Descripció del projecte
The Endocannabinoid system (ECS) was recently discovered as a master regulator of cellular homeostasis and therefore as a target to prevent or treat a vast number of diseases ranging from cancer to Alzheimer’s to obesity. Despite the ever-increasing list of constituent members of the ECS, the full extent of the ECS is currently unknown. Computational biochemistry or biosimulation is a powerful technique that can help predict novel cannabinoid receptors and ligands within the ECS.
By using computational-chemistry approaches such as QM/MM, the proposed study aims to create, on the one hand, a statistical dataset of the binding affinities that relates cannabinoids and receptors, as well as detailed molecular information about the receptors: binding site, residues involved in the interaction with the cannabinoid, etc. On the other hand, this project aims to obtain a set of pharmacophores or a description of molecular features that are necessary for molecular recognition of a ligand by a biological macromolecule.
These results would provide a complete overview of the dynamics between cannabinoids and their known receptors. Since these receptors are involved or related to many diseases, the results could orient towards the design of medical treatments.
