README.md

metadata

license: other
pretty_name: moses_train
tags:
  - chemistry
  - molecules
  - graph-generation
  - flow-matching
size_categories:
  - 1M<n<10M

nico8771/moses_train — cleaned MOSES (train split)

Each row is a molecule as canonical SMILES plus RDKit-recomputed targets. MOSES is neutral by construction, so molecules are featurized over 7 atom types with no formal charges, and aromatic bonds are kept as their own class (no kekulization) so the model learns aromaticity directly.

Source: official MOSES train.csv.gz (molecularsets/moses). Code: https://github.com/Nico-Conti/flow-matching-molecules (dataset/).

Schema

column	type	description
smiles	string	canonical, single-fragment SMILES (post-sanitize)
y	list[float]	RDKit targets, columns = logP, qed, SAS

Pipeline

1. Parse with RDKit; unparseable dropped.
2. Standardize — remove stereochemistry, sanitize (MOSES is neutral; no Uncharger).
3. Featurize over atom vocab (C, N, S, O, F, Cl, Br); atoms outside the vocab dropped.
4. Round-trip check — smiles -> (X, E) -> mol -> smiles, aromatic bonds preserved.

Bonds use 5 classes (none / single / double / triple / aromatic). Targets (logP, qed, SAS) are recomputed from the sanitized SMILES with RDKit.

Drop / keep counts (this build)

outcome	count
kept	1,415,728
kept_no_roundtrip	168,935

Kept: 1,584,663 molecules.