Automated Bio-Marker: Nano-medicine, which uses hard or soft nano-particles that attach selectively to tumours, is one of the most promising fields for cancer imaging and treatment. A major challenge for progress in this field is the development of Anti-Cancer Drugs (ACDs) which are able to target directly the tumour cells, without affecting healthy cells. ACDs are identified mainly through large and expensive trial-and-error screenings, with limited help from computational modelling. In collaboration with Prof. I. Coluzza, I am developing Automated Bio-Marker, a novel computational protocol to design protein ligands that can be used as coating for drug-delivery vehicles to cancer cells. The computational design protocol adopted in this project is based on Caterpillar, a coarse-grained model recently introduced by Prof. Coluzza and on advanced stochastic techniques to explore the phase space of ligands. Using these instruments allows for control over the ligand-receptor binding affinity without affecting the selectivity. This project focuses in particular on CD47, a signal regulatory protein alpha receptor (SIRPa) present in many cancers such as ovarian, breast, colon, bladder, glioblastoma, hepatocellular carcinoma, and prostate.
Physics of Viruses: Viruses are subcellular agents that infect organisms in order to reproduce themselves. While viruses can not reproduce autonomously, they are subject to several evolutionary pressures and are arguably among the simplest systems on which evolution can be studied. Most viruses encode their genes on RNA genomes, often single-stranded (ssRNA). The simplest of such single-stranded RNA viruses are constituted by a single molecule of RNA surrounded by a protective protein shell, called viral capsid. In several cases, these viruses reproduce themselves through a spontaneous self-assembly process in which the protein of the capsid attach to the RNA genome. Viral ssRNAs often have physical properties which facilitate the formation of the virus, suggesting that their genome encodes not only for viral proteins, but also for its own physical properties. Using statistical mechanics and computational methods I am investigating the evolutionary relationship between the physical properties viral ssRNA and its functional and genetic properties.
Topological entanglement in polymers: Long polymers, as well as compact polymers, are found to be knotted with high probability. The presence of knots affects polymers' physical properties and has deep effects on the functional properties of biopolymers like dsDNA or proteins. Recent studies also suggested that tight knots may be manipulated for nanotechnological applications. Using computational methods I am investigating the equilibrium and dynamical properties of knots in various polymeric systems, focussing in particular on the possible strategies to manipulate them in experimentally reproducible setups.