| Popis: |
Computer aided drug design (CADD) plays a crucial role in the drug discovery pipeline e.g. in virtual screening of chemical databases, de novo drug design, and lead optimization. Due to the increased numbers of protein structures elucidated, structure-based methods for developing pharmacophore models have started gaining in popularity and are becoming of particular importance. There have been a number of studies combining such methods with the use of molecular dynamics (MD) simulations to model protein exibility. In this project, the development and application of a new methodology, based on coarse grained (CG) MD, through the use of the MARTINI forcefield, and employed to explore protein ligand interactions, will be presented. An overview of the history of CADD is presented, along with current computational fragment based methods available for exploring protein-ligand interactions. An overview of the theory and methods behind MD simulations both all atom and CG is also provided. In the first results chapter, the parametrization of MARTINI beads as pharmacophoric probes, the analysis protocol and the application of this method to a data set of water soluble targets of pharmacological interest is described. The results suggest that the pharmacophoric probes have the ability to identify protein-ligand interactions on the targets of interest. The probes are also able to identify the residues involved in forming ligand binding interactions, showing a particular accuracy in identifying "hotspot" interactions. In the second results chapter, the extension of the initial data set to a range of GPCRs is described. The results suggest that the pharmacophoric probes have the ability to accurately explore both the orthosteric and allosteric binding sites of the GPCR targets and accurately identify the interactions and residues involved in ligand binding. This is done without the need to embed the protein in a lipid bilayer. In the final results chapter, the application of the dynamic pharmacophoric probes to identifying PIP2 and cholesterol binding sites, on membrane proteins, is presented. The results suggest that the probes can indeed identify these binding sites, along with identifying the residues that are involved in binding the PIP2 head groups. This was also done without embedding the protein in a lipid bilayer, which is the usual practice for identifying lipid binding interactions, reducing the computational resource requirements. |
