Andrea Toscana
AI-driven design of novel inhibitors of the FAB12 protein for drug development against advanced prostate cancer: the use of Boltz-2 for structure and affinity prediction.
Rel. Jacek Adam Tuszynski. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2026
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Abstract
Prostate cancer (PC) remains one of the most spread tumors worldwide and it is included in the top five of cancer death among men. While therapeutic approaches exist, some forms of PC –such as advanced and metastatic forms– continue to be a challenge for the modern medicine, leading research towards novel molecular targets. Among the emerging candidates, Fatty Acid-Binding Protein 12 (FABP12) has attracted attention because of its overexpression in metastatic cancer tissues and its involvement in lipid metabolism reprogramming and epithelial-to-mesenchymal transition (EMT). However, no selective FABP12 inhibitors have been developed and the lack of a crystalized structure for this protein results in a significant challenge for a structure-based drug design pipeline.
This thesis presents the computational work done for the prediction of the FABP12 structure and the identification of novel inhibitor candidates
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