Dimensionality Reduction-Based Analysis of the Molecular Dynamics of G
Protein-Coupled Receptors
Abstract
G-protein coupled receptors (GPCRs) are the most abundant and
varied family of transmembrane proteins. Beyond their basic biological
functions, they are of relevance to pharmacology, as they are involved
in a variety of human pathologies. Molecular dynamics (MD) are a
reliable and effective simulation technique that allows us to
investigate and examine the structure and activity that shape
biomolecular energy systems. In this article, Dimensionality Reduction
(DR) methods are used to explore protein trajectories by generating
different data abstractions with the objective of finding the best
simplified representation of such proteins. For that, these methods are
applied to publicly available data from a GPCR MD database. The protein
abstractions generated by several DR methods applied to the inactive,
intermediate, and active conformational states of the GPRC MD
simulations are compared through their entropy quantification and visual
representation. In addition, experiments involve three types of MD data
representation, namely the 3D position of amino acids, the distances
between the helices of the molecules, and the dihedral angles
representing the torsion angles of Psi and Phi of each amino acid. The
reported results show how some of the DR methods capture the smooth
temporal evolution of the GPCR representations and their state
transitions.