Although aromatase is a validated target for hormone-dependent breast cancer, resistance and toxicity highlight the need for new chemotypes with improved profiles. The aim of this project is to discover and optimise novel small-molecule aromatase inhibitors by combining large-scale exploration of chemical space with ligand- and structure-based design. BioSolveIT tools will be used to identify diverse, synthetically accessible scaffolds, while CoLibri will curate ligand information. Selected hits will be evaluated in SeeSAR through docking and HYDE scoring to prioritise favourable binding modes. Promising candidates will then be refined using ReCore and Inspirator mode for fragment growth, scaffold hopping and multi-parameter optimisation. This integrated workflow is expected to yield a curated set of optimised, computationally validated inhibitor candidates supported by clear binding rationales and strong potential for experimental follow-up.
Marialuigia intends to achieve the following milestones:
- Early Discover & Hit Identification
- Structure-Based Evaluation and Hit Refinement
- Lead-Like Candidate Selection & Final Validation