---
name: Antibody Design Agent
slug: antibody-design-agent
category: AI Engineering
description: Antibody Design Agent designs de novo antibodies against viral or tumoral targets using protein language models (MAGE) and RFdiffusion, then validates candidates with AlphaFold3 or ESMFold. Use it when you need binder sequences for a specific antigen or epitope.
github: "https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/antibody-design-agent"
language: Python
stars: 2944
forks: 410
install: "npx degit https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/antibody-design-agent ~/.claude/skills/antibody-design-agent"
installs_to: ~/.claude/skills/antibody-design-agent
source_path: skills/antibody-design-agent/SKILL.md
collection_size: 25
category_size: 2451
collection_url: "https://dirskills.com/collections/FreedomIntelligence/OpenClaw-Medical-Skills"
added: 2026-08-17T07:09:40.346Z
last_synced: 2026-08-17T07:09:40.346Z
canonical_url: "https://dirskills.com/skills/antibody-design-agent"
---

# Antibody Design Agent

Antibody Design Agent designs de novo antibodies against viral or tumoral targets using protein language models (MAGE) and RFdiffusion, then validates candidates with AlphaFold3 or ESMFold. Use it when you need binder sequences for a specific antigen or epitope.

**Install:**

```bash
npx degit https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/antibody-design-agent ~/.claude/skills/antibody-design-agent
```

## README

<!--
# COPYRIGHT NOTICE
# This file is part of the "Universal Biomedical Skills" project.
# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
# All Rights Reserved.
#
# This code is proprietary and confidential.
# Unauthorized copying of this file, via any medium is strictly prohibited.
#
# Provenance: Authenticated by MD BABU MIA

-->

---
name: 'antibody-design-agent'
description: 'An advanced agent for de novo antibody design and optimization using state-of-the-art protein language models (MAGE, RFdiffusion).'
measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.
allowed-tools:
  - read_file
  - run_shell_command
---


# Antibody Design Agent

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.

## When to Use This Skill

*   **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.

## 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.


<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->