Skip to content
Back to skills

Antibody Design Agent

ASecurity

--> --- 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 --- This skill brings together cutting-edge tools for antibody engineering, including MAGE (Monoclonal Antibody Generator) and RFdiffusion for Antibodies. It enables the de ...

  • 2,984 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added May 29, 2026
toolsshellexpressapi

Works with

  • api

Security analysis

A100/100

Pro scans all 18 files and shows the line behind each finding

Scanned May 29, 2026

npx -y skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill antibody-design-agent --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Antibody Design Agent?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Antibody Design Agent
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/freedomintelligence-antibody-design-agent/badge)](https://www.skillsdirectory.com/skills/freedomintelligence-antibody-design-agent)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
<!--
# 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 -->

Files in this skill

  • MAGE/README.md1.6 KB
  • MAGE/SKILL.md1.7 KB
  • MAGE/repo/Data cleaning/ASAb_database_metadata_v2_24-03-12.xlsx31.1 KB
  • MAGE/repo/Data cleaning/CoVAbDab/covabdab_gen_curation_allBinders_allVariants_v2_24-03-12.ipynb41.1 KB
  • MAGE/repo/Data cleaning/Other_notebooks/10618/10618_antigen_alignment_v1_24-03-06.ipynb26.8 KB
  • MAGE/repo/Data cleaning/Other_notebooks/10618/AA_10618_LLM-clean_24-03-06.ipynb35.6 KB
  • MAGE/repo/Data cleaning/Other_notebooks/SAbDab/SAbDab_final_clean_v1_24-03-04.ipynb16.9 KB
  • MAGE/repo/Data cleaning/Other_notebooks/atlas_antigen_alignment_v1_24-03-04.ipynb10.8 KB
  • MAGE/repo/Data cleaning/Other_notebooks/published_LIBRA-seq_concatenation_24-05-31.ipynb22.8 KB
  • MAGE/repo/Data cleaning/Other_notebooks/signalP/detagging_nonSAbDab_24-03-12.ipynb26.2 KB
  • MAGE/repo/Data cleaning/Other_notebooks/signalP/signalP_summary_output_24-03-12.txt6.2 KB
  • MAGE/repo/Data cleaning/PlAbDab/ebola_Bornholdt_24-03-07.ipynb7.2 KB
  • MAGE/repo/Data cleaning/PlAbDab/ebola_EhrHardt_24-01-03.ipynb65.5 KB
  • MAGE/repo/Data cleaning/PlAbDab/gilman_RSV_24-01-04.ipynb8.9 KB
  • MAGE/repo/Data cleaning/PlAbDab/hcv_24-01-03.ipynb3.2 KB
  • MAGE/repo/Data cleaning/crowe_ebola/crowe_ebola_processing_24-03-07.ipynb7.1 KB
  • MAGE/repo/Data cleaning/denovo_absci/denovo_trastuzamab_24-02-29.ipynb7.8 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…