Graph-based algorithms to dissect long-distance water-mediated H-bond networks for conformational couplings in GPCRs.

Changes in structure and dynamics elicited by agonist ligand binding at the extracellular side of G protein coupled receptors (GPCRs) must be relayed to the cytoplasmic G protein binding side of the receptors. To decipher the role of water-mediated hydrogen-bond networks in this relay mechanism, we have developed graph-based algorithms and analysis methodologies applicable to datasets of static structures of distinct GPCRs. For a reference dataset of static structures of bovine rhodopsin solved at the same resolution, we show that graph analyses capture the internal protein-water hydrogen-bond network. The extended analyses of static structures of rhodopsins and opioid receptors suggest a relay mechanism whereby inactive receptors have in place much of the internal core hydrogen-bond network required for long-distance relay of structural change, with extensive local H-bond clusters observed in structures solved at high resolution and with internal water molecules.

Structures of channelrhodopsin paralogs in peptidiscs explain their contrasting K+ and Na+ selectivities.

Kalium channelrhodopsin 1 from Hyphochytrium catenoides (HcKCR1) is a light-gated channel used for optogenetic silencing of mammalian neurons. It selects K+ over Na+ in the absence of the canonical tetrameric K+ selectivity filter found universally in voltage- and ligand-gated channels. The genome of H. catenoides also encodes a highly homologous cation channelrhodopsin (HcCCR), a Na+ channel with >100-fold larger Na+ to K+ permeability ratio. Here, we use cryo-electron microscopy to determine atomic structures of these two channels embedded in peptidiscs to elucidate structural foundations of their dramatically different cation selectivity. Together with structure-guided mutagenesis, we show that K+ versus Na+ selectivity is determined at two distinct sites on the putative ion conduction pathway: in a patch of critical residues in the intracellular segment (Leu69/Phe69, Ile73/Ser73 and Asp116) and within a cluster of aromatic residues in the extracellular segment (primarily, Trp102 and Tyr222). The two filters are on the opposite sides of the photoactive site involved in channel gating.

Graphs of protein-water hydrogen bond networks to dissect structural movies of ion-transfer microbial rhodopsins.

Microbial rhodopsins are membrane proteins that use the energy absorbed by the covalently bound retinal chromophore to initiate reaction cycles resulting in ion transport or signal transduction. Thousands of distinct microbial rhodopsins are known and, for many rhodopsins, three-dimensional structures have been solved with structural biology, including as entire sets of structures solved with serial femtosecond crystallography. This sets the stage for comprehensive studies of large datasets of static protein structures to dissect structural elements that provide functional specificity to the various microbial rhodopsins. A challenge, however, is how to analyze efficiently intra-molecular interactions based on large datasets of static protein structures. Our perspective discusses the usefulness of graph-based approaches to dissect structural movies of microbial rhodopsins solved with time-resolved crystallography.

Opioid Receptors and Protonation-Coupled Binding of Opioid Drugs.

Opioid receptors are G-protein-coupled receptors (GPCRs) part of cell signaling paths of direct interest to treat pain. Pain may associate with inflamed tissue characterized by acidic pH. The potentially low pH at tissue targeted by opioid drugs in pain management could impact drug binding to the opioid receptor, because opioid drugs typically have a protonated amino group that contributes to receptor binding, and the functioning of GPCRs may involve protonation change. In this review, we discuss the relationship between structure, function, and dynamics of opioid receptors from the perspective of the usefulness of computational studies to evaluate protonation-coupled opioid-receptor interactions.

C-Graphs Tool with Graphical User Interface to Dissect Conserved Hydrogen-Bond Networks: Applications to Visual Rhodopsins.

Dynamic hydrogen-bond networks provide proteins with structural plasticity required to translate signals such as ligand binding into a cellular response or to transport ions and larger solutes across membranes and, thus, are of central interest to understand protein reaction mechanisms. Here, we present C-Graphs, an efficient tool with graphical user interface that analyzes data sets of static protein structures or of independent numerical simulations to identify conserved, vs unique, hydrogen bonds and hydrogen-bond networks. For static structures, which may belong to the same protein or to proteins with different sequences, C-Graphs uses a clustering algorithm to identify sites of the hydrogen-bond network where waters are conserved among the structures. Using C-Graphs, we identify an internal protein-water hydrogen-bond network common to static structures of visual rhodopsins and adenosine A2A G protein-coupled receptors (GPCRs). Molecular dynamics simulations of a visual rhodopsin indicate that the conserved hydrogen-bond network from static structure can recruit dynamic hydrogen bonds and extend throughout most of the receptor. We release with this work the code for C-Graphs and its graphical user interface.

Protein-water hydrogen-bond networks of G protein-coupled receptors: Graph-based analyses of static structures and molecular dynamics.

Protein and protein-water hydrogen bonds shape the conformational energy landscape of G Protein-Coupled Receptors, GPCRs. As numerous static structures of GPCRs have been solved, the important question arises whether GPCR structures and GPCR conformational dynamics could be described in terms of conserved hydrogen-bond networks, and alterations of these hydrogen-bond networks along the reaction coordinate of the GPCR. To enable efficient analyses of the hydrogen-bond networks of GPCRs we implemented graph-based algorithms, and applied these algorithms to static GPCR structures from structural biology, and from molecular dynamics simulations of two opioid receptors. We find that static GPCR structures tend to have a conserved, core hydrogen-bond network which, when protein and water dynamics are included with simulations, extends to comprise most of the interior of an inactive receptor. In an active receptor, the dynamic protein-water hydrogen-bond network spans the entire receptor, bridging all functional motifs. Such an extensive, dynamic hydrogen-bond network might contribute to the activation mechanism of the GPCR.

A graph-based approach identifies dynamic H-bond communication networks in spike protein S of SARS-CoV-2.

Corona virus spike protein S is a large homo-trimeric protein anchored in the membrane of the virion particle. Protein S binds to angiotensin-converting-enzyme 2, ACE2, of the host cell, followed by proteolysis of the spike protein, drastic protein conformational change with exposure of the fusion peptide of the virus, and entry of the virion into the host cell. The structural elements that govern conformational plasticity of the spike protein are largely unknown. Here, we present a methodology that relies upon graph and centrality analyses, augmented by bioinformatics, to identify and characterize large H-bond clusters in protein structures. We apply this methodology to protein S ectodomain and find that, in the closed conformation, the three protomers of protein S bring the same contribution to an extensive central network of H-bonds, and contribute symmetrically to a relatively large H-bond cluster at the receptor binding domain, and to a cluster near a protease cleavage site. Markedly different H-bonding at these three clusters in open and pre-fusion conformations suggest dynamic H-bond clusters could facilitate structural plasticity and selection of a protein S protomer for binding to the host receptor, and proteolytic cleavage. From analyses of spike protein sequences we identify patches of histidine and carboxylate groups that could be involved in transient proton binding.

[Applicability of laser-based geological techniques in bone research: analysis of calcium oxide distribution in thin-cut animal bones]. / Lézeralapú geológiai technikák felhasználhatósága a csontkutatásban: kalcium-oxid-eloszlás vizsgálata állati csont vékonycsiszolatain.

The structural similarities between the inorganic component of bone tissue and geological formations make it possible that mathematic models may be used to determine weight percentage composition of different mineral element oxides constituting the inorganic component of bone tissue. The determined weight percentage composition can be verified with the determination of element oxide concentration values by laser induced plasma spectroscopy and inductively coupled plasma optical emission spectrometry. It can be concluded from calculated weight percentage composition of the inorganic component of bone tissue and laboratory analyses that the properties of bone tissue are determined primarily by hydroxylapatite. The inorganic bone structure can be studied well by determining the calcium oxide concentration distribution using the laser induced plasma spectroscopy technique. In the present study, thin polished bone slides prepared from male bovine tibia were examined with laser induced plasma spectroscopy in a regular network and combined sampling system to derive the calculated calcium oxide concentration distribution. The superficial calcium oxide concentration distribution, as supported by "frequency distribution" curves, can be categorized into a number of groups. This, as such, helps in clearly demarcating the cortical and trabecular bone structures. Following analyses of bovine tibial bone, the authors found a positive association between the attenuation value, as determined by quantitative computer tomography and the "ρ" density, as used in geology. Furthermore, the calculated "ρ" density and the measured average calcium oxide concentration values showed inverse correlation.