Supervisors info:
Κανδαράκης Ιωάννης, Καθηγητής, Μηχανικών Βιοϊατρικής, Πανεπιστήμιο Δυτικής Αττικής
Summary:
Nanomaterials offer new promising applications in medicine, physics, engineering and other fields varying from energy storage to paints, industrial catalysts and drug delivery. The increasing applications of these engineered nanostructures require that they have specialized properties for each of their desired functions; these properties can be acquired through functionalization of their surface with various chemical groups and architectures. Nanoparticles can be functionalized with surface attachment of ligands such as small molecules, surfactants, dendrites, polymers, biomolecules, etc.
Indefinite combinations of functionalized nanoparticles can exist when coating them with different ligands. To test which functionalized nanoparticles are best suited for the intended nanoparticle application, one may resort to wet lab experiments. However, experiments can be costly considering different experimental steps such as nanoparticle synthesis, functionalization, characterization, quality control, conduction of experiments etc. One way to minimize the cost and time needed for these experiments, is to first run inexpensive computer simulations in order to predict which nanoparticles are best suited for the intended application, and then test in the lab only a few nanoparticles, which are predicted as promising from simulations.
This master thesis describes the creation of a web-based tool, which allows users to coat any nanoparticle with a desired ligand, creating functionalized nanoparticles ready for simulation. The operation of this tool is based on the processes described below. First, the user uploads the nanoparticle and ligand coordinates. The algorithm reads the nanoparticle and ligand elements, their coordinates and the ligand bonds, and prompts the user to select which nanoparticle element will interact with the ligand. To identify the positions of these elements on the nanoparticle surface as well as the surface area of the nanoparticle, the Concave-Hull algorithm is implemented. The ligand is then rotated in 3D space and the area of the ligand along its main axis is calculated. Using the area of the ligand, the recommended grafting density of the nanoparticle is calculated and provided to the user. Then, the user is asked to choose whether a bond should exist between the nanoparticle and the ligand elements and the default bond value is calculated from the distance table of chemical bonds and provided to the user. Finally, in order to construct the topology file for molecular mechanics simulations, the bonded and non-bonded empirical force field parameters are requested from the user through the browser interface panel. After the input of the desired parameters, the algorithm distributes, replicates and places the ligands on the nanoparticle surface, and provides three nanoparticle-ligand complex files for download: i) coordinate file with .pdb extension, ii) coordinate file with .gro file extension, iii) topology file for use with the GROMACS Molecular Dynamics package for molecular simulation. The algorithm is developed in Python and the associated web server with HTML, PHP, Javascript and CSS. The tool can be temporarily accessed and used at http://83.212.106.195/nanofunctioner.html
Keywords:
Nanomaterials, ligands, functionalized nanoparticles, Molecular Dynamics simulations, web development
