drug-discovery

You can search for bioactive compounds in ChEMBL without an API key by using this skill to query the database directly via Python requests. It retrieves compound data based on your target criteria, such as a specific protein like EGFR.

To calculate drug-likeness, this skill evaluates compound bioavailability using Lipinski's Rule of Five and Veber's Oral Bioavailability Rules. It processes the molecular data retrieved from ChEMBL to assess if a compound is a viable lead.

You retrieve drug-drug interaction data from OpenFDA by utilizing this skill's API interaction capabilities. It uses Python requests and json to query OpenFDA and parse the returned interaction profiles for your specified compounds.

Yes, you can perform ADMET analysis on compounds found in ChEMBL. This skill interprets Absorption, Distribution, Metabolism, Excretion, and Toxicity profiles, allowing you to evaluate the safety and efficacy of potential lead compounds.

The best way to identify lead compounds is to search ChEMBL for bioactive molecules, calculate their drug-likeness using Lipinski and Veber rules, and check OpenFDA for drug interactions. This skill automates that entire cheminformatics workflow.

You do not need an API key to search for bioactive compounds in the ChEMBL database. The skill handles OpenFDA drug interaction retrieval and ChEMBL searches using standard Python requests without requiring authentication.