---
title: "Datamol Cheminformatics Skill"
type: skill
id: "k-dense-scientific/scientific-python/datamol"
category: "Research"
publisher: "K-Dense"
license: "MIT"
source: "https://github.com/K-Dense-AI/claude-scientific-skills/tree/a25cf9e"
canonical: "https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/datamol"
open_in_pho: "https://pho.chat/customize?item=k-dense-scientific%2Fscientific-python%2Fdatamol&utm_source=labs&utm_medium=skill-page&utm_campaign=skills-library"
---

# Datamol Cheminformatics Skill

Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.

Source: K-Dense (MIT), copied at a pinned commit. Free to use. Part of the Phở Skills library (https://labs.pho.chat/en/skills).
Skill set: Scientific Python (https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python.md).

## What it covers
- Overview
- Installation and Setup
- Core Workflows
- Parallelization
- Reference Documentation
- Best Practices
- Error Handling
- Integration with Machine Learning
- Troubleshooting
- Additional Resources
- Citing Scientific Agent Skills

## Other skills in this set
- [CZ CELLxGENE Census](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/cellxgene-census.md): Queries the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. Use when you need population-scale cell metadata, gene expression slices, Census…
- [Cirq - Quantum Computing with Python](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/cirq.md): Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise…
- [Histolab](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/histolab.md): Extracts and preprocesses whole-slide histology image tiles with Histolab. Use for WSI inspection, tissue masks, random/grid/score-based tile extraction, H&E stain normalization, and tile dataset…
- [LaminDB](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/lamindb.md): Manages biological datasets and models with LaminDB, including artifact registration, lineage tracking, schema validation, Bionty ontology annotation, query/search, collections, branches, storage…
- [Molecular Dynamics](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/molecular-dynamics.md): Runs and analyzes molecular dynamics simulations with OpenMM and MDAnalysis. Sets up protein/small molecule systems, defines force fields, runs energy minimization and production MD, and analyzes…
- [Molfeat — Small-molecule featurization](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/molfeat.md): Featurizes small molecules with Molfeat for QSAR/QSPR, chemical similarity, virtual screening, and molecular ML. Covers ECFP/MACCS fingerprints, RDKit descriptors, pharmacophores, pretrained…
- [GPU Optimization for Python with NVIDIA](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/optimize-for-gpu.md): GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX…
- [PennyLane](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/pennylane.md): Builds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows. Use for variational quantum algorithms, quantum machine learning, simulator…
- [polars-bio](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/polars-bio.md): Performs genomic interval overlap, nearest, merge, coverage, complement and subtraction on Polars DataFrames, and reads or writes BED, VCF, BCF, BAM, CRAM, GFF, GTF, FASTA and FASTQ data. Use for…
- [TileDB-VCF](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/tiledbvcf.md): Stores and retrieves genomic variant calls with TileDB-VCF. Use for indexed single-sample VCF/BCF ingestion, incremental cohorts, region and sample queries, streaming results, allele statistics, QC…
- [PyTorch Geometric (PyG)](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/torch-geometric.md): Supports PyTorch Geometric (PyG) graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets. Use…
- [TorchDrug](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/torchdrug.md): Builds and troubleshoots TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, protein representation learning, and…
- [Transformers](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/transformers.md): Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Applies when working with…
- [Vaex](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/vaex.md): Processes large tabular scientific datasets with Vaex expressions, filtered views, streamed statistics, binned visualizations, and file conversion. Use for larger-than-RAM HDF5, Arrow, CSV, or…
- [Zarr Python](https://labs.pho.chat/en/skills/k-dense-scientific/scientific-python/zarr-python.md): Stores and queries chunked N-D scientific arrays with Zarr-Python 3, including codecs, sharding, S3/GCS storage, and NumPy/Dask/Xarray integration. Use for array layout, bounded I/O, format…

## Use it
- In Phở: open https://pho.chat/customize?item=k-dense-scientific%2Fscientific-python%2Fdatamol&utm_source=labs&utm_medium=skill-page&utm_campaign=skills-library and press Try, or add it so Phở loads it whenever a request matches. Phở works with your own API key (OpenAI, Anthropic, Google and others).
- Full instructions (original SKILL.md, unchanged): https://labs.pho.chat/skills/raw/k-dense-scientific/scientific-python/skills/datamol/SKILL.md
- Original files: https://github.com/K-Dense-AI/claude-scientific-skills/tree/a25cf9e (MIT).
- Full machine-readable index: https://labs.pho.chat/skills.json