Computational design of novel protein-drug delivery systems

Cancer is one of the leading causes of death throughout the world and the number of cases per year is reported to rise to 23.6 million by 2030. Amongst the different types of treatments available, chemotherapy represent the most common one. Despite its proven capability of tumour shrinkage and prevention from coming back after surgery, several factors limit its potential. These include poor bioavailability and biodistribution of the majority of the chemotherapeutic agents commonly used, the high dose required, their numerous adverse side effects, the development of drug resistance and non-specific targeting. To overcome these limitations, I propose to develop novel protein-based drug delivery system capable of selectively transporting large quantities of chemotherapeutics at the tumour-site thus conferring greater therapeutic indices and efficacy. The new systems are based on proteins, natural existing polymers, that have the intrinsic property of binding small molecules with high affinity and specificity. The project is structured in two phases. In the first phase I applied FuncLib, an automated method that uses phylogenetic analysis and Rosetta design calculations, to design mutants with higher affinity toward two selected chemotherapeutic agents. In the second phase, fifty-five designs were selected according to G Rosetta energy score and structural diversity, synthesised and assembled using a repertoire of molecular biology techniques.