Skill: aipoch-ai/protein-docking-configurator (version 1.0.0)

--- name: protein-docking-configurator description: Prepare input files for molecular docking software, automatically determine Grid Box center and size. Supports AutoDock Vina, AutoDock4, and other mainstream docking tools. version: 1.0.0 category: Bioinfo tags: [] author: AIPOCH license: MIT status: Draft risk_level: Medium skill_type: Tool/Script owner: AIPOCH reviewer: '' last_updated: '2026-02-06' --- # Protein Docking Configurator ## Features - Parse protein PDB files, identify ligand binding pockets - Automatically calculate Grid Box center coordinates and dimensions - Generate AutoDock Vina configuration files - Generate AutoDock4 Grid parameter files - Support Box positioning based on active site residues or ligands ## Usage ### As Command Line Tool ```bash # Calculate Grid Box based on active site residues python scripts/main.py --receptor protein.pdb --active-site-residues "A:120,A:145,A:189" --software vina # Calculate Grid Box based on reference ligand python scripts/main.py --receptor protein.pdb --reference-ligand ligand.pdb --software vina # Manually specify Box parameters python scripts/main.py --receptor protein.pdb --center-x 10.5 --center-y -5.2 --center-z 20.1 --size-x 20 --size-y 20 --size-z 20 --software vina ``` ### As Python Module ```python from scripts.main import DockingConfigurator config = DockingConfigurator() # Calculate box from receptor and active site config.from_active_site("protein.pdb", ["A:120", "A:145", "A:189"]) config.write_vina_config("config.txt", exhaustiveness=32) # Calculate box from receptor and reference ligand config.from_reference_ligand("protein.pdb", "ligand.pdb", padding=5.0) config.write_autodock4_gpf("protein.gpf", spacing=0.375) ``` ## Parameter Description ### Command Line Parameters | Parameter | Description | Required | |------|------|------| | `--receptor` | Receptor protein PDB file path | Yes | | `--software` | Docking software type (vina/autodock4) | Yes | | `--active-site-residues` | Active site residue list, format: "chain:residue_number" | No | | `--reference-ligand` | Reference ligand PDB/MOL file | No | | `--center-x/y/z` | Grid Box center coordinates | No | | `--size-x/y/z` | Grid Box dimensions (Å) | No | | `--spacing` | Grid spacing (AutoDock4 only) | No (default 0.375) | | `--exhaustiveness` | Search exhaustiveness (Vina only) | No (default 32) | | `--output` | Output file path | No | ## Output - **AutoDock Vina**: Generates config.txt configuration file - **AutoDock4**: Generates .gpf (Grid Parameter File) and corresponding macromolecule files ## Dependencies - Python 3.8+ - numpy ## Examples ```bash # Example 1: Using active site residues python scripts/main.py --receptor 1abc_receptor.pdb --active-site-residues "A:45,A:92,A:156" --software vina --output vina_config.txt # Example 2: Using reference ligand with custom Box size python scripts/main.py --receptor kinase.pdb --reference-ligand ATP.pdb --software vina --size-x 25 --size-y 25 --size-z 25 # Example 3: AutoDock4 configuration python scripts/main.py --receptor protein.pdb --active-site-residues "A:100" --software autodock4 --spacing 0.375 --output protein.gpf ``` ## Notes 1. Input PDB files should have water molecules and heteroatoms removed (unless needed) 2. It is recommended to protonate and calculate charges for the receptor (using AutoDock Tools, etc.) 3. Grid Box size should be sufficient to cover ligand conformational space, typically 20-30Å 4. Active site residues should include catalytic residues and key binding residues ## Risk Assessment | Risk Indicator | Assessment | Level | |----------------|------------|-------| | Code Execution | Python/R scripts executed locally | Medium | | Network Access | No external API calls | Low | | File System Access | Read input files, write output files | Medium | | Instruction Tampering | Standard prompt guidelines | Low | | Data Exposure | Output files saved to workspace | Low | ## Security Checklist - [ ] No hardcoded credentials or API keys - [ ] No unauthorized file system access (../) - [ ] Output does not expose sensitive information - [ ] Prompt injection protections in place - [ ] Input file paths validated (no ../ traversal) - [ ] Output directory restricted to workspace - [ ] Script execution in sandboxed environment - [ ] Error messages sanitized (no stack traces exposed) - [ ] Dependencies audited ## Prerequisites No additional Python packages required. ## Evaluation Criteria ### Success Metrics - [ ] Successfully executes main functionality - [ ] Output meets quality standards - [ ] Handles edge cases gracefully - [ ] Performance is acceptable ### Test Cases 1. **Basic Functionality**: Standard input → Expected output 2. **Edge Case**: Invalid input → Graceful error handling 3. **Performance**: Large dataset → Acceptable processing time ## Lifecycle Status - **Current Stage**: Draft - **Next Review Date**: 2026-03-06 - **Known Issues**: None - **Planned Improvements**: - Performance optimization - Additional feature support


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)