AI Analysis
Final verdict: SAFE
The package is deemed safe with a moderate risk score due to its use of external commands and network calls, which are likely for legitimate purposes related to molecular docking and chemical structure manipulation.
- Network calls to PubChem API are for legitimate purposes.
- Execution of external commands poses a potential risk but appears to be for functionality rather than malicious intent.
Per-check LLM notes
- Network: Network calls to PubChem API are likely for legitimate purposes such as fetching chemical compound information.
- Shell: Execution of external commands like 'unipka' and 'obabel' could indicate the package is using third-party tools for chemical structure manipulation, but it may also pose a risk if these commands are misused.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows low effort in metadata and maintainer history, but there are no clear signs of malicious intent.
Package Quality Overall: Low (3.6/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (5156 chars)
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
12 type-annotated function signatures detected in source
◈ Medium
Multiple Contributors
5.0
Limited contributor diversity
1 unique contributor(s) across 100 commits in nyelidl/anyone-dockingSingle author but highly active (100 commits)
Heuristic Checks
Outbound Network Calls
score 4.5
Found 3 network call pattern(s)
1: get CID from name r = requests.get( f"https://pubchem.ncbi.nlm.nih.gov/rest/pug/compountry: r2 = requests.get( f"https://pubchem.ncbi.nlm.nih.gov/rest/pugnd JSON try: r3 = requests.get( f"https://pubchem.ncbi.nlm.nih.gov/rest/pug/com
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
score 6.0
Found 3 shell execution pattern(s)
OK and not _PROPKA_OK: if subprocess.run(["which", "unipka"], capture_output=True).returncode == 0:rn False try: r = subprocess.run(["obabel", pdb_path, "-O", mol2_path],smiles): try: r = subprocess.run(["unipka","--smiles",smiles,"--json"], capture_output=True,
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository nyelidl/anyone-docking appears legitimate
Maintainer History
score 6.0
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with anyonecandock
Create a molecular docking utility app using the 'anyonecandock' Python package. This app will allow users to perform molecular docking simulations on their own ligands and protein structures. Here’s a detailed plan of what the app should do: 1. **User Input**: The app should accept user inputs for the path to the ligand (.pdbqt file) and receptor (.pdbqt file) files. Additionally, it should allow users to specify a grid box size and center coordinates. 2. **Molecular Docking**: Utilize the 'anyonecandock' package to perform molecular docking simulations using AutoDock Vina. The app should display progress updates during the docking process. 3. **pKa Prediction**: After docking, use pKaNET from the 'anyonecandock' package to predict the pKa values of the docked ligand-protein complexes. This feature will help users understand the ionization states of the molecules under different pH conditions. 4. **Visualization**: Implement a visualization feature that allows users to view the docked structures in 3D. Use RDKit from the 'anyonecandock' package to handle the molecular structure rendering. 5. **Output Results**: Provide users with detailed output results including the binding energy of each docked pose, predicted pKa values, and a visual representation of the best docked pose. 6. **Interactive Interface**: Develop a simple yet interactive command-line interface where users can easily navigate through the various functionalities of the app. 7. **Documentation**: Include comprehensive documentation explaining how to install the app, prepare input files, and interpret the output results. The 'anyonecandock' package simplifies the process of molecular docking and analysis, making it accessible even to those without extensive computational chemistry experience. By following these steps, you will create a powerful tool for researchers and students interested in studying molecular interactions.
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