###### Abstract  
Two independent 1.5 \(\upmu\)s long MD simulations were conducted for the fully atomistic model of the human beta2-adrenergic receptor (\(\beta_{2}\)AR) in a complex with a G protein to investigate the signal transmission in a fully active state via mutual information and transfer entropy based on \(\alpha\)-carbon displacements and rotameric states of backbone and side-chain torsion angles. Significant correlations between fluctuations in \(\alpha\)-Carbon displacements were mostly detected between transmembrane (TM) helices, especially TM5 and TM6 located at each end of ICL3 and TM7. Signal transmission across \(\beta_{2}\)-AR was quantified by shared mutual information; a high amount of correspondence was distinguished in almost all loop regions when rotameric states were employed. Moreover, polar residues, especially _Arg_, made the most contribution to signal transmission via correlated side-chain rotameric fluctuations as they were more frequently observed in loop regions than hydrophobic residues. Furthermore, transfer entropy identified all loop regions as major entropy donor sites, which drove future rotameric states of torsion angles of residues in transmembrane helices. Polar residues appeared as donor sites from which entropy flowed towards hydrophobic residues. Overall, loops in \(\beta_{2}\)AR were recognized as potential allosteric hot spot regions, which play an essential role in signal transmission and should likely be used as potential drug targets. transfer entropy; rotameric state; loop region; allosteric network; mutual information +
Footnote †: journal: Medical  
studies as they often provide high specificity/selectivity in comparison to orthosteric binding site residues, which are mostly conserved among species [9; 10; 11; 12; 13; 14]. Over the years, several graph-based algorithms have been developed to estimate this functional allosteric circuit with its constitutive residues [15; 16; 17]. Here, we used correlated fluctuations between residues to establish an allosteric communication network, which is described in terms of entropy/information transfer from one site to another. Transfer entropy was previously introduced by [PERSON] in 2000 as an information-theoretic measure to quantify the exchange of information between two systems [18] and was later used in several MD studies as an analysis tool to understand the effects of various structural changes [19; 20; 21; 22; 23]. In our current study, the transfer information of coupled fluctuations was not only based on translational C\(\alpha\) displacements, as often considered in several studies, but also on rotational displacements of backbone and side-chain torsion angles in each residue. The thermodynamic importance of side-chain variability was previously emphasized in calmodulin-ligand binding studies [24; 25]. Furthermore, NMR mutational studies demonstrated the contribution of side-chain fluctuations to long-range communication networks [26]. Previously, using Monte Carlo sampling, [PERSON] and his coworkers demonstrated that allosteric communication in proteins can be transmitted by correlated side-chain fluctuations only [27]. However, they assumed a fixed backbone rotation and quantified the correspondence using a mutual information metric only. Here, our study will be the first to consider both backbone and side-chain rotatable bonds altogether to identify the correlated fluctuations in the rotameric states of these torsion angles. In addition, we will use another information-theoretic measure, the so-called _\"transfer entropy\"_ to determine the dynamics of information transport, i.e., the direction of the exchange of information from one site to another distant site in the receptor at a future time. The system under study is a human beta2-adrenergic receptor (\(\beta_{2}\)AR) in complex with G protein representing the active state. It was subjected to two separate 1.5 \(\upmu\)s long MD simulations, which amounted to a 3 \(\upmu\)s long trajectory.