Project summary
This subproject serves as a platform for the design of novel CatSper and Slo3 inhibitors. An AI-guided approach to in silico drug development is pursued, based on homology models of potential inhibitor-binding sites in CatSper and Slo3. New inhibitors are identified through the analysis of known CatSper and Slo3 inhibitors and virtual compound screening. Using high-resolution channel structures, the project will transition towards structure-based drug development. The optimisation of validated inhibitors will employ AI-supported generative design and will be integrated into a design–make–test–analyse cycle. The aim is to develop highly potent and selective CatSper and Slo3 inhibitors.
Based on a homology of the human CatSper transmembrane domain, we investigate the binding of known inhibitors like mibefradil to generate hypotheses for ligand binding modes These models guide virtual screening of compound libraries using protein–ligand docking and pharmacophore-based searches to identify novel CatSper inhibitor. Promising hits are subsequently optimized using AI-driven molecular design tools to improve binding affinity and ADME/Tox properties.
