Nuclear receptors (NRs) are a superfamily of transcription factors whose activity is regulated upon the binding of a specific ligand. In this work, we utilized the new AI-driven Drug Design (AIDD) module within the ADMET Predictor® suite to derive novel and promising RORyT agonists with suitable predicted ADMET and PK properties. The AIDD module uses chemically intelligent SMIRKS transformations to generate new molecules based on seed compounds. The generation process is channeled towards molecules of desired properties within a multicriteria optimization loop. The objectives, including potency and selectivity at the chosen target, synthetic feasibility, and ADMET/pharmacokinetic (PK) properties are considered simultaneously. Thus, the properties of optimized molecules are on a Pareto front and are excellent candidates for experimental verification.
By Rafał A. Bachorz
Ninth Joint Sheffield Conference on Chemoinformatics, – University of Sheffield, UK