drug-discovery

Search bioactive compounds in ChEMBL by specifying a target like EGFR in a simple command-line query. This automated pharmaceutical research task requires no API key and returns matching compound data directly for further drug discovery analysis.

Calculate drug-likeness by evaluating compounds against Lipinski's Rule of Five and Veber's Oral Bioavailability Rules. This automated analysis provides immediate feedback on whether a compound meets the criteria for oral bioavailability in pharmaceutical research.

Look up drug interactions and adverse events by querying the OpenFDA database through curl and Python scripts. This approach automates safety and interaction research, retrieving relevant adverse event data without manual API navigation.

No API key is required to search for bioactive compounds in ChEMBL. The drug discovery automation handles external API requests seamlessly via curl, so you can execute pharmaceutical research tasks without prior external service registration.

Yes, this drug discovery tool requires Python3 and curl to interpret ADMET profiles. It leverages various Python libraries for data manipulation to analyze absorption, distribution, metabolism, excretion, and toxicity profiles of pharmaceutical compounds.

Automate lead optimization by combining compound search results, drug-likeness calculations, and ADMET profiles. The tool processes these pharmaceutical research parameters through Python scripts to assist in optimizing lead compounds for further development.