To: 05/02/2020 14:00
Recently, in the field of bio-inspired materials, the non-covalent self-assembly of relatively simple peptide based molecules has gained increasing attention for the formation of nanostructured, biologically functional materials, including nanofibers and hydrogels, all with nanoscale order. Moreover, polypeptide self-assembly is often associated with human medical disorders. Understanding the physicochemical determinants that underlie peptide self-assembly is a fundamental step, in view of the rational design, or redesign of already existed nano building blocks for biotechnological and biomedical applications. The theoretical principles that govern self-assembly and polymorphism of these building blocks are currently unknown. Computer simulations contribute to the clarification of some of the basic questions related to structural, conformational and dynamical properties of these molecules from first principles. Therefore, one part of our work concerns the modeling of small biological molecules, such as peptides and lipids as well as of proteins, where the self-assembly propensity and the conformational properties, are studied through all-atom Molecular Dynamics simulations using an explicit solvent model.
More complex systems constitute another direction of our work, which concerns the modeling of m-RNA molecules which are suggested as navigators of ribonucleoproteins for individual breast cancer therapy. Through atomistic Molecular Dynamics simulations the detailed structure-properties relations of such bioactive complexes will be explored in the atomic level. Our main goal is to study the associative behavior between RNA and an ionizable lipid in an aqueous environment and at physiological pH conditions. This will provide important information regarding the different stages involved in the complexation process and will assess the potential of the formed complex to be part of a delivery mechanism for the nucleic acid cargo. The detailed information obtained though this study, may provide new insight towards a rational design of optimized lipid-based gene delivery vectors.