Development of reverse docking protocols for virtual screening in nanomedicine

One of the first computational chemistry tools that have been used in pharmaceutical research is molecular docking, which infers the interaction between two molecules, usually a small active compound and a receptor, on the basis of their 3D structures. During my three years of PhD studies I worked mainly on re-purposing molecular docking tools to investigate the interactions between a single molecule of interest and a collection of proteins of pharmacological interest. Since this process is essentially the inverse of what is usually done in pharmaceutical research, the technique is called reverse screening. Reverse screening can help in the identification of new therapeutical targets, in predicting toxicological effects and unwanted interactions or in the design of new therapeutic platforms based on the conjugation between a synthetic compound and a protein carrier. In this work, reverse screening has been applied to porphine and phthalocyanine, two chemically related photosensitizers employed in photodynamic therapy, and Gd@C82, the most promising endohedral gadofullerene for theranostic applications. For each of these two types of molecule, a reverse docking protocols has been designed and has allowed the discovery of new potential pharmaceutical targets and carrier systems that can help overcome the physico-chemical limitations to their widespread usage in nanomedicine. Finally, the application of reverse screening protocols to study the interactions between small nanoparticles (d < 5 nm) and 2D materials against bio-molecules was explored. Although theoretically possible, the sheer number of atoms that must be considered and the nanoparticle size result in a plethora of problems since docking tools have been designed with small active molecules in mind. Nevertheless, a new protocol has been devised to perform reverse screening of gold, silver and silica nanoparticles and 2D materials and it has been successfully tested on a small number of proteins.