Dataset Information

In Silico Prediction of Human Leukocytes Antigen (HLA) Class II Binding Hepatitis B Virus (HBV) Peptides in Botswana.

ABSTRACT: Hepatitis B virus (HBV) is the primary cause of liver-related malignancies worldwide, and there is no effective cure for chronic HBV infection (CHB) currently. Strong immunological responses induced by T cells are associated with HBV clearance during acute infection; however, the repertoire of epitopes (epi) presented by major histocompatibility complexes (MHCs) to elicit these responses in various African populations is not well understood. In silico approaches were used to map and investigate 15-mers HBV peptides restricted to 9 HLA class II alleles with high population coverage in Botswana. Sequences from 44 HBV genotype A and 48 genotype D surface genes (PreS/S) from Botswana were used. Of the 1819 epi bindings predicted, 20.2% were strong binders (SB), and none of the putative epi bind to all the 9 alleles suggesting that multi-epitope, genotype-based, population-based vaccines will be more effective against HBV infections as opposed to previously proposed broad potency epitope-vaccines which were assumed to work for all alleles. In total, there were 297 unique epi predicted from the 3 proteins and amongst, S regions had the highest number of epi (n = 186). Epitope-densities (Depi) between genotypes A and D were similar. A number of mutations that hindered HLA-peptide binding were observed. We also identified antigenic and genotype-specific peptides with characteristics that are well suited for the development of sensitive diagnostic kits. This study identified candidate peptides that can be used for developing multi-epitope vaccines and highly sensitive diagnostic kits against HBV infection in an African population. Our results suggest that viral variability may hinder HBV peptide-MHC binding, required to initiate a cascade of immunological responses against infection.

SUBMITTER: Choga WT

PROVIDER: S-EPMC7412261 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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In Silico Prediction of Human Leukocytes Antigen (HLA) Class II Binding Hepatitis B Virus (HBV) Peptides in Botswana.

Choga Wonderful Tatenda WT Anderson Motswedi M Zumbika Edward E Phinius Bonolo B BB Mbangiwa Tshepiso T Bhebhe Lynnette N LN Baruti Kabo K Kimathi Peter Opiyo PO Seatla Kaelo K KK Musonda Rosemary M RM Bell Trevor Graham TG Moyo Sikhulile S Blackard Jason T JT Gaseitsiwe Simani S

Viruses 20200706 7

Hepatitis B virus (HBV) is the primary cause of liver-related malignancies worldwide, and there is no effective cure for chronic HBV infection (CHB) currently. Strong immunological responses induced by T cells are associated with HBV clearance during acute infection; however, the repertoire of epitopes (<i>epi</i>) presented by major histocompatibility complexes (MHCs) to elicit these responses in various African populations is not well understood. In silico approaches were used to map and inves ...[more]

PMID: 32640609

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Project description:The presentation of virus-derived peptides by HLA class I molecules on the surface of an infected cell and the recognition of these HLA-peptide complexes by, and subsequent activation of, CD8+ cytotoxic T cells provides an important mechanism for immune protection against viruses. Recent advances in proteogenomics have allowed researchers to discover a growing number of unique HLA-restricted viral peptides, resulting in a rapidly expanding repertoire of targets for immunotherapeutics (i.e. bispecific antibodies, engineered T-cell receptors (TCRs), chimeric antigen receptor T-cells (CAR-Ts)) to infected tissues. However, genomic variability between viral strains, such as Hepatitis-B virus (HBV), in combination with differences in patient HLA alleles, make it difficult to develop therapeutics against these targets. To address this challenge, we developed a novel proteogenomics approach for generating patient-specific databases that enable the identification of viral peptides based on the viral transcriptomes sequenced from individual patient liver samples. We also utilized DNA sequencing of patient samples to identify HLA genotypes and assist in target selection. Liver samples from 48 HBV infected patients, primarily from Asia, were examined to reconstruct patient-specific HBV genomes, identify regions within the human chromosomes targeted by HBV integrations and obtain a comprehensive view of HBV peptide epitopes using our HLA class-I (HLA-I) immunopeptidomics discovery platform. Two previously reported HLA associated HBV-derived peptides, HLA-A02 binder FLLTRILTI (S194-202) from the large surface antigen and HLA-A11 binder STLPETTVVRR (C141-151) from the capsid protein were validated by our discovery platform, but both were detected at a very low frequencies. In addition, we identified and validated, using heavy peptide analogues, novel strain-specific HBV-HLA associated peptides, such as GSLPQEHIVQK (P606-616) and variants. Overall, our novel approach can guide the development of bispecific antibody, TCR-T, or CAR-T based therapeutics for the treatment of HBV-related HCC and inform vaccine development.

Project description:BackgroundMajor histocompatibility complex class I (MHC-I) plays an important role in cell immune response, and stable interaction between polypeptides and MHC-I ensures efficient presentation of polypeptide-MHC-I (pMHC-I) molecular complexes to T cells. The aim of this study was to explore ways to improve the affinity and stability of the p-Human Leukocyte Antigen (HLA)-A*2402 complex.MethodsThe peptide sequences of the restricted antigen peptides for HLA-A*2402 and the results of the in vitro competitive binding test were retrieved from the literature. The affinity values were predicted using NetMHCpan v4.1 server, and the stability values were predicted using the NetMHCstab v1.0 server. Auto Vina was used to dock peptides to HLA-A*2402 protein in a flexible docking manner, while Flexpepdock was employed to optimize the docking morphology. Maestro was used to analyze the intermolecular forces and the binding affinity of the complex, while MM-GBSA was used to calculate the binding free energy values.ResultsThe intermolecular interactions that maintained the affinity and stability of peptide-HLA-A*2402 complex relied mainly on HB, followed by pi stack. The binding affinity values of molecular docking were associated with the predicted values of affinity and stability, the binding affinity and the binding free energy, as well as the intermolecular force pi-stack. The pi stack had a significant negative correlation with binding affinity and binding free energy. The replacement of the residues of the polypeptides that did not form pi-stack interactions with HLA-A*2402 improved the affinity and/or stability compared to before replacement.ConclusionsThe generation and increase in the number of pi-stacks between peptides and HLA-A*2402 molecules may help improve the affinity and stability of p-HLA-A*2402 complexes. The prediction of intermolecular forces and binding affinity of peptide-HLA by means of molecular docking is a supplement to the current commonly used prediction databases.

Dataset Information

In Silico Prediction of Human Leukocytes Antigen (HLA) Class II Binding Hepatitis B Virus (HBV) Peptides in Botswana.

Publications

In Silico Prediction of Human Leukocytes Antigen (HLA) Class II Binding Hepatitis B Virus (HBV) Peptides in Botswana.

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