UniProt

uniprot.Uniprot

Uniprot is an extensive database of proteins and features of proteins, It has several API endpoints, the ones that are integrated are the most compreshenive ones called: proteins, mutagensis (high throughput mutagenesis experiments), isoforms and variation. You can query this using a single command like so:

from benchmate.apis import UniProt
uniprot=UniProt()

# Get detailed information for a specific UniProt ID
results=uniprot.get_info(uniprot_id="P01308", get_isoforms=True, get_variations=True,
                         get_mutagenesis=True, get_interactions=True, consolidate_refs=True)

The results are consolidated into an ApiCall object whose .results dictionary contains the details. You can see the references under results["references"] as PubMed IDs, and a human-readable description. All the keys in the result dictionary are:

dict_keys(['id', 'name', 'sequence', 'organism', 'gene', 'feature_types', 'comment_types', 'references', 'xref_types', 'xrefs', 'description', 
'json', 'secondary_accessions', 'variation', 'interactions', 'mutagenesis', 'isoforms'])

User-Facing Methods

search(query, page_size=500): Search UniProt by text query or keywords. Returns a pandas DataFrame with UniProt IDs, gene names, synonyms, and descriptions.
get_info(uniprot_id, ...): Retrieve complete entry details (sequence, features, isoforms, variants, mutagenesis data) for a protein ID.
get_features(results, feature_types): Extract specific feature annotations (e.g. "SIGNAL", "CHAIN", "BINDING") from the raw JSON response.
get_comments(results, types): Extract functional comments (e.g. "DISEASE", "FUNCTION", "SUBCELLULAR LOCATION") from the entry JSON.

# Inspect available comment & feature categories
print(results["comment_types"])
print(results["feature_types"])

# Extract specific features or comments
signal_features = uniprot.get_features(results["json"], "SIGNAL")
disease_comments = uniprot.get_comments(results["json"], "DISEASE")

If you do not know the UniProt ID of the protein you are interested in, you can search UniProt using keywords:

search_results=uniprot.search("insulin human")

This will return a dataframe that contains the uniprot id, gene name, its synonyms and a brief description. You can then use the ids provided in the dataframe to get all the results you need.