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https://github.com/glambard/molecules_dataset_collection

Collection of data sets of molecules for a validation of properties inference
https://github.com/glambard/molecules_dataset_collection

classification dataset inference machine-learning molecule moleculenet properties rdkit smiles

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Collection of data sets of molecules for a validation of properties inference

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# Collection of data sets of molecules and properties :gift: :smile:



## What is it? 



- Inspired by [Moleculenet.ai](http://moleculenet.ai/)

- Selection of data sets of molecules (SMILES) and physicochemical properties



## Aim?



1. SMILES in the data sets have all been uniformized through the [RDKit](http://www.rdkit.org)

2. Cluster the data sets at the same place. They are all here!

3. Use it for validating the inference of molecular properties through various machine learning models as proposed in [Z. Wu et al.](https://arxiv.org/abs/1703.00564)



## Method?



- All data sets are regularized following the [RDKit](http://www.rdkit.org/docs/GettingStartedInPython.html) methods to output isomeric, canonical and kekulise SMILES ([Daylight](http://www.daylight.com/dayhtml/doc/theory/theory.smiles.html)) 

- If a SMILES was not successfully regularized, a blank replaces the SMILES compared to the original data set



## But what are these data sets?



- Quantum Mechanics: **QM9**

- Physical Chemistry: **ESOL**, **FreeSolv**, **Lipophilicity**

- Biophysics: **PCBA**, **HIV**, **BACE**

- Physiology: **BBBP**, **Tox21**, **ToxCast**, **SIDER**, **ClinTox**



From [Moleculenet.ai](http://moleculenet.ai/datasets-1), here are their short description and the task for inference between squared brackets (for the regularized data sets reported here): 



* **QM9**: Geometric,  energetic, electronic and thermodynamic properties of DFT-modelled small molecules [classification]



* **ESOL**: Water solubility data(log solubility in mols per litre) for common organic small molecules [regression]

* **FreeSolv**: Experimental and calculated hydration free energy of small molecules in water [regression]

* **Lipophilicity**: Experimental results of octanol/water distribution coefficient(logD at pH 7.4) [regression]



* **PCBA**: Selected from PubChem BioAssay, consisting of measured biological activities of small molecules generated by high-throughput screening [classification]

* **HIV**: Experimentally measured abilities to inhibit HIV replication [classification]

* **BACE**: Quantitative (IC50) and qualitative (binary label) binding results for a set of inhibitors of human β-secretase 1(BACE-1) [classification/regression]



* **BBBP**: Binary labels of blood-brain barrier penetration(permeability) [classification]

* **Tox21**: Qualitative toxicity measurements on 12 biological targets, including nuclear receptors and stress response pathways [classification]

* **ToxCast**: Toxicology data for a large library of compounds based on in vitro high-throughput screening, including experiments on over 600 tasks [classification]

* **SIDER**: Database of marketed drugs and adverse drug reactions (ADR), grouped into 27 system organ classes [classification]

* **ClinTox**: Qualitative data of drugs approved by the FDA and those that have failed clinical trials for toxicity reasons [classification]



# Citation



**Source:** [Moleculenet.ai](http://moleculenet.ai/)



**Paper:** Zhenqin Wu, Bharath Ramsundar, Evan N. Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S. Pappu, Karl Leswing, Vijay Pande, *MoleculeNet: A Benchmark for Molecular Machine Learning*, [arXiv: 1703.00564, 2017 [cs.LG]](https://arxiv.org/abs/1703.00564)