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name: 'molecule-evolution-agent' description: 'Evolve Molecules' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

Molecule Evolution Agent

The Molecule Evolution Agent acts as an autonomous medicinal chemist. It takes a starting molecule (or uses a default like Aspirin) and iteratively modifies its structure to optimize binding for a specific protein target.

When to Use This Skill

  • Lead Optimization: When you have a hit molecule and want to improve its potency.
  • De Novo Design: To explore chemical space around a target protein.
  • Idea Generation: To get creative structural modifications suggested by an LLM.

Core Capabilities

  1. SMILES Manipulation: Reads and writes chemical structures in SMILES format.
  2. LLM Chemist: Uses an LLM to suggest chemically valid modifications (e.g., "Add a fluorine group to the ring").
  3. Mock Scoring: (Currently) Uses a mock scoring function to simulate docking affinity.

Workflow

  1. Input: Target Protein Name (e.g., "GPRC5D").
  2. Process:
    • Start with a seed molecule.
    • Loop for N generations.
    • Ask LLM for a modification.
    • Score the new molecule.
    • Keep the best candidate.
  3. Output: Top candidate SMILES and the evolution history.

Example Usage

User: "Design a better binder for GPRC5D."

Agent Action:

python3 Skills/Drug_Discovery/Molecule_Design/evolution_agent.py
# (Note: The script currently defaults to GPRC5D, but can be extended for arguments)