README.md

metadata

tags:
  - chemistry
size_categories:
  - 1M<n<10M
configs:
  - config_name: default
    data_files: allmolgen.tar.xz

Downloaded using PyTDC (https://tdcommons.ai/).

Contains the unique canonicalized SMILES molecules from MOSES, ZINC-250K, and ChEMBL-29, done with RDKit.

Distribution of tokenized SMILES sequence lengths below. The following regex string was used to split the SMILES molecule into tokens: ([[^]]+]|Br?|Cl?|N|O|S|P|F|I|b|c|n|o|s|p|(|)|.|=|#|-|+|\|/|:|~|@|?|>>?|*|$|%[0-9]{2}|[0-9])

Included in the .csv (after extracting the .tar.xz file) is a column "smi_len". If using the same SMILES tokenization regex string as above, you can simply filter using the values in this column ("smi_len"). I'd recommend post-processing since clearly a majority of the sequences are of a much shorter length than the highest, which is above 1400 (using my regex string).