MontgomeryBohde

MontgomeryBohde / PyLipidParse

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PyLipidParse is a lightweight Python library for converting standard lipid notation into RDKit and SMILES representations.

15
1
100% credibility
Found Apr 13, 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

PyLipidParse converts shorthand notations for lipids (like those from LIPID MAPS or HMDB) into standard molecular formats such as SMILES strings, InChI identifiers, and structure files.

How It Works

1
🔍 Discover the lipid tool

While studying fats and oils in biology or chemistry, you stumble upon PyLipidParse, a helper that turns simple lipid names into detailed molecule blueprints.

2
💻 Set it up simply

Download and prepare it on your computer or link it to your AI chat buddy like Claude with easy steps, no coding needed.

3
💬 Type a lipid name

Enter a shorthand like 'PC 16:0/18:1(9Z)' and watch it transform into a clear molecule description, fingerprint code, or picture-ready file.

4
Handle more lipids
📝
Convert a bunch

Feed in several names at once and get all structures together quickly.

💾
Save your structures

Download files with drawings of the molecules to open in science apps.

✅ Molecules unlocked

You now have precise blueprints of lipids for drawings, databases, or experiments, making your research smoother and faster.

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AI-Generated Review

What is PyLipidParse?

PyLipidParse is a lightweight Python library for converting standard lipid notation from LIPID MAPS, SwissLipids, or HMDB into RDKit molecules, SMILES strings, InChI, and InChIKeys. Tell it "PC 16:0/18:1(9Z)" and it spits out canonical representations ready for cheminformatics pipelines. No more hand-crafting structures – it handles fatty acids, glycerolipids, phospholipids, sphingolipids, and sterols with full stereo and ether/plasmalogen support.

Why is it gaining traction?

It fills a glaring gap: no other open-source tool converts lipid shorthand directly to SMILES or RDKit. Users get a dead-simple API for single lipids or batches, plus MOL/SDF file exports with 2D coordinates. The MCP server hooks into Claude AI for on-the-fly conversions without leaving your chat.

Who should use this?

Lipidomics researchers standardizing mass spec hits from LIPID MAPS databases. Cheminformaticians building lipid QSAR models or virtual screens needing RDKit mols from notation. Bioinformaticians scripting structure generation for membrane simulations or database lookups.

Verdict

Worth adding to your lipidomics stack if shorthand parsing slows you down – it's focused and exports clean files fast. With 15 stars and 1.0% credibility, it's early-stage but has solid docs, tests, and PyPI readiness; contribute if you need more classes.

(178 words)

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