MDAprolint

v0.5.0 safe
4.0
Medium Risk

A fast python package that uses MDAnalysis and its openmp backend to calculate lipid-protein interactions, lipid-protein distances, and lipid residence times. Based on the principles of Prolint.

🤖 AI Analysis

Final verdict: SAFE

The package is assessed as safe with low risks identified across obfuscation and credential handling. However, there are some concerns regarding metadata quality and maintainer activity.

  • Low obfuscation risk
  • No credential harvesting patterns detected
  • Metadata quality and maintainer activity are suboptimal
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets.
  • Metadata: The package shows signs of low maintainer activity and metadata quality, raising concerns but not definitive evidence of malice.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ 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 score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 MDAprolint 
Create a comprehensive mini-application called 'LipidProInteract' that leverages the MDAprolint package to analyze molecular dynamics simulations of lipid-protein interactions. This application will serve as a tool for researchers to gain insights into the dynamics between lipids and proteins within biological membranes. Here’s a step-by-step guide to building the application:

1. **Project Setup**: Begin by setting up a virtual environment and installing necessary packages including MDAprolint, MDAnalysis, numpy, and matplotlib.
2. **Data Input**: Design a user-friendly interface where users can upload their trajectory (.trr or .dcd) and topology (.top or .pdb) files from molecular dynamics simulations. Ensure that the application supports common file formats used in molecular dynamics.
3. **Configuration Settings**: Allow users to configure settings such as time intervals for analysis, lipid types, protein residues, and interaction distance thresholds.
4. **Core Analysis**:
   - Utilize MDAprolint to calculate lipid-protein interaction energies over specified time intervals.
   - Use MDAprolint to compute average distances between specific lipid headgroups and protein surfaces.
   - Calculate lipid residence times around protein regions using MDAprolint’s capabilities.
5. **Visualization Tools**: Implement visualization features to display the calculated data. For instance, plot interaction energy profiles over time, show average distances as bar graphs, and represent residence times through heatmaps or line plots.
6. **Output Reports**: Generate detailed reports summarizing the findings from the analysis. Include tables and figures to present key metrics like total interaction energy, average distances, and residence times. Allow users to download these reports in PDF format.
7. **Interactive Exploration**: Enable interactive exploration of the simulation data. Users should be able to select different time points or lipid/protein regions and see instant updates in the visualizations.
8. **Documentation and Help**: Provide comprehensive documentation explaining how to use the application, interpret the results, and understand the underlying principles of lipid-protein interactions.
9. **Testing and Validation**: Before finalizing the application, ensure thorough testing with various datasets to validate the accuracy and reliability of the analyses performed by MDAprolint.

This project aims to simplify the complex task of analyzing lipid-protein interactions, making it accessible to a broader audience of researchers and students in biophysics and biochemistry.