Antibody Humanizer

Overview

Bioinformatics platform for converting murine antibodies into humanized variants by grafting complementarity-determining regions (CDRs) onto human framework templates while preserving antigen-binding affinity and reducing immunogenicity risk.

Key Capabilities:

• CDR Identification: Automatic CDR boundary detection (Kabat/Chothia/IMGT schemes)
• Framework Matching: Database search for optimal human germline templates
• Humanization Scoring: Multi-parameter immunogenicity risk assessment
• Back-Mutation Prediction: Identify critical framework residues for retention
• Batch Processing: Humanize multiple antibody candidates efficiently
• Immunogenicity Assessment: T-cell epitope and humanness scoring

When to Use

✅ Use this skill when:

• Converting murine hybridoma antibodies to therapeutic candidates
• Reducing immunogenicity risk of rodent-derived antibodies
• Selecting human framework templates for CDR grafting
• Identifying critical framework residues for antigen binding
• Comparing multiple humanization strategies for lead optimization
• Preparing antibody sequences for patent filings
• Teaching antibody engineering principles

❌ Do NOT use when:

• Fully human antibody generation from phage display → Use phage-display-library
• De novo antibody design → Use antibody-design-ai
• Affinity maturation → Use affinity-maturation-predictor
• ADCC/CDC optimization → Use fc-engineering-toolkit
• Final therapeutic candidate selection → Requires experimental validation

Integration:

• Upstream: antibody-sequencer (VH/VL sequence determination), cdr-grafting-validator (structural assessment)
• Downstream: protein-struct-viz (3D visualization), immunogenicity-predictor (T-cell epitope analysis)

Core Capabilities

1. CDR Region Identification

Parse antibody sequences and identify CDR boundaries:

from scripts.humanizer import AntibodyHumanizer

humanizer = AntibodyHumanizer()

# Analyze antibody sequence
analysis = humanizer.analyze_sequence(
    vh_sequence="QVQLQQSGPELVKPGASVKISCKASGYTFTDYYMHWVKQSHGKSLEWIGYINPSTGYTEYNQKFKDKATLTVDKSSSTAYMQLSSLTSEDSAVYYCAR...",
    vl_sequence="DIQMTQSPSSLSASVGDRVTITCRASQGISSWLAWYQQKPGKAPKLLIYKASSLESGVPSRFSGSGSGTDFTLTISSLQPEDFATYYCQQYSSYPYT...",
    scheme="chothia"  # Options: kabat, chothia, imgt
)

# Output CDR locations
print(analysis.cdr_regions)
# {
#   "VH_CDR1": {"start": 26, "end": 32, "seq": "GYTFTDY"},
#   "VH_CDR2": {"start": 52, "end": 58, "seq": "INPSTGY"},
#   ...
# }

Numbering Schemes:

2. Human Framework Matching

Identify optimal human germline templates: