Antibody AI Design Pipeline
From antigen to ranked antibody candidates — end-to-end
A production-grade computational pipeline that takes an antigen sequence and epitope residues as input and outputs ranked, wet-lab-ready antibody candidates. Built on state-of-the-art structure prediction and multi-criteria scoring, it dramatically accelerates the early stages of antibody drug discovery.
Request a DemoFive-Stage Pipeline
Each stage is independently modular and production-tested, enabling flexible integration into existing research workflows.
Epitope Processing
Validates antigen residues and computes physicochemical properties — charge, hydrophobicity, and solvent exposure — to inform downstream CDR design.
CDR Generation
Generates diverse antibody candidates using epitope-informed seeding (40%) and controlled random mutagenesis (60%) within human VH3-23 / VK1-39 germline frameworks.
Structure Prediction
Integrates ABodyBuilder2 (ImmuneBuilder) for high-confidence 3D structure prediction with pLDDT scoring. Falls back to deterministic mock PDB for rapid iteration.
Multi-Criteria Scoring & Ranking
Ranks candidates across five weighted criteria: Binding (35%), Developability (25%), Humanness (20%), Diversity (10%), and Structural confidence (10%).
Wet-Lab Ready Outputs
Produces ranked_candidates.csv, top_candidates.fasta, PDB structures, score distribution charts, and a human-readable summary report — everything needed for handoff to wet lab.
Extensible Architecture
Modular design allows each stage to be used independently or replaced — plug in ProteinMPNN, DiffAb, or AntiBERTy for improved CDR generation with zero pipeline changes.
Multi-Criteria Scoring
Candidates are ranked across five scientifically-grounded criteria with configurable weights.
Binding
Charge and hydrophobicity complementarity to the target epitope
Developability
Aggregation risk, instability motifs, and isoelectric point assessment
Humanness
CDR-H3 sequence similarity to human germline antibody repertoire
Diversity
Sequence-space coverage across the candidate set
Structural
pLDDT confidence from 3D structure prediction
Key Highlights
Validated on SARS-CoV-2 Spike RBD → ACE2 binding interface
Generates 100+ ranked candidates in a single run
Python API and CLI for flexible integration
Full pytest coverage for production reliability
Supports OAS (Observed Antibody Space) for real humanness scoring
Optional AutoDock-Vina / Rosetta docking integration
Pipeline Outputs
Every run produces a complete handoff package for your wet-lab team.
Full scoring table for all generated candidates
Top-N heavy + light chain sequences, wet-lab ready
Machine-readable metadata for downstream pipelines
Human-readable run summary and key statistics
Bar, histogram, and radar charts for scoring analysis
3D antibody structures from prediction stage
Interested in the Antibody AI Pipeline?
Get in touch to discuss licensing, integration, or a custom deployment tailored to your research environment.