Data & ReproProtein Structure & DesignFreedomIntelligence/OpenClaw-Medical-SkillsData & Reproduction
AN

antibody-design-agent

Maintainer FreedomIntelligence · Last updated April 1, 2026

Antibody design: epitope mapping, CDR engineering, bispecific construction.

OpenClawNanoClawAnalysisReproductionantibody-design-agent🧠 bioos extended suitedrug discovery & designantibody

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/antibody-design-agent

Maintainer
FreedomIntelligence
License
MIT
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • This skill brings together cutting-edge tools for antibody engineering, including MAGE (Monoclonal Antibody Generator) and RFdiffusion for Antibodies. It enables the de novo design of antibodies against specific viral or tumoral targets.
  • De Novo Design: Generating antibody sequences/structures that bind to a specific antigen.
  • Epitope Targeting: Designing VHH or binders for a specific epitope on a target protein.
  • Optimization: Improving the affinity or stability of an existing antibody candidate.
  • Viral Defense: Rapidly generating antibodies against novel viral strains.

Source Doc

Excerpt From SKILL.md

Core Capabilities

  1. MAGE (Monoclonal Antibody Generator): Uses a protein language model to generate diverse antibody sequences against unseen viral strains.
  2. RFdiffusion for Antibodies: Generates 3D antibody structures that bind to a target structure with high precision.
  3. ProteinMPNN: Optimizes the sequence of the generated structures for solubility and expression.

Workflow

  1. Target Definition: Input the PDB structure or sequence of the antigen (target).
  2. Design Phase:
    • Use RFdiffusion to generate the backbone of the binder (CDR loops).
    • Use ProteinMPNN to design the sequence for the backbone.
    • Alternatively, use MAGE to generate sequences directly from viral strain data.
  3. Validation (In Silico): Use AlphaFold3 or ESMFold to predict the complex structure and assess binding confidence (pLDDT, PAE).
  4. Selection: Rank candidates for synthesis.

Example Usage

User: "Design a VHH nanobody that binds to the RBD of the SARS-CoV-2 KP.2 variant."

Agent Action:

  1. Retrieves RBD structure for KP.2.
  2. Runs RFdiffusion with "binder" constraints on the RBD surface.
  3. Generates 100 backbone candidates.
  4. Sequences them with ProteinMPNN.
  5. Folds the complexes with AlphaFold3 to verify binding interface.
  6. Returns top 5 sequences.

Use cases

  • **De Novo Design**: Generating antibody sequences/structures that bind to a specific antigen.
  • **Epitope Targeting**: Designing VHH or binders for a specific epitope on a target protein.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

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