Quickstart ========== Installation ------------ .. code-block:: powershell pip install -e . If you plan to build the docs, add the ``docs`` extra: .. code-block:: powershell pip install -e ".[docs]" Create a drug object -------------------- .. code-block:: python from drugs import Drug, PUBCHEM_MINIMAL_STABLE # Start from any identifier aspirin = Drug.from_pubchem_cid(2244) # alternatives: # Drug.from_chembl_id("CHEMBL25") # Drug.from_inchikey("BSYNRYMUTXBXSQ-UHFFFAOYSA-N") print(aspirin.map_ids()) Fetch properties and text ------------------------- .. code-block:: python props = aspirin.fetch_pubchem_properties() text = aspirin.fetch_pubchem_text(PUBCHEM_MINIMAL_STABLE) Structure and fingerprints -------------------------- .. code-block:: python smiles = aspirin.smiles() selfies = aspirin.selfies() fp = aspirin.molecular_fingerprint(method="morgan") Similarity and batch workflows ------------------------------ .. code-block:: python ibuprofen = Drug.from_chembl_id("CHEMBL521") sim = aspirin.similarity_to(ibuprofen) cohort = Drug.from_batch([2244, "CHEMBL521", "BSYNRYMUTXBXSQ-UHFFFAOYSA-N"]) mat = Drug.batch_similarity_matrix(cohort) Bioactivity and safety ---------------------- .. code-block:: python acts = aspirin.fetch_chembl_bioactivities(min_pchembl=6.0, assay_types=["B", "F"]) ddis = aspirin.fetch_drug_interactions() RDKit property calculators -------------------------- .. code-block:: python props = aspirin.molecular_properties() print(props["qed"], props["tpsa"], props["lipinski_violations"]) Mechanisms and targets ---------------------- .. code-block:: python mechs = aspirin.fetch_chembl_mechanisms() accessions = aspirin.target_accessions() genes = aspirin.target_gene_symbols() Embeddings ---------- Plug in any embedding function. A trivial example: .. code-block:: python vec = aspirin.text_embedding(lambda s: s.upper()) Report generation ----------------- .. code-block:: python aspirin.write_drug_markdown(output_path="aspirin.md") # yields artifacts/embeddings when using cached embedding helpers