Screening and structure-based modeling of T-cell epitopes of Nipah virus proteome: an immunoinformatic approach for designing peptide-based vaccine

Kamthania, Mohit; Sharma, Dixit

doi:10.1007/s13205-015-0303-8

Cited by 26 publications

(21 citation statements)

References 27 publications

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“…Docking flexible oligopeptides is even more challenging than docking small molecules. Thus, there is often a need to refine the docked complexes using MD simulations [for example references (47, 67, 68)] or other flexible refinement methods such as FlexPepDock (44). Moreover, completely new docking algorithms have been recently developed specifically for docking peptides to MHC molecules (60, 61).…”

Section: Discussionmentioning

confidence: 99%

Antigenic Peptide Prediction From E6 and E7 Oncoproteins of HPV Types 16 and 18 for Therapeutic Vaccine Design Using Immunoinformatics and MD Simulation Analysis

et al. 2018

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Human papillomavirus (HPV) induced cervical cancer is the second most common cause of death, after breast cancer, in females. Three prophylactic vaccines by Merck Sharp & Dohme (MSD) and GlaxoSmithKline (GSK) have been confirmed to prevent high-risk HPV strains but these vaccines have been shown to be effective only in girls who have not been exposed to HPV previously. The constitutively expressed HPV oncoproteins E6 and E7 are usually used as target antigens for HPV therapeutic vaccines. These early (E) proteins are involved, for example, in maintaining the malignant phenotype of the cells. In this study, we predicted antigenic peptides of HPV types 16 and 18, encoded by E6 and E7 genes, using an immunoinformatics approach. To further evaluate the immunogenic potential of the predicted peptides, we studied their ability to bind to class I major histocompatibility complex (MHC-I) molecules in a computational docking study that was supported by molecular dynamics (MD) simulations and estimation of the free energies of binding of the peptides at the MHC-I binding cleft. Some of the predicted peptides exhibited comparable binding free energies and/or pattern of binding to experimentally verified MHC-I-binding epitopes that we used as references in MD simulations. Such peptides with good predicted affinity may serve as candidate epitopes for the development of therapeutic HPV peptide vaccines.

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Section: Discussionmentioning

confidence: 99%

Antigenic Peptide Prediction From E6 and E7 Oncoproteins of HPV Types 16 and 18 for Therapeutic Vaccine Design Using Immunoinformatics and MD Simulation Analysis

et al. 2018

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“…as viral vectors for the vaccine development (Satterfield, Dawes, et al, 2016). Some groups have also put forward in silico approaches to design epitope-based vaccine candidates against the Glycoprotein, Fusion protein or the RdRp of Nipah virus (Kamthania & Sharma, 2015;Parvege, Rahman, Nibir, & Hossain, 2016;Ravichandran, Venkatesan, & Febin Prabhu Dass, 2019;C. K. Saha, Mahbub Hasan, Saddam Hossain, Asraful Jahan, & Azad, 2017;Sakib, Islam, Hasan, & Nabi, 2014).…”

Section: Introductionmentioning

confidence: 99%

Designing of a multi-epitope vaccine candidate against Nipah virus by in silico approach: a putative prophylactic solution for the deadly virus

Majee

Jain

Kumar

2020

Journal of Biomolecular Structure and Dynamics

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Nipah virus (NPV) is one of the most notorious viruses with a very high fatality rate. Because of the recurrent advent of this virus and its severe neurological implications, often leading to high mortality, the WHO R&D Blueprint, 2018 has listed the Nipah virus as one of the emerging infectious diseases requiring urgent research and development effort. Yet there is a major layback in the development of effective vaccines or drugs against NPV. In this study, we have designed a stable multivalent vaccine combining several T-cell and B-cell epitopes of the essential Nipah viral proteins with the help of different ligands and adjuvants which can effectively induce both humoral and cellular immune responses in human. Different advanced immune-informatic tools confirm the stability, high immunogenicity and least allergenicity of the vaccine candidate. The standard molecular dynamic cascade analysis validates the stable interaction of the vaccine construct with the human Toll-like receptor 3 (TLR3) complex. Later, codon optimization and in silico cloning in a known pET28a vector system shows the possibility for the expression of this vaccine in a simple organism like E.coli. It is believed that with further in vitro and in vivo validation, this vaccine construct can pose to be a better prophylactic solution to the Nipah viral disease.

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“…Moreover, epitope-based vaccine is effective in both pre-exposure and post-exposure periods which makes it more advantageous to fight COVID-19 since the repeated infection by the SARS-CoV-2 to the same individual has been reported in several cases [ 21 , 22 ]. Concerning all the aspects of epitope-based vaccine design, this study is focused on the candidate epitope prediction for SARS-CoV-2 exploiting viral S protein and investigates the immunogenic properties of candidate epitopes as they are effective, safe and stable vaccine [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

An immunoinformatics study on the spike protein of SARS-CoV-2 revealing potential epitopes as vaccine candidates

Ashik

Hasan

Tasnim

et al. 2020

Heliyon

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Background The pandemic situation of SARS-CoV-2 infection has sparked global concern due to the disease COVID-19 caused by it. Since the first cluster of confirmed cases in China in December 2019, the infection has been reported across the continents and inflicted upon a substantial number of populations. Method This study is focused on immunoinformatics analyses of the SARS-CoV-2 spike glycoprotein (S protein) which is key for the viral attachment to human host cells. Computational analyses were carried out for the prediction of B-cell and T-cell (MHC class I and II) epitopes of S protein and the analyses were extended further for the prediction of their immunogenic properties. The interaction and binding affinity of T-cell epitopes with HLA-B7 were also investigated by molecular docking. Result Three distinct epitopes for vaccine design were predicted from the sequence of S protein. The potential B-cell epitope was KNHTSPDVDLG possessing the highest antigenicity score of 1.4039 among other B-cell epitopes. T-cell epitope for human MHC class I was VVVLSFELL with an antigenicity score of 1.0909 and binding ability to 29 MHC-I alleles. The predicted T-cell epitope for human MHC class II molecule was VVIGIVNNT with a corresponding 1.3063 antigenicity score, less digesting enzymes, and 7 MHC-II alleles binding ability. All these three peptides were predicted to be highly antigenic, non-allergenic, and non-toxic. Analyses of the physiochemical properties of these predicted epitopes indicate their stable nature for plausible vaccine design. Furthermore, molecular docking investigation between the MHC class-I epitopes and human HLA-B7 reflects the stable interaction with high affinity among them. Conclusion The present study posits three potential epitopes of S protein of SARS-CoV-2 predicted by immunoinformatic methods based on their immunogenic properties and interactions with the host counterpart that can facilitate the development of vaccine against SARS-CoV-2. This study can act as the springboard for the future development of the COVID-19 vaccine.

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Screening and structure-based modeling of T-cell epitopes of Nipah virus proteome: an immunoinformatic approach for designing peptide-based vaccine

Cited by 26 publications

References 27 publications

Antigenic Peptide Prediction From E6 and E7 Oncoproteins of HPV Types 16 and 18 for Therapeutic Vaccine Design Using Immunoinformatics and MD Simulation Analysis

Antigenic Peptide Prediction From E6 and E7 Oncoproteins of HPV Types 16 and 18 for Therapeutic Vaccine Design Using Immunoinformatics and MD Simulation Analysis

Designing of a multi-epitope vaccine candidate against Nipah virus by in silico approach: a putative prophylactic solution for the deadly virus

An immunoinformatics study on the spike protein of SARS-CoV-2 revealing potential epitopes as vaccine candidates

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