Abstract:
Chemical and biological processes are stochastic and intrinsically heterogeneous at both microscopic and mesoscopic levels. The present thesis investigates the microscopic mechanisms of such processes using discrete-state stochastic modelling frameworks. The first section explores the impact of macromolecular crowders on a protein molecule’s search for target sequences on DNA, revealing how the nature of crowders, the length and position of crowding and non-specific crowder-protein interactions may control the search process. The ubiquitous nature of these crowders may influence other biological processes as well. We probe the capture and translocation of ssDNA through biological nanopores in crowded conditions, providing precise analytical solutions applicable to single-molecule experiments. In the context of chemical processes, the final section focuses on understanding the molecular mechanisms of heterogeneous catalytic reactions mediated by individual nanoparticles. Our theoretical investigation provides a quantitative microscopic understanding of catalytic cooperativity between different active sites on a single nanocatalyst. In conclusion, the interdisciplinary investigation presented in this thesis aims to highlight the strength of discrete-state stochastic modelling techniques in understanding complex chemical and biological systems, offering crucial insights for advancing both theoretical and experimental efforts.
