<jupyter_start><jupyter_text>Metabolites are indexed using InChI key.For example:1. 2-Deoxy-Glucose: PMMURAAUARKVCB-CERMHHMHSA-N-D2. Norvaline: SNDPXSYFESPGGJ-SCSAIBSYSA-N<jupyter_code>Metabolite.get('PMMURAAUARKVCB-CERMHHMHSA-N')
Metabolite.get('SNDPXSYFESPGGJ-SCSAIBSYSA-N')<jupyter_output><empty_output><jupyter_text>The query can also be done using identifiers from databasesReferences are not indexed so this can be very slow.<jupyter_code>ref = Reference.get(accession="ZINC00391822", database="zinc")
ref.id
mets = Metabolite.from_references(references=[ref])
mets[0]<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11092715231788079, 'fraction_numerical': 0.019867549668874173, 'mean_word_length': 9.431034482758621, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '149460', 'license': 'Apache-2.0', 'n_tokens_mistral': 261, 'n_tokens_neox': 246, 'n_words': 36, 'path': 'notebooks/2.1 Find metabolites in the database.ipynb', 'repo_name': 'biosustain/marsi', 'size': '604'}