DE GIOIA LUCA

Persico, F., Galuzzi, B., Pellegrino, M., Claudel, A., De Gioia, L., Nastri, F., et al. (2026). Predicting Metalloprotein Redox Potentials with Machine Learning: A Focus on Iron–Sulfur Systems. Intervento presentato a: XIV International Conference on Hydrogenase and Other Redox Metalloenzymes 2026, Leicester, UK. Detail

Incarbone, S., De Gioia, L. (2026). Recent Advancements in Information Ratchet Design. MOLECULES, 31(8) [10.3390/molecules31081282]. Detail

Rovaletti, A., Wu-Lu, M., Arrigoni, F., De Gioia, L., Ryde, U., Greco, C., et al. (2026). QM/MM Modeling of the Electronic Structure and Properties of the Fe-S Clusters in Desulfovibrio desulfuricans [FeFe]-Hydrogenase. INORGANIC CHEMISTRY, 65(25), 13988-13999 [10.1021/acs.inorgchem.6c01252]. Detail

Orlando, C., Bellei, M., Zampolli, J., Mangiagalli, M., Di Gennaro, P., Lotti, M., et al. (2025). Comparative analysis of Polyethylene-Degrading Laccases: Redox Properties and Enzyme-Polyethylene Interaction Mechanism. CHEMSUSCHEM, 18(10) [10.1002/cssc.202402253]. Detail

Pozzoli, U., Forni, D., Arrigoni, F., Cagliani, R., De Gioia, L., Sironi, M. (2025). Mycobacterium tuberculosis uses intrinsically disordered, fast evolving proteins to interact with conserved host factors. GENOME BIOLOGY, 26(1) [10.1186/s13059-025-03854-6]. Detail