Computational Modeling and Simulations of Protein-Drug and Protein-Protein Complexes: as potential target for therapeutics development

The main objective of my thesis is to illustrate the potential of computational modeling techniques in determining decisive protein-protein interactions and protein-ligand interactions of two relevant macromolecular biological systems associated to human diseases. Computational tools such as homology modeling, molecular docking, molecular dynamics simulations and the developed protocols implemented for the preparation, simulation and analysis of each biological system are presented. The first contribution is the simulation of modeling of protein-peptide-protein complexes related to adaptive immune system and multiple sclerosis disease. Investigation of molecular similarity between self-peptide and two microbial peptides for the complexes with respect to molecular recognition mechanism is presented. The second contribution is the investigation of protein-ligand interactions of biological systems associated to Alzheimer’s disease. Computational results are compared with experiments to evidence the origin and degree of selective inhibition displayed by 2-Phenylbenzofurans ligands against butyrylcholinesterase (BChE) protein. The final contribution is on the application of a priori knowledge gathered on protein-ligand interactions in designing ligands with specific structural modifications that display an improved inhibitory activity against BChE protein. In conclusion, therapeutical perspectives and application of hybrid computational approaches to design and develop of potential drugs are discussed.