1JELC1

1JELC1 / Interaction-Map-Explorer

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A Python tool for automated identification and topological analysis (QTAIM) of Critical Points at the interface between molecular fragments.

bond-critical-points computational-chemistry critical-points dft molecular-interactions
15
4
100% credibility
Found Mar 22, 2026 at 15 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Interaction Map Explorer is a specialized tool for chemists to automatically detect and analyze key interaction points between molecular fragments from quantum chemistry wavefunction files, producing visualizations and property data.

How It Works

1
🔬 Discover Interaction Map Explorer

You find this helpful tool while researching ways to study how molecules touch and interact in chemistry simulations.

2
📥 Get it ready

Download the files to your computer and set up the simple environment so everything works smoothly.

3
📁 Gather your data

Place your molecule simulation files into a folder, and if needed, add a sample of the key part you're interested in.

4
▶️ Launch the explorer

Run the program and tell it where your files are and where to save results.

5
Pick your analysis style
🖱️
Interactive mode

Use the 3D viewer to click and select groups of atoms, like picking puzzle pieces, and see connections light up right away.

🤖
Batch mode

Provide one example molecule part, and it automatically spots the same part in all your files without extra work.

6
✨ See the magic happen

Interaction points between your molecule groups glow in colors, showing bonds, rings, and more in a 3D preview.

👏 Enjoy your insights

Get colorful 3D view scripts, data tables with measurements, and files ready to open in your favorite molecule viewer for sharing or further study.

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Star Growth

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AI-Generated Review

What is Interaction-Map-Explorer?

Interaction-Map-Explorer is a Python tool for automated QTAIM analysis, pinpointing critical points like bonds, rings, and cages at interfaces between molecular fragments in molecule-molecule or protein-ligand systems. It handles Gaussian .fchk and ORCA .wfn/.wfx files, offering interactive 3D fragment selection or batch mode with ligand matching via graph isomorphism, then exports VMD-ready .tcl scripts and CSV tables with 25 properties including electron density, Laplacian, ELF, and RDG. Computational chemists use it to map interactions without manual thresholding, skipping reprocessed files for resumable workflows.

Why is it gaining traction?

It stands out by automating tedious interface CP detection—no arbitrary distance cutoffs, just nearest-neighbor geometry—while integrating seamlessly with Multiwfn for property extraction and VMD for instant 3D visuals. Batch processing shines for screening ligand environments across datasets, and the python github library setup via conda makes it a quick python toolbox addition for automated analysis in python github projects. Developers appreciate the skip-if-exists logic and color-coded outputs that cut visualization time.

Who should use this?

Computational chemists analyzing protein-ligand binding sites or intermolecular H-bonds/vdW contacts via QTAIM. Ideal for those processing batches of quantum wavefunctions, needing VMD visuals of interface CPs, or studying fragment interactions in drug design pipelines.

Verdict

Grab it if QTAIM interface mapping is your bottleneck—solid docs, Zenodo DOI, and Apache 2.0 license make it production-ready for niche use despite 15 stars and 1.0% credibility score signaling early maturity. Test on a small dataset first; lacks broad tests but delivers focused value.

(198 words)

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