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A U T O V A X
Multi-Epitopic Peptide Vaccine Design Pipeline
================================================================================
TABLE OF CONTENTS
-----------------
1. Overview
2. Requirements
3. Pipeline Workflow
4. Tools & Platforms
5. Epitope Selection Criteria
6. Vaccine Construction
7. References
8. Disclaimer
================================================================================
1. OVERVIEW
================================================================================
This Python script implements an automated pipeline for identifying and
analyzing epitopes (antigenic determinants) for MHC-I, MHC-II, and B cells,
followed by the construction of a multi-epitopic peptide vaccine.
The pipeline integrates various bioinformatics tools and platforms to
predict, filter, and construct a potential peptide vaccine with optimized
immunogenicity and safety profiles.
Pipeline Summary:
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ MHC-I │ │ MHC-II │ │ B Cell │
│ Epitope │ │ Epitope │ │ Epitope │
│ Prediction │ │ Prediction │ │ Prediction │
└────────┬────────┘ └────────┬────────┘ └────────┬────────┘
│ │ │
└──────────┬──────────┴──────────┬──────────┘
│ │
v v
┌─────────────────┐ ┌─────────────────┐
│ Duplicate │ │ Antigenicity │
│ Removal │──>│ & Allergen │
│ │ │ Screening │
└─────────────────┘ └────────┬────────┘
│
v
┌─────────────────┐
│ Vaccine │
│ Construction │
└─────────────────┘
================================================================================
2. REQUIREMENTS
================================================================================
CRITICAL: WEB DRIVER SETUP
--------------------------
╔════════════════════════════════════════════════════════════════════╗
║ IMPORTANT NOTICE ║
╠════════════════════════════════════════════════════════════════════╣
║ ║
║ Microsoft Edge WebDriver (.exe) MUST be: ║
║ ║
║ 1. Downloaded from OFFICIAL channels ONLY: ║
║ https://developer.microsoft.com/en-us/microsoft-edge/ ║
║ tools/webdriver/ ║
║ ║
║ 2. Placed in the SAME FOLDER as the Python script ║
║ ║
║ 3. Version MUST MATCH your installed Edge browser version ║
║ ║
╚════════════════════════════════════════════════════════════════════╝
PROJECT STRUCTURE
-----------------
epitope_finder/
│
├── main.py ................. Main pipeline script
└── msedgedriver.exe ........ Microsoft Edge WebDriver (required)
PYTHON DEPENDENCIES
-------------------
• selenium
• pandas
• requests
• beautifulsoup4
• (additional dependencies as required by the script)
================================================================================
3. PIPELINE WORKFLOW
================================================================================
STEP 1: MHC-I EPITOPE IDENTIFICATION
------------------------------------
Platform: MHC-I Binding Predictions (IEDB)
Method: NetMHCpan 4.1
Alleles: HLA Reference Alleles
Selection: Top 100 epitopes by affinity score
Process Flow:
Input Sequence --> NetMHCpan 4.1 --> Ranked Epitopes --> Top 100
................................................................................
STEP 2: MHC-II EPITOPE IDENTIFICATION
-------------------------------------
Platform: MHC-II Binding Predictions (IEDB)
Method: NetMHCIIpan 4.1
Alleles: HLA-DR Reference Alleles
Selection: Top 100 epitopes by affinity score
Process Flow:
Input Sequence --> NetMHCIIpan 4.1 --> Ranked Epitopes --> Top 100
................................................................................
STEP 3: B CELL EPITOPE IDENTIFICATION
-------------------------------------
Platform: Antibody Epitope Prediction (IEDB)
Models Applied:
+---+--------------------------------------------------+
| # | Prediction Model |
+---+--------------------------------------------------+
| 1 | Bepipred Linear Epitope Prediction 2.0 |
| 2 | Bepipred Linear Epitope Prediction (Original) |
| 3 | Chou & Fasman Beta-Turn Prediction |
| 4 | Emini Surface Accessibility Prediction |
| 5 | Karplus & Schulz Flexibility Prediction |
| 6 | Kolaskar & Tongaonkar Antigenicity |
| 7 | Parker Hydrophilicity Prediction |
+---+--------------------------------------------------+
................................................................................
STEP 4: EPITOPE CLEANING (DUPLICATE REMOVAL)
--------------------------------------------
Objective: Eliminate duplicate peptide sequences
Results Summary:
+-------------+------------------+-------------------+
| Epitope Type| Before Cleaning | After Cleaning |
+-------------+------------------+-------------------+
| MHC-I | 100 | 50 |
| MHC-II | 100 | 67 |
| B Cell | 33 | 27 |
+-------------+------------------+-------------------+
................................................................................
STEP 5: ANTIGENICITY & SAFETY EVALUATION
----------------------------------------
Antigenicity Assessment:
........................
Tool: VaxiJen v2.0
Threshold: 0.6 (protective antigen classification)
URL: http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html
Allergenicity Assessment:
.........................
Tool: AllerTOP v2.0
Purpose: Identify potential allergens
URL: https://www.ddg-pharmfac.net/AllerTOP/
Selection Criteria:
[✓] Antigenicity score ≥ 0.6 (VaxiJen)
[✓] Non-allergen classification (AllerTOP)
................................................................................
STEP 6: MULTI-EPITOPIC VACCINE CONSTRUCTION
-------------------------------------------
See Section 6 for detailed construction methodology.
================================================================================
4. TOOLS & PLATFORMS
================================================================================
EPITOPE PREDICTION TOOLS
------------------------
┌────────────────────────────────────────────────────────────────────┐
│ IMMUNE EPITOPE DATABASE (IEDB) │
│ National Institutes of Health │
├────────────────────────────────────────────────────────────────────┤
│ │
│ MHC-I Binding Predictions │
│ └─ Algorithm: NetMHCpan 4.1 │
│ └─ URL: http://tools.iedb.org/mhci/ │
│ │
│ MHC-II Binding Predictions │
│ └─ Algorithm: NetMHCIIpan 4.1 │
│ └─ URL: http://tools.iedb.org/mhcii/ │
│ │
│ B Cell Epitope Prediction │
│ └─ Multiple algorithms (see Step 3) │
│ └─ URL: http://tools.iedb.org/bcell/ │
│ │
└────────────────────────────────────────────────────────────────────┘
EVALUATION TOOLS
----------------
┌────────────────────────────────────────────────────────────────────┐
│ VaxiJen v2.0 │
├────────────────────────────────────────────────────────────────────┤
│ Purpose: Prediction of protective antigens and subunit │
│ vaccines │
│ Method: Auto cross covariance (ACC) transformation │
│ Threshold: 0.6 for protective antigen classification │
│ URL: http://www.ddg-pharmfac.net/vaxijen/ │
└────────────────────────────────────────────────────────────────────┘
┌────────────────────────────────────────────────────────────────────┐
│ AllerTOP v2.0 │
├────────────────────────────────────────────────────────────────────┤
│ Purpose: In silico prediction of allergens │
│ Method: Machine learning based on amino acid descriptors │
│ Output: Allergen / Non-allergen classification │
│ URL: https://www.ddg-pharmfac.net/AllerTOP/ │
└────────────────────────────────────────────────────────────────────┘
================================================================================
5. EPITOPE SELECTION CRITERIA
================================================================================
FILTERING HIERARCHY
-------------------
Level 1: Binding Affinity
.........................
• MHC-I: Top 100 by NetMHCpan 4.1 affinity
• MHC-II: Top 100 by NetMHCIIpan 4.1 affinity
• B Cell: Positive predictions from multiple models
Level 2: Redundancy Removal
...........................
• Eliminate identical peptide sequences
• Retain unique epitopes only
Level 3: Antigenicity
.....................
• VaxiJen score ≥ 0.6
• Ensures immunogenic potential
Level 4: Safety (Allergenicity)
...............................
• AllerTOP classification: Non-allergen
• Ensures vaccine safety profile
================================================================================
6. VACCINE CONSTRUCTION
================================================================================
LINKER SEQUENCES
----------------
Different linkers are used to connect epitopes based on their function:
+------------+----------+--------------------------------------------+
| Linker | Sequence | Purpose |
+------------+----------+--------------------------------------------+
| Adjuvant | EAAAK | Connects adjuvant to epitope regions |
| MHC-I | AAY | Links MHC-I epitopes |
| MHC-II | GPGPG | Links MHC-II epitopes |
| B Cell | KK | Links B cell epitopes |
+------------+----------+--------------------------------------------+
FINAL VACCINE ARCHITECTURE
--------------------------
┌──────────────────────────────────────────────────────────────────┐
│ VACCINE CONSTRUCT STRUCTURE │
└──────────────────────────────────────────────────────────────────┘
[ADJUVANT]─EAAAK─[MHC-I REGION]─EAAAK─[MHC-II REGION]─EAAAK─[B CELL REGION]
Where:
[MHC-I REGION]:
Epitope1─AAY─Epitope2─AAY─Epitope3─AAY─...─EpitopeN
[MHC-II REGION]:
Epitope1─GPGPG─Epitope2─GPGPG─Epitope3─GPGPG─...─EpitopeN
[B CELL REGION]:
Epitope1─KK─Epitope2─KK─Epitope3─KK─...─EpitopeN
OVERLAP PROCESSING
------------------
Overlapping regions are processed to improve immunogenic coverage
while avoiding redundancy in the final construct.
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7. REFERENCES
================================================================================
Please cite the following publications when using this pipeline:
IMMUNE EPITOPE DATABASE (IEDB)
------------------------------
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
VAXIJEN
-------
Doytchinova IA, Flower DR.
"VaxiJen: a server for prediction of protective antigens, tumour
antigens and subunit vaccines."
BMC Bioinformatics 8, 4 (2007).
DOI: https://doi.org/10.1186/1471-2105-8-4
ALLERTOP
--------
Dimitrov I, Bangov I, Flower DR, Doytchinova I.
"AllerTOP v.2 - a server for in silico prediction of allergens."
J. Mol. Model., 20, 2278 (2014).
VACCINE ALLERGIES
-----------------
Chung EH.
"Vaccine allergies."
Clin Exp Vaccine Res. 2014 Jan;3(1):50-7.
DOI: 10.7774/cevr.2014.3.1.50
PMID: 24427763 | PMCID: PMC3890451
METHODOLOGY REFERENCE
---------------------
Hossain MS, Hossan MI, Mizan S, Moin AT, Yasmin F, Akash AS,
Powshi SN, Hasan AKR, Chowdhury AS.
"Immunoinformatics approach to designing a multi-epitope vaccine
against Saint Louis Encephalitis Virus."
Informatics in Medicine Unlocked, 22, 100500 (2021).
DOI: https://doi.org/10.1016/j.imu.2020.100500
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8. DISCLAIMER
================================================================================
╔════════════════════════════════════════════════════════════════════╗
║ IMPORTANT LEGAL NOTICE ║
╠════════════════════════════════════════════════════════════════════╣
║ ║
║ WEB SCRAPING DISCLAIMER ║
║ ───────────────────────────────────────────────────────────── ║
║ ║
║ This software utilizes web scraping techniques that may be ║
║ subject to the terms of service or usage policies of third- ║
║ party websites. ║
║ ║
║ USERS ARE RESPONSIBLE FOR: ║
║ ║
║ • Reviewing and complying with the terms of use, privacy ║
║ policies, and applicable laws of all websites accessed ║
║ by this software ║
║ ║
║ • Obtaining explicit permission from website owners before ║
║ scraping their content when required ║
║ ║
║ • Ensuring all usage complies with local, national, and ║
║ international laws and regulations ║
║ ║
║ The developers assume NO LIABILITY for any misuse, violation ║
║ of terms of service, or legal consequences arising from the ║
║ use of this software. ║
║ ║
║ Any misuse or violation of terms is the SOLE RESPONSIBILITY ║
║ of the user. ║
║ ║
╚════════════════════════════════════════════════════════════════════╝
╔════════════════════════════════════════════════════════════════════╗
║ RESEARCH USE DISCLAIMER ║
╠════════════════════════════════════════════════════════════════════╣
║ ║
║ This pipeline is intended for RESEARCH PURPOSES ONLY. ║
║ ║
║ Predicted vaccine candidates require extensive experimental ║
║ validation, including but not limited to: ║
║ ║
║ • In vitro immunogenicity assays ║
║ • In vivo animal studies ║
║ • Clinical trials ║
║ ║
║ Computational predictions do NOT guarantee real-world efficacy ║
║ or safety of vaccine candidates. ║
║ ║
╚════════════════════════════════════════════════════════════════════╝
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END OF DOCUMENTATION
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