Distinctive communication networks in inactive states of β₂‐adrenergic receptor: Mutual information and entropy transfer analysis

Abstract

Mutual information and entropy transfer analysis employed on two inactive states of human beta-2 adrenergic receptor (β 2-AR) unraveled distinct communication pathways. Previously, a so-called "highly" inactive state of the receptor was observed during 1.5 microsecond long molecular dynamics simulation where the largest intracellular loop (ICL3) was swiftly packed onto the G-protein binding cavity, becoming entirely inaccessible. Mutual information quantifying the degree of correspondence between backbone-C α fluctuations was mostly shared between intra-and extra-cellular loop regions in the original inactive state, but shifted to entirely different regions in this latest inactive state. Interestingly, the largest amount of mutual information was always shared among the mobile regions. Irrespective of the conformational state, polar residues always contributed more to mutual information than hydrophobic residues, and also the number of polar-polar residue pairs shared the highest degree of mutual information compared to those incorporating hydrophobic residues. Entropy transfer, quantifying the correspondence between backbone-C α fluctuations at different timesteps, revealed a distinctive pathway directed from the extracellular site toward intracellular portions in this recently exposed inactive state for which the direction of information flow was the reverse of that observed in the original inactive state where the mobile ICL3 and its intracellular surroundings drove the future fluctuations of extracellular regions.

HB‐EGF promotes progenitor cell proliferation and sensory neuron regeneration in the zebrafish olfactory epithelium

“…For two residues to be considered in contact, at least one pair of their heavy atoms should be closer than the cutoff distance (), which was taken as 6 Å. A value of 1 was assigned for a residue pair in contact and 0 otherwise [139] as defined by . values of residue pairs between the R‐domain and Dr‐Hbegfa were calculated for every snapshot and were averaged over the whole trajectory as , where is the number of snapshots in the trajectory.…”

Gaussian network model revisited: effects of mutation and ligand binding on protein behavior

“…In the paper, we hinted in several places that increase in MI and increase in binding affinity and stability are similar effects. We cite here only a few of the numerous studies which suggest MI as a measure for binding affinity and binding stability [45][46][47][48][49][50][51][52].…”

Dynamic correlations: exact and approximate methods for mutual information

“…Several computational studies have investigated mutual information in proteins using both exact ( McClendon et al 2014 , Cortina and Kasson 2016 , Long and Tian 2016 , Singh and Bowman 2017 , Sogunmez and Akten 2020 , Shao et al 2021 , Schneider and Antes 2023 ), mostly considering the magnitudes of fluctuations, and approximate calculations ( Lange and Grubmüller 2006 , Jana et al 2011 , Rennebaum and Caflisch 2012 , Invernizzi et al 2014 , Scarabelli and Grant 2014 , Köhler et al 2015 , Tiberti et al 2015 , Ahmed and Barakat 2017 , Milenkovic and Bondar 2018 , Zhang et al 2018 , Foster et al 2021 , Payne et al 2022 , Tekpinar and Yildirim 2022 ). By relying on the three approximations, calculations requiring shorter simulations or only static crystal structures may become possible.…”