Network-based approaches to study human health and disease
18 febbraio 2025
Andreas Zanzoni is an Associate Professor of Bioinformatics and Genomics at the Department of Biology, Aix-Marseille University. His research focuses on understanding the molecular basis of human diseases through network-based approaches, with a particular emphasis on:
• Host-microbe protein interactions in chronic diseases
• The role of protein-RNA interactions in cellular networks
• Multifunctional proteins, regulatory sites, and signal transduction
• Mapping host-pathogen interactomes, particularly between coronaviruses and the human host
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How artificial intelligence is reshaping computer-aided drug design
04 giugno 2025
Computer-aided drug design (CADD) has become a key tool in modern drug discovery, significantly accelerating development while reducing costs. Recent advancements in CADD integrate various computational approaches, combining physics-based modeling with emerging artificial intelligence (AI) technologies. I will illustrate how atomic-level simulations have played a key role in identifying new drug candidates for diseases with major socio-economic impact, while advancements in AI, driven by increasing data availability and continuous model refinement, are unlocking new possibilities for predicting therapeutic target structures, analyzing molecular properties, and designing novel molecules.
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Comprehensive in silico characterization of mitochondrial carriers of the SLC25 protein family
11/06/2025
Mitochondria and cytosol metabolic processes require the import/export of metabolites across the impermeable inner mitochondrial membrane. The transport of these molecules is performed by a family of membrane transporters known as the mitochondrial carriers (MCs), which act as master regulators of cell metabolism in health and disease. Further, MCs are key players in the reprogramming of cell metabolism that occurs in cancer. Several of them are overexpressed in various cancer types as essential gatekeepers of the trafficking of metabolic intermediates. These represent promising targets to develop novel therapies aimed at restoring the physiological metabolic processes, reducing cancer cell proliferation and metastasis formation.
In this framework, in the last few years we employed a computation approach to uncover the structural determinants of endogenous and exogenous (drug-like) ligands recognition of several members of this protein family. In addition, we also developed a computational protocol for the de-orphanization of transporters whose ligand is still unknown with the aim of uncovering novel mitochondrial metabolic pathways. Prominent results of these activities will be illustrated and discussed.
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