环肽计算分析工具

./quick_setup.sh

# Navigate to the MCP directory
cd /home/xux/Desktop/CycPepMCP/CycPepMCP/tool-mcps/rosetta_kic_mcp

# Create conda environment (use mamba if available)
mamba create -p ./env python=3.12 pip numpy pandas -y
# or: conda create -p ./env python=3.12 pip numpy pandas -y

# Activate environment
mamba activate ./env
# or: conda activate ./env

# Install core scientific packages
mamba install -p ./env -c conda-forge rdkit -y
mamba install -p ./env -c conda-forge biopython -y

# Install Python utilities
mamba run -p ./env pip install loguru click tqdm

# Install MCP framework
mamba run -p ./env pip install fastmcp

# Install PyRosetta
pip install pyrosetta --find-links https://west.rosettacommons.org/pyrosetta/quarterly/release

# Activate environment
mamba activate ./env

# Run peptide closure
mamba run -p ./env python scripts/cyclic_peptide_closure.py \
  --input examples/data/structures/linear_peptide_sample.pdb \
  --length 6 \
  --nstruct 5 \
  --output results/closed_peptides

mamba run -p ./env python scripts/structure_prediction.py \
  --sequence "GRGDSP" \
  --output_dir results/structures \
  --nstruct 10 \
  --runtime 900

mamba run -p ./env python scripts/loop_modeling.py \
  --input examples/data/structures/test_in.pdb \
  --loop_start 10 \
  --loop_end 20 \
  --output results/loop_models

# Install MCP server for Claude Code
fastmcp install src/server.py --name rosetta-kic-mcp

# Add MCP server to Claude Code
claude mcp add rosetta-kic-mcp -- $(pwd)/env/bin/python $(pwd)/src/server.py

# Verify installation
claude mcp list

{
  "mcpServers": {
    "rosetta-kic-mcp": {
      "command": "/home/xux/Desktop/CycPepMCP/CycPepMCP/tool-mcps/rosetta_kic_mcp/env/bin/python",
      "args": ["/home/xux/Desktop/CycPepMCP/CycPepMCP/tool-mcps/rosetta_kic_mcp/src/server.py"]
    }
  }
}

# Start Claude Code
claude

What tools are available from rosetta-kic-mcp?

Validate this peptide structure file: @examples/data/structures/linear_peptide_sample.pdb

Submit a 3D structure prediction job for the sequence GRGDSP with 10 structures and 15 minute runtime

Close this linear peptide into a cyclic structure: @examples/data/structures/linear_peptide_sample.pdb
Use 5 structures and GLY residues for closure

Check the status of job abc12345

Submit batch structure prediction for these sequences from @examples/data/sequences/sample_cyclic_peptide.txt:
- Generate 5 structures per sequence
- Set runtime to 10 minutes per sequence

{
  "mcpServers": {
    "rosetta-kic-mcp": {
      "command": "/home/xux/Desktop/CycPepMCP/CycPepMCP/tool-mcps/rosetta_kic_mcp/env/bin/python",
      "args": ["/home/xux/Desktop/CycPepMCP/CycPepMCP/tool-mcps/rosetta_kic_mcp/src/server.py"]
    }
  }
}

# Start Gemini CLI
gemini

# Example prompts (same as Claude Code)
> What tools are available?
> Validate peptide sequence GRGDSP
> Submit structure prediction for cyclic peptide CRGDSC

# Check structure file format
mamba run -p ./env python scripts/cyclic_peptide_closure.py \
  --input examples/data/structures/linear_peptide_sample.pdb \
  --validate_only

Validate this peptide structure: @examples/data/structures/linear_peptide_sample.pdb

mamba run -p ./env python scripts/cyclic_peptide_closure.py \
  --input examples/data/structures/linear_peptide_sample.pdb \
  --length 6 \
  --nstruct 5 \
  --output results/closure_test

Close this linear peptide into a cyclic structure: @examples/data/structures/linear_peptide_sample.pdb

Use these parameters:
- Maximum loop length: 6
- Number of structures: 5
- Residue type for closure: GLY
- Job name: "closure_demo"

Check the job status and show me the results when complete.

mamba run -p ./env python scripts/structure_prediction.py \
  --sequence "GRGDSP" \
  --nstruct 10 \
  --runtime 900 \
  --output_dir results/grgdsp_prediction

Predict 3D structures for the cyclic peptide sequence GRGDSP:
- Generate 10 structures
- Set runtime limit to 15 minutes
- Name the job "grgdsp_prediction"

Monitor the progress and analyze the results when finished.

I want to screen these cyclic peptide sequences for structural diversity:

Read the sequences from @examples/data/sequences/sample_cyclic_peptide.txt and the other sequence files in that directory.

For each sequence:
1. First validate the sequence format
2. Submit structure prediction with 5 conformers each
3. Set runtime to 10 minutes per sequence
4. Name the batch job "diversity_screen"

Track all jobs and summarize the results when complete.

{
  "general": {
    "output_format": "auto",
    "verbose": true,
    "create_backups": false
  },
  "validation": {
    "sequence_min_length": 3,
    "sequence_max_length": 50,
    "validate_inputs": true
  },
  "performance": {
    "max_memory_gb": 8,
    "timeout_seconds": 3600,
    "checkpoint_interval": 100
  }
}

# Recreate environment
mamba create -p ./env python=3.12 pip numpy pandas -y
mamba activate ./env
mamba install -p ./env -c conda-forge rdkit biopython -y
mamba run -p ./env pip install loguru click tqdm fastmcp

# Install RDKit from conda-forge
mamba install -p ./env -c conda-forge rdkit -y

# Verify installation
mamba run -p ./env python -c "import rdkit; print('RDKit:', rdkit.__version__)"
mamba run -p ./env python -c "import fastmcp; print('FastMCP working')"
mamba run -p ./env python -c "from src.server import mcp; print('Server imports working')"

# Check MCP registration
claude mcp list

# Re-add if needed
claude mcp remove rosetta-kic-mcp
fastmcp install src/server.py --name rosetta-kic-mcp

Ensure your amino acid sequence uses standard single-letter codes (ACDEFGHIKLMNPQRSTVWY).
For cyclic peptides, the sequence represents the linear order before cyclization.

# Test server directly
mamba run -p ./env python src/server.py

# Check job directory
ls -la jobs/

# View job logs through MCP
# Use get_job_log tool with job_id

Use get_job_log with job_id and tail 100 to see error details.
Common causes:
- Invalid input file paths
- Insufficient disk space
- Memory limitations
- Missing PyRosetta installation

Scripts run in demo mode when PyRosetta is not available.
For full functionality, install PyRosetta from Rosetta Commons.
Demo mode generates realistic example outputs for testing.

Check that your PDB file:
- Uses standard PDB format
- Contains valid amino acid residues
- Has proper chain identifiers
- Is readable and not corrupted

For peptide closure:
- Ensure termini are properly positioned
- Check for reasonable loop length (3-20 residues)
- Verify input peptide is linear (not already cyclic)
- Consider adjusting closure parameters

# Activate environment
mamba activate ./env

# Run basic tests
mamba run -p ./env python test_simple.py

# Run MCP tests
mamba run -p ./env python test_mcp.py

# Run MCP server in dev mode
mamba run -p ./env fastmcp dev src/server.py

# Or run directly
mamba run -p ./env python src/server.py