Molecular Dynamics and Machine Learning Study of Adrenaline Dynamics in the Binding Pocket of GPCR

G-protein coupled receptors (GPCRs) are the most prominent
family
of membrane proteins that serve as major targets for one-third of
the drugs produced. A detailed understanding of the molecular mechanism
of drug-induced activation and inhibition of GPCRs is crucial for
the rational design of novel therapeutics. The binding of the neurotransmitter
adrenaline to the β2-adrenergic receptor (β2AR) is known to induce a flight or fight cellular response,
but much remains to be understood about binding-induced dynamical
changes in β2AR and adrenaline. In this article,
we examine the potential of mean force (PMF) for the unbinding of
adrenaline from the orthosteric binding site of β2AR and the associated dynamics using umbrella sampling and molecular
dynamics (MD) simulations. The calculated PMF reveals a global energy
minimum, which corresponds to the crystal structure of β2AR–adrenaline complex, and a meta-stable state in which
the adrenaline is moved slightly deeper into the binding pocket with
a different orientation compared to that in the crystal structure.
The orientational and conformational changes in adrenaline during
the transition between these two states and the underlying driving
forces of this transition are also explored. Based on the clustering
of MD configurations and machine learning-based statistical analyses
of time series of relevant collective variables, the structures and
stabilizing interactions of these two states of the β2AR–adrenaline complex are also investigated.