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Vol. 26. Issue 2.
(April - June 2025)
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Vol. 26. Issue 2.
(April - June 2025)
Original
Exploring structural proteins of Nipah, Lassa, and coronaviruses for multi-epitope vaccine design using immuno-informatics and in silico studies
Explorar las proteínas estructurales de los virus Nipah, Lassa y coronavirus para el diseño de vacunas multiepitópicas utilizando unmunoinformática y estudios in silico
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Ananya Sajia, Sagaya Jansi Rozarioa,
, Balamurugan Shanmugarajb, Praveen Kumar Panthaganic
a Department of Bioinformatics, Stella Maris College, Chennai, Tamil Nadu, India
b Department of Biotechnology, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, India
c Molecular Biology Department, Ampath Lab, Hyderabad, Telangana, India
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Tables (16)
Table 1. Antigenic character prediction of protein using Vaxijen v2.0 server at threshold 0.4.
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Table 2. Predicted CTL Epitopes for NiV, LASV and SARS-CoV-2.
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Table 3. A detailed score table of predicted CTL epitopes of NiV, LASV and SARS-CoV-2.
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Table 4. The predicted HTL epitopes with antigenic, non-toxin and non-allergen behavior from SARS-CoV-2, NiV and LASV.
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Table 5. Cytokines of selected peptides.
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Table 6. Predicted B cell epitopes of SARS-CoV-2, NiV, LASV.
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Table 7. Population coverage analysis of predicted epitopes.
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Table 8. Docking score of CTL peptides vs TLR receptors using FireDock.
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Table 9. Docking score of HTL peptides vs TLR receptors using FireDock.
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Table 10. HDock docking result of CTL epitopes against TLR receptors.
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Table 11. HDock docking result of HTL epitopes against TLR receptors.
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Table 12. Selected target proteins from PDB for docking using Schrodinger.
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Table 13. Docking results of drug repurposing molecules.
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Table 14. Docking results of proteins against plant derived compounds.
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Table 15. ADME prediction of docked molecules using SWISSADME and Qikprop.
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Table 16. Accuracy of molecular descriptors created by OCHEM web server.
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Abstract
Objective

In recent years, public awareness of the risks posed by zoonotic diseases has significantly increased. Nipah virus (NiV) and Coronavirus are known to cause serious respiratory and neurological effects, while Lassa virus is a hemorrhagic virus. The current study employs an immunoinformatics approach to predict antigenic epitopes against NiV, Lassa virus (LASV), and Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) for the development of multi-epitope vaccines (MEV) and to identify the potential drug molecules using molecular docking approaches.

Results

Thirteen Cytotoxic T lymphocyte (CTL) epitopes for SARS-CoV-2, three for NiV, and three for LASV were selected. Additionally, eight Helper T lymphocyte (HTL) epitopes for NiV, seven for SARS-CoV-2, and five for LASV, all of which demonstrated antigenicity, non-allergenicity, and non-toxicity were identified and included. Molecular docking and subsequent construction of the 3D structure for the best epitopes from each virus revealed stable and strong binding affinities between the MEV and human pathogenic Toll-like receptors (TLRs), specifically TLR3 and TLR8.

Conclusion

This work presents evidence of in silico research on vaccine design and molecular docking against the Nipah, Lassa viruses and SARS-CoV-2 target proteins. It highlights the computational approaches used for drug repurposing and the exploration of natural drug compounds. These findings suggest that the plant-derived or naturally sourced drugs exhibit significant potential in combating viral diseases in humans.

Keywords:
Zoonotic diseases
Multi-epitope vaccine
Toll-like receptors
Molecular docking
Resumen
Objetivo

En los últimos años, ha incrementado considerablemente la concienciación pública sobre los riesgos planteados por las enfermedades zoonóticas. Se sabe que el virus Nipah (NiV) y el Coronavirus suscitan efectos respiratorios y neurológicos graves, mientras que el virus Lassa (LASV) es un virus hemorrágico. El estudio actual utiliza un enfoque inmunoinformático para predecir los epítopos antigénicos contra el NiV, el virus Lassa y el Coronavirus del Síndrome respiratorio agudo severo 2 (SARS-CoV-2) para el desarrollo de vacunas multiepitópicas (MEV), así como identificar las moléculas potenciales de los fármacos, utilizando técnicas de acoplamiento molecular.

Resultados

Se seleccionaron trece epítopos de linfocitos T citotóxicos (CTL) para SARS-CoV-2, tres para NiV, y tres para LASV. Además, se identificaron e incluyeron ocho epítopos de linfocitos T-helper (HTL) para NiV, siete para SARS-CoV-2, y cinco para LASV, demostrando todos ellos antigenicidad y ausencia de alergenicidad y toxicidad. El acoplamiento molecular y la construcción de la estructura en 3D subsiguiente de los mejores epítopos de cada virus revelaron afinidades de unión estables y fuertes entre las MEV y los receptores patogénicos humanos de tipo Toll (TLRs), específicamente TLR3 y TLR8.

Conclusión

Este estudio aporta evidencia de la investigación in silico sobre el diseño de vacunas y el acoplamiento molecular contra los virus Nipah y Lassa y las proteínas objetivo del SARS-CoV-2. Destaca los enfoques computacionales utilizados para la reutilización de fármacos y la exploración de compuestos farmacológicos naturales. Los hallazgos sugieren que los fármacos derivados de las plantas o de origen natural muestran un potencial significativo para combatir las enfermedades virales en humanos.

Palabras clave:
Enfermedades zoonóticas
Vacuna multiepitópicas
Receptores de tipo Toll
Acoplamiento molecular.

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