The Group develops a in silico and in cogito approach for hydrated NanoBioSystems under realistic conditions (e.g., nanoparticles and protein solutions at physiological conditions over timescales up to hours). Within the framework of Interdisciplinary Statistical Physics, we combine theory and atomistic simulations of hydrated bio-interfaces (e.g., proteins or membranes) and nano-interfaces (e.g., nanoparticles and nanomaterials) with coarse-grain models for protein folding and design, protein adsorption, aggregation and crystallization, confined complex liquids, and hydrated nano-systems. We collaborate with several experimental groups worldwide to find answers for fundamental questions (Which properties make water unique for biological processes and life?) and applications (What makes a nanoparticle safe and sustainable by design? How can we develop Nanomedicine against cancer or neurodegenerative diseases? How can we improve nano-theranostics?).
Giancarlo Franzese (Associate Professor) gfranzese(at)ub.edu
Carlos Calero Borrallo (Tenure-Track Lecture)
Oriol Vilanova Gabarrón (Predoctoral Researcher)
Gionni Marchetti (Technician)
Exploring optimal graphene slit-pore width for the physical separation of water-methanol mixture. Bellido-Peralta R.; Leoni F.; Calero C.; Franzese G. 2023, Journal of Molecular Liquids. 391 , 123356. Doi: 10.1016/j.molliq.2023.123356
Correction to: Protein Unfolding and Aggregation near a Hydrophobic Interface. March D.; Bianco V.; Franzese G. 2023, Polymers, 15, 9, 2053. Doi: 10.3390/polym15092053
Size–Pore-Dependent Methanol Sequestration from Water–Methanol Mixtures by an Embedded Graphene Slit. Bellido-Peralta R.; Leoni F.; Calero C.; Franzese G. 2023, Molecules, 28, 9, 3697. Doi: 10.3390/molecules28093697
Using Car-Parrinello simulations and microscopic order descriptors to reveal two locally favored structures with distinct molecular dipole moments and dynamics in ambient liquid water. Skarmoutsos I., Franzese G., Guardia E. Journal of Molecular Liquids, 364, 119936, 2022
Modeling and Simulation of Lipid Membranes. Martí J., Calero C. Membranes, 12, 6, 549, 2022
Protein unfolding and aggregation near a hydrophobic interface. March D., Bianco V., Franzese G. March D., Bianco V., Franzese G. Polymers. 2021, 13, 1, 153
Redefining the concept of hydration water near soft interfaces. Martelli F., Calero C., Franzese G. Biointerphases. 2021, 16, 2, 020801
Structure and dynamics of nanoconfined water and aqueous solutions. Corti H.R., Appignanesi G.A., Barbosa M.C., Bordin J.R., Calero C., Camisasca G., Elola M.D., Franzese G., Gallo P., Hassanali A., Huang K., Laria D., Menéndez C.A., de Oca J.M.M., Longinotti M.P., Rodriguez J., Rovere M., Scherlis D., Szleifer I. European Physical Journal E. 2021, 44, 11, 136
In Silico Evidence That Protein Unfolding is a Precursor of Protein Aggregation. Bianco V., Franzese G., Coluzza I. ChemPhysChem, 2020, 21(5), 358-358
Network Topology in Water Nanoconfined between Phospholipid Membranes. Martelli F., Crain J., Franzese G. ACS Nano, 2020, 14(7), 8616-8623
Water under extreme confinement in graphene: Oscillatory dynamics, structure, and hydration pressure explained as a function of the confinement width. Calero C., Franzese G. Journal of Molecular Liquids. 2020, 317, 114027
D. March, V. Bianco, and G. Franzese, Protein Unfolding and Aggregation near a Hydrophobic Interface, Polymers 13, 156 (2021) [Accepted on 24/12/2020]
L.E. Coronas, O. Vilanova, V. Bianco, F. de los Santos, and G. Franzese, The Franzese-Stanley Coarse Grained Model for Hydration Water in “Properties of Water from Numerical and Experimental Perspectives”, F. Martelli ed. (CRC Press, 2020), accepted. [Invited by the Editor; Available as e-print: arXiv: 2004.03646]
Autotermoforesis en la nanoescala. CNS2022-135395. IP: Carlos Calero Borrallo. Ministerio de Ciencia e Innovación (2023-2025)
Física estadística para materia blanda Bio-Nano. PID2021-124297NB-C31. IP1: Giancarlo Franzese/IP2: Carlos Calero Borrallo. Convocatoria 2021 de ayudas a «Proyectos de Generación de Conocimiento». Modalidad Proyectos de «Investigación No Orientada». Ministerio de Ciencia, Innovación y Universidades. (2022-2025)
Física estadística para simulaciones a gran escala de sistemas bioinspirados hacia la erradicación de tumores (PGC2018-099277-B-C22) PI: Giancarlo Franzese. Ministerio de Ciencia, Innovación y Universidades (2019-2021)
Protein-Nanoparticle Corona Formation investigated by UV Resonant Raman spectroscopy (CALIPSOplus H2020-730872-proposal n. 20195350) PI: Giancarlo Franzese. Elettra-Sincrotrone Trieste within the European Union’s Horizon 2020 program (2019-2021)
Statistical Physics for Biological Systems at the Nanoscale (EIN2020-112431) PI: Giancarlo Franzese. Ministerio de Ciencia e Innovación (2020-2021)
The group is co-responsible of a remarkable infrastructure dedicated to scientific computing, shared with three other PIs of the UB: the “Laboratorio de Supercomputación en Física Estadística”, which is used to run the simulations and numerical calculations necessary for the development of scientific projects. Currently, this laboratory comprises two dedicated computing clusters: one cluster with 64-bit CPU machines, consisting of 39 nodes, for a total of 772 virtual cores working with Hyper- Threading Technology and 1404 Gb of RAM; and a second cluster of 9 GPU platforms, with INVIDIA GTX 460 (x6), 760, 780, 980, 1060 (x2) and RTX 2081Ti (x11) cards, for a total value of more than 200.000€.
The group has an extended network of active scientific collaborations with many highly prestigious scientific centers all over the world, such as Boston (US), University of Bristol (UK), IBM (UK), University College Dublin (IE), Royal College of Surgeons in Ireland (IE), Elettra – Sincrotrone Trieste (IT), Università di Rome La Sapienza (IT), Università di Torino (IT), National Hellenic Research Foundation (GR).