preferable in Linux/Shell, Python and R) and knowledge in immunology, bioinformatics and statistics. However, students from more biology oriented background but strong interest to learn bioinformatics and programming are also encouraged to apply. This MRes project will provide opportunity to a researcher to develop computational skills in immunoinformatics and vaccine designing. Following [1-6] reading is recommended and for any further informal enquiry and/or to discuss more about the project, please contact the supervisors.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Experience using research methods or other approaches relevant to the subject domain
• A comprehensive and articulate personal statement
• A demonstrable interest in the research area associated with the studentship

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Use of personal initiative as evidenced by record of work above that normally expected at career stage.
• Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.
• Relevant professional qualification and/or a Degree in a Health or Health related area

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility