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Project that collects all possible used IUPAC names in literature into a CCZero database.

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# iupac-names

Project that collects all possible used [IUPAC names](https://en.wikipedia.org/wiki/IUPAC_nomenclature_of_chemistry)
in literature into a [CCZero](https://creativecommons.org/public-domain/cc0/) database. Every
contributor guarantees that the contribution is CCZero and void of any legal claim otherwise.
Autogenerated IUPAC names are forbidden and the IUPAC name must be found in literature. The latter
includes the IUPAC names to be part of larger names, but a valid IUPAC name by itself.
Zero metadata on the origin of the IUPAC name is recorded, and just the existence that the
IUPAC name exists is the copyright-free fact we are recording here.

Our ambition was to have 1M IUPAC names within the first year. After one year, we collected
[a bit over 280 thousand IUPAC names](https://github.com/BlueObelisk/iupac-names/blob/c71224034aa88b8e9b1838147b2ca3b732fdf1a2/iupac-names.txt)
(mind the notes below). We also [noted in summer 2025](https://doi.org/10.59350/6f7he-kxt56)
that by creating variations of the names with simple heuristics, we could easily create 1M names.
In May 2026 we reached [500 thousand names](https://github.com/BlueObelisk/iupac-names/blob/06a6a4bfafeb3d4eb0f5c7d9e9ecb0dc9defb981/iupac-names.txt),
where we also found a small problem in the pipeline with newlines, explaining the first
line in that version.

This repository is very simple, consists of a single, sorted list of IUPAC names in the `iupac-names.txt` file.
Each line in that file is a valid IUPAC names, as defined by [OPSIN](https://doi.org/10.1021/ci100384d)
being able to generate a [SMILES](https://en.wikipedia.org/wiki/Simplified_Molecular_Input_Line_Entry_System)
string from it.

## Adding new names

The list is sorted and contains only unique names. On GNU/Linux, the reference algorithm for this
process is:

There are small name variants, like `1,1 Dimethylhydrazine` and `1,1-dimethylhydrazine`,
of which it is not clear if they are typos in the articles, artifacts of the text mining,
but we do know they parse into a SMILES. By removing all spaces and all hyphens, we can count
the number of unique lower-case names with:

## Calculating unique InChIKeys

As an idea of the chemical space covered, we can check the number of unique InChIKeys (mind the
tautomerism normalization):

```shell
groovy extractInChIKeys.groovy | sort | uniq | tee inchikeys.txt | wc -l
```

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