drug-discovery

Drug discovery bioactive compound search queries the ChEMBL API by target name, activity, or molecule name to retrieve matching compounds and bioactivity data. You can search targets like EGFR directly to identify potential lead molecules.

ADMET analysis interprets Absorption, Distribution, Metabolism, Excretion, and Toxicity profiles of compounds to evaluate their pharmacokinetic properties. It assists lead optimization by identifying safety liabilities and drug-like molecular properties early.

Drug-likeness calculation evaluates molecular properties against Lipinski Rule of Five and Veber score thresholds to predict oral bioavailability. It processes molecular structure data to determine if a compound meets standard drug-like chemical criteria.

Yes, drug discovery requires Python3 and curl dependencies to execute API query scripts and retrieve data from OpenFDA, PubChem, ChEMBL, and OpenTargets. The local Python environment executes the bioinformatics scripts that fetch external molecular data.

Drug interaction and safety lookup queries the OpenFDA API with drug identifiers to retrieve comprehensive interaction warnings, adverse event data, and safety profiles. It provides regulatory safety context for analyzed compounds.

Analyzing novel molecules combines ChEMBL bioactive compound search, drug-likeness calculation, and OpenFDA drug interaction lookup. This integrates molecular property assessment with safety data to characterize novel compounds comprehensively.