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Inicio Vacunas (English Edition) An immunoinformatics approach to study the epitopes of SARS-CoV-2 helicase, Nsp1...
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Vol. 24. Issue 3.
Pages 190-202 (July - September 2023)
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Vol. 24. Issue 3.
Pages 190-202 (July - September 2023)
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An immunoinformatics approach to study the epitopes of SARS-CoV-2 helicase, Nsp13
Enfoque inmunoinformático Para estudiar los epítopes de la helicasa de SARS-CoV-2, Nsp13
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Sushant Kumar, Khushboo Kumari, Gajendra Kumar Azad
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gkazad@patnauniversity.ac.in

Corresponding author.
Department of Zoology, Patna University, Patna, Bihar 800005, India
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Table 1. The table show the identity and properties of Nsp13 protein mutants identified among Indian SARS-CoV-2 isolates. The frequency of each mutant along with polarity and charge changes are also indicated. The table also show the ΔΔG and ΔΔSvib ENCoM values of the mutants observed in Nsp13.
Table 2. The table show the details of T cell epitopes of Nsp13 related to MHC-I and MHC-II molecules. The MHC-I and MHC-II interaction with top most alleles (affinity IC50 value of <200) are mentioned in the table along with Vaxijen score and allergenicity and population coverage.
Table 3. The table shows the physiochemical properties of B-cell, MHC-I and MHC-II molecules. Several parameters were obtained using different webserver and tools as mentioned in methods section. The immunodominance was identified by comparing the B-cell, MHC-I and MHC-II peptides. If a peptide is present in any one of them then One ‘+’ is assigned; however, when it is present in two of them then two ‘++’ is assigned. In this way the immunodomiance of all peptides were measure and shown in table. * represents the most immunodominant epitope (peptide 403–408, its six amino acids are present in both B-cell epitope and MHC-I peptide).
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Abstract
Introduction and objective

Vaccines are administered worldwide to control on-going coronavirus disease-19 (COVID-19) pandemic caused by SARS-CoV-2. Vaccine efficacy is largely contributed by the epitopes present on the viral proteins and their alteration might help emerging variants to escape host immune surveillance. Therefore, this study was designed to study SARS-CoV-2 Nsp13 protein, its epitopes and evolution.

Methods

Clustal Omega was used to identify mutations in Nsp13 protein. Secondary structure and disorder score was predicted by CFSSP and PONDR-VSL2 webservers. Protein stability was predicted by DynaMut webserver. B cell epitopes were predicted by IEDB DiscoTope 2.0 tools and their 3D structures were represented by discovery studio. Antigenicity and allergenicity of epitopes were predicted by Vaxijen2.0 and AllergenFPv.1.0. Physiochemical properties of epitopes were predicted by Toxinpred, HLP webserver tool.

Results

Our data revealed 182 mutations in Nsp13 among Indian SARS-CoV-2 isolates, which were characterised by secondary structure and per-residue disorderness, stability and dynamicity predictions. To correlate the functional impact of these mutations, we characterised the most prominent B cell and T cell epitopes contributed by Nsp13. Our data revealed twenty-one epitopes, which exhibited antigenicity, stability and interactions with MHC class-I and class-II molecules. Subsequently, the physiochemical properties of these epitopes were analysed. Furthermore, eighteen mutations reside in these Nsp13 epitopes.

Conclusions

We report appearance of eighteen mutations in the predicted twenty-one epitopes of Nsp13. Among these, at least seven epitopes closely matches with the functionally validated epitopes. Altogether, our study shows the pattern of evolution of Nsp13 epitopes and their probable implications.

Keywords:
SARS-CoV-2
COVID-19
Nsp13
B cell epitopes
T cell epitopes
Mutations
Indian geographical area
Immunoinformatics
Resumen
Introducción y objetivo

Las vacunas se administran a nivel mundial para controlar la pandemia en curso de la enfermedad por coronavirus de 2019 (COVID-19) causada por SARS-CoV-2. A la eficacia de la vacuna contribuyen ampliamente los epítopes presentes en las proteínas virales, y su alteración puede contribuir a que las variantes emergentes se escapen de la vigilancia inmunológica del huésped. Por tanto, este estudio fue diseñado para estudiar la proteína Nsp13 de SARS-CoV-2, sus epítopes y su evolución.

Métodos

Se utilizó Clustal Omega para identificar las mutaciones de la proteína Nsp13. La estructura secundaria y la tasa de desorden se predijeron mediante los servidores web CFSSP y PONDR-VSL2. La estabilidad de la proteína fue predicha mediante el servidor web DynaMut. Los epítopes de las células B fueron predichos mediante las herramientas DiscoTope 2.0 de IEDB, y sus estructuras en 3D fueron representadas mediante Discovery Studio.

La antigenicidad y alergenicidad de los epítopes fueron predichas mediante Vaxijen2.0 y AlergenFPv.1.0. Las propiedades fisioquímicas de los epítopes fueron predichas mediante Toxinpred, la herramienta del servidor web HLP.

Resultados

Nuestros datos revelaron 182 mutaciones en Nsp13 entre los aislados indios de SARS-CoV-2, que fueron caracterizadas mediante las predicciones de la estructura secundaria y la capacidad de desorden por residuo, la estabilidad y la dinamicidad. Para correlacionar el impacto funcional de estas mutaciones, caracterizamos los epítopes más prominentes de las células B y las células T a los que contribuyó Nsp13. Nuestros datos revelaron veintiún epítopes, que exhibieron antigenicidad, estabilidad e interacciones con las moléculas MHC de clase I y clase II. Seguidamente se analizaron las propiedades fisioquímicas de estos epítopes. Además, en estos epítopes de Nsp13 residen ocho mutaciones.

Conclusiones

Reportamos el aspecto de ocho mutaciones en los veintiún epítopes de Nsp13 predichos. Entre estos, al menos siete epítopes concuerdan estrechamente con los epítopes funcionalmente validados. En su conjunto, nuestro estudio refleja el patrón evolutivo de los epítopes de Nsp13 y sus implicaciones probables.

Palabras clave:
SARS-CoV-2
Nsp13
Epítopes de las células B y las células T
Mutaciones
Inmunoinformática

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