license: cc-by-4.0
Synthetic mass spectra dataset No. 2
This is the second iteration of the GC-EI-MS synthetic dataset generated by NEIMS and RASSP models from 4.8 million structures downloaded from ZINC 20. The overlap with version 1 is approximately 8k structures (negligible), so it's usable as an extension to synth1.
Spectra generators
For generating this dataset, we used custom-trained NEIMS and RASSP models. We did this step because RASSP model is not publicly available and we wanted to have more control over potential dataleaks in the context of further models stemming from this dataset. For better reproducibility we make the NIST splits used for training NEIMS and RASSP models available in our GitHub repository (#TODO)
Dataset creation
To uniformly cover the chemical space, we first scraped 1.8 billion SMILES strings from the ZINC20 library using the 2D-standard-annotated-druglike query. From this dataset, we extracted a random sample of 30 million noncorrupted SMILES strings shorter than 100 characters. Further, we canonicalized, deduplicated, and stripped the SMILES of stereochemical information, as stereochemistry is not reliably translated into spectra and cannot be accurately detected. Additionally, we removed all NIST 20 compounds to prevent data leakage during the testing of our trained model in the future.
To evaluate the impact of RASSP and NEIMS respective spectrum prediction capabilities on SpecTUS performance, we created two identical sets of spectra generated by each model. RASSP's strict input filters reduced the dataset to approximately 4.8 million compounds. In total, the pretraining datasets comprises 4.8 million unique compounds and 9.6 million unique spectra.
Lastly, we split each synthetic dataset into training, validation, and test sets using a 0.9:0.05:0.05 ratio. The splitting process was random, but corresponding splits (training, validation, and test sets) for the NEIMS and RASSP-generated spectra contained the same compounds.
Size
rassp_custom_gen/train.jsonl 4364744
rassp_custom_gen/valid.jsonl 242486
rassp_custom_gen/test.jsonl 242486
TOTAL 4849716
neims_custom_gen/train.jsonl 4364748
neims_custom_gen/valid.jsonl 242483
neims_custom_gen/test.jsonl 242485
TOTAL 4849716
Data format
Each line of every file is a json comprising three items:
{"intensity":[0.01,0.08,0.06,0.05 ... 0.02,0.79,0.34,0.12],
"mz":[18,27,28,29,38,39,40,41,42,43, ... 202,203,270,271,272,299,300,301],
"smiles":"CCC(C)C1CCCCN1C(=O)CNc1cccc(C#N)c1"}
From the nature of the NEIMS spectra predictor, all NEIMS-generated peak intensities are in 2 decimals precision. RASSP generated intensities are not restricted in this way, so to save storage we rounded them up to 6 decimal places which is beyond recognition for our model in the downstream task.
Our [preprint] (TODO) provides more information about the task background, the final finetuned model, and the experiments.