Original ArticleJournal of Young PharmacistsVol. 10 | Issue 3 | 2018 | pp. 260–266Open access
Immunoinformatics Based Vaccine Design for Zea M 1 Pollen Allergen
- 1*,
- 2,
- 3
- 1 Department of Biochemistry, Gurudas College, Kolkata, West Bengal, INDIA.
- 2 Department of Computer Science and Engg, IEEE Senior member (SMIEEE) Jadavpur University, Kolkata, West Bengal, INDIA.
- 3 Director, School of Bioscience and Engineering, Jadavpur University, Kolkata, West Bengal, INDIA.
Published in Journal of Young Pharmacists
Correspondence: Anamika Basu
Department of Biochemistry, Gurudas College, Kolkata, West Bengal, INDIA.
Email: basuanamikaami@gmail.com
Copyright: © 2018 Manuscript Technomedia. This is an open access article.
- Published:
- Jul 23, 2018
- Received:
- Apr 16, 2018
- Accepted:
- Jun 22, 2018
How to cite
Basu, A., Sarkar, A., & Basak, P. (2018). Immunoinformatics Based Vaccine Design for Zea M 1 Pollen Allergen. Journal of Young Pharmacists, 10(3), 260–266. https://doi.org/10.5530/jyp.2018.10.59
Abstract
Objective: Zea m1 is one of the most common aeroallergens, causing allergy. This pollen allergen, present in maize, is responsible for type I hypersensitivity reaction. Despite having available X ray crystal structure of this pollen allergen, no definite vaccine has been developed for allergic disorder in humans. Method: In our present study, an epitope-based peptide vaccine against Zea m 1 pollen allergen, using a combination of B cell and T cell epitope predictions, followed by molecular docking and molecular dynamics simulation methods are carried out. Here, protein sequences of homologous pollen allergens of Zea m1 are collected and conserved regions present in them are investigated. Result: From the identified region of the allergenic protein, the peptide sequence KVPPGPNITTNY and the sequence AEWKPMKLSM are considered as the most potential B cell and T cell epitopes respectively. Furthermore, this predicted T cell epitope AEWKPMKLSM interacted with MHC allelic protein HLAB* 44:02 with the lowest IC50 value (7.94 nM). This epitope perfectly fitted into the epitope binding groove of alpha helix of MHC I molecule with lowest energy weighted score -620.0, showing stability in MHC binding. This epitope also showed a good conservancy of 69.75% in world population coverage. Conclusion: The epitopes KVPPGPNITTNY and AEWKPMKLSM may be considered as potential peptide for peptide vaccine for pollen allergen after further experimental study.
Key message: Immunoinformatic study shows that the predicted epitopes KVPPGPNITTNY and AEWKPMKLSM provide in long term and highly specific protective immunity against Zea m 1 pollen allergen during allergic reaction for whole world population.
Keywords
Subject
Article metadata
| Title | Immunoinformatics Based Vaccine Design for Zea M 1 Pollen Allergen |
|---|---|
| Authors | Anamika Basu; Anasua Sarkar; Piyali Basak |
| Affiliations | Department of Biochemistry, Gurudas College, Kolkata, West Bengal, INDIA.; Department of Computer Science and Engg, IEEE Senior member (SMIEEE) Jadavpur University, Kolkata, West Bengal, INDIA.; Director, School of Bioscience and Engineering, Jadavpur University, Kolkata, West Bengal, INDIA. |
| Corresponding author | basuanamikaami@gmail.com |
| Journal | Journal of Young Pharmacists |
| Volume / Issue | Vol. 10, Issue 3 (2018) |
Also in this issue
- Journal of Young Pharmacists - Fact sheetpp. 249
- Diabetes Related Distress and Depression: An Emerging Threat to Human Healthpp. 250–251
- Molecular Docking, 3D Structure-Based Pharmacophore Modeling, and ADME Prediction of Alpha Mangostin and its Derivatives against Estrogen Receptor Alphapp. 252–259
- Synthesis, Characterization and Biological Evaluation of Novel 1, 4-Benzodiazepine Derivatives as Potent Anti-Tubercular Agentspp. 267–271
- Optimization of Imidazolium-Based Ionic Liquid-Microwave Assisted Extraction for Oxyresveratrol Extraction from Morus alba Rootspp. 272–275
Readers Also Viewed
Development and Validation of UV/visible Spectrophotometric Method for Estimation of Piroxicam from Bulk and Formulation
Sandip Mohan Honmane, Kunal Rajaram Yadav, Yuvraj Dilip Dange
Apr 23, 2025
Effects of Artificial Intelligence on Academic Performance of Library and Information Science University Students: A Meta-Analysis (2023-2025)
Kayode Sunday John Dada
Aug 6, 2026
Bridging Innovation and Impact: A Multidisciplinary Approach to Contemporary Research Challenges
Mueen Ahmed KK
Aug 11, 2026