NOTE: Web Driver EDGE file .exe must downloaded through official channels (https://developer.microsoft.com/en-us/microsoft-edge/tools/webdriver/) and be in the same file folder. Please cite the different programs used.  

This Python script presents a pipeline for identifying and analyzing epitopes (antigenic determinants) for MHC-I, MHC-II, and B cells, and then constructing a multi-epitopic peptide vaccine. Let's break down the steps and functions of the Python code:

1.- Identification of MHC-I Epitopes:

Platform Used: MHC-I Binding Predictions (NetMHCpan 4.1) from the National Institutes of Health.
Method: NetMHCpan 4.1, using HLA reference alleles.
Selection Criteria: Top 100 epitopes based on affinity scores.
Result Processing: Selecting the top 100 epitopes for further analysis.

2.- Identification of MHC-II Epitopes:

Platform Used: MHC-II Binding Predictions (NetMHCIIpan 4.1) from the National Institutes of Health.
Method: NetMHCIIpan 4.1, using HLA-DR reference alleles.
Selection Criteria: Top 100 epitopes based on affinity scores.
Result Processing: Selecting the top 100 epitopes for further analysis.

3.- Identification of B Cell Epitopes:

Platform Used: Antibody Epitope Prediction from the National Institutes of Health, utilizing various models.
Models Used: Bepipred Linear Epitope Prediction 2.0, Bepipred Linear Epitope Prediction, Chou & Fasman Beta-Turn Prediction, Emini Surface Accessibility Prediction, Karplus & Schulz Flexibility Prediction, Kolaskar & Tongaonkar Antigenicity, and Parker Hydrophilicity Prediction.
Result Processing: Obtaining different B cell epitopes from different models.

4.- Epitope Cleaning:

Objective: Eliminating duplicate peptide sequences.
Result Processing: Reducing the number of MHC-I epitopes from 100 to 50, MHC-II epitopes from 100 to 67, and B cell epitopes from 33 to 27.

5.- Evaluation of Antigenicity and Safety:

Tools Used: VaxiJen v2.0 and AllerTop v2.0.
Antigenicity Evaluation: Using VaxiJen with a threshold of 0.6.
Allergenicity Evaluation: Using AllerTop.
Result Processing: Identifying MHC-I epitopes, MHC-II epitopes, and B cell epitopes that passed the antigenicity level.

6.- Construction of Multi-Epitopic Peptide Vaccine:

Linkers Used: "EAAAK" for adjuvants, "AAY" for MHC-I, "GPGPG" for MHC-II, and "KK" for B cell epitopes.
Overlap Processing: Overlapping regions to improve immunogenic coverage.
Result Processing: Constructing final regions with different safe and antigenic MHC-II epitopes, MHC-II epitopes, and B cell epitopes.

7.- Final Structure:

Combining the constructed regions to form a multi-epitopic peptide vaccine for MHC-I, MHC-II, and B cells.

This script integrates various bioinformatics tools and platforms to predict, filter, and construct a potential peptide vaccine with optimized immunogenicity and safety. The final structure represents a concatenated sequence of epitopes with appropriate linkers for each type of immune response.


References: 
Vita R, Mahajan S, Overton JA, Dhanda SK, Martini S, Cantrell JR, Wheeler DK, Sette A, Peters B. The Immune Epitope Database (IEDB): 2018 update. Nucleic Acids Res. 2018 Oct 24. doi: 10.1093/nar/gky1006. PMID: 30357391; PMCID: PMC6324067 
Doytchinova, I.A., Flower, D.R. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics 8, 4 (2007). https://doi.org/10.1186/1471-2105-8-4 
Dimitrov, I., Bangov, I., Flower, D.R., Doytchinova, I. AllerTOP v.2 - a server for in silico prediction of allergens. J. Mol. Model., 20, 2278, 2014.
Chung EH. Vaccine allergies. Clin Exp Vaccine Res. 2014 Jan;3(1):50-7. doi: 10.7774/cevr.2014.3.1.50. Epub 2013 Dec 18. PMID: 24427763; PMCID: PMC3890451.
Md. Shakhawat Hossain, Mohammad Imran Hossan, Shagufta Mizan, Abu Tayab Moin, Yasmin, F., Al-Shahriar Akash, Shams Nur Powshi, A.K Rafeul Hasan, & Afrin Sultana Chowdhury. (2021). Immunoinformatics approach to designing a multi-epitope vaccine against Saint Louis Encephalitis Virus. Informatics in Medicine Unlocked, 22, 100500–100500. https://doi.org/10.1016/j.imu.2020.100500


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