Matteo Levrone
Multitarget Graph Neural Networks Approach to predict Selective Class I HDAC Inhibitors.
Rel. Jacek Adam Tuszynski, Gianvito Grasso, Marcello Miceli, Gabriele Maroni. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2026
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Abstract
Histone deacetylases (HDAC) are a superfamily of enzymes, divided into classes due to their different roles in biological mechanisms. In particular, class I HDAC are zinc-dependent nuclear enzimes that remove acetil groups from histons, causing epigenetic modifications that deeply affect gene expression. It has been deeply documented that, due to their role in DNA transcription, HDAC dysregulation is involved in a plethora of maladies, such as neurological disorders, cardiovascular diseases, cardiometabolic and fibrotic diseases, autoimmune/inflammatory conditions, and infectious and viral diseases. On top of that, HDAC is especially involved in various forms of cancer. Being a known and priority target, various forms of HDAC inhibitors (HDACi) have been studied and marketed, most of them being pan-inhibitors, which are not selective for a specific isoform.
The lack of targeting efficiency can cause a plethora of side effects, compromising the therapeutic treatment
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