Exploratory analysis of the molecular dynamics of cannabinoid receptor proteins

Abstract

G protein-coupled receptors, also known as GPCRs, are a kind of protein receptors that transfer signals to the inner part of cells when a certain kind of molecule is detected outside. In this thesis this kind of receptors have been analyzed from a molecular dynamics perspective. The interest in GPCRs is their structural and functional complexity, which confers great richness to their ligand space because the molecular space for drug design will be more extensive. The molecular dynamics approach allows us to explore the conformational space of GPCRs by obtaining large scale time series of protein conformations by computational simulation. Machine learning techniques have been used to differentiate between different ligand-induced conformational changes in GPCR cannabinoid receptors, focusing on feature selection in the form of protein motif search and on the analysis of different strategies for the transformation of raw molecular dynamics data into alternative representations that could be more suitable for, ease and improve the performance of machine learning based methods.