Protons taken hostage: Dynamic H-bond networks of the pH-sensing GPR68.

Proton-sensing G Protein Coupled Receptors (GPCRs) sense changes in the extracellular pH to effect cell signaling for cellular homeostasis. They tend to be overexpressed in solid tumors associated with acidic extracellular pH, and are of direct interest as drug targets. How proton-sensing GPCRs sense extracellular acidification and activate upon protonation change is important to understand, because it may guide the design of therapeutics. Lack of publicly available experimental structures make it challenging to discriminate between conflicting mechanisms proposed for proton-binding, as main roles have been assigned to either an extracellular histidine cluster or to an internal carboxylic triad. Here we present a protocol to derive and evaluate structural models of the proton-sensing GPR68. This approach integrates state-of-the-art homology modeling with microsecond-timescale atomistic simulations, and with a detailed assessment of the compatibility of the structural models with known structural features of class A GPCRs. To decipher structural elements of potential interest for protonation-coupled conformational changes of GPR68, we used the best-compatible model as a starting point for independent atomistic simulations of GPR68 with different protonation states, and graph computations to characterize the response of GPR68 to changes in protonation. We found that GPR68 hosts an extended hydrogen-bond network that inter-connects the extracellular histidine cluster to the internal carboxylic triad, and which can even reach groups at the cytoplasmic G-protein binding site. Taken together, results suggest that GPR68 relies on dynamic, hydrogen-bond networks to inter-connect extracellular and internal proton-binding sites, and to elicit conformational changes at the cytoplasmic G-protein binding site.

Structural basis of adenylyl cyclase 9 activation.

Adenylyl cyclase 9 (AC9) is a membrane-bound enzyme that converts ATP into cAMP. The enzyme is weakly activated by forskolin, fully activated by the G protein Gαs subunit and is autoinhibited by the AC9 C-terminus. Although our recent structural studies of the AC9-Gαs complex provided the framework for understanding AC9 autoinhibition, the conformational changes that AC9 undergoes in response to activator binding remains poorly understood. Here, we present the cryo-EM structures of AC9 in several distinct states: (i) AC9 bound to a nucleotide inhibitor MANT-GTP, (ii) bound to an artificial activator (DARPin C4) and MANT-GTP, (iii) bound to DARPin C4 and a nucleotide analogue ATPαS, (iv) bound to Gαs and MANT-GTP. The artificial activator DARPin C4 partially activates AC9 by binding at a site that overlaps with the Gαs binding site. Together with the previously observed occluded and forskolin-bound conformations, structural comparisons of AC9 in the four conformations described here show that secondary structure rearrangements in the region surrounding the forskolin binding site are essential for AC9 activation.

Conserved hydrogen-bond motifs of membrane transporters and receptors.

Membrane transporters and receptors often rely on conserved hydrogen bonds to assemble transient paths for ion transfer or long-distance conformational couplings. For transporters and receptors that use proton binding and proton transfer for function, inter-helical hydrogen bonds of titratable protein sidechains that could change protonation are of central interest to formulate hypotheses about reaction mechanisms. Knowledge of hydrogen bonds common at sites of potential interest for proton binding could thus inform and guide studies on functional mechanisms of protonation-coupled membrane proteins. Here we apply graph-theory approaches to identify hydrogen-bond motifs of carboxylate and histidine sidechains in a large data set of static membrane protein structures. We find that carboxylate-hydroxyl hydrogen bonds are present in numerous structures of the dataset, and can be part of more extended H-bond clusters that could be relevant to conformational coupling. Carboxylate-carboxyamide and imidazole-imidazole hydrogen bonds are represented in comparably fewer protein structures of the dataset. Atomistic simulations on two membrane transporters in lipid membranes suggest that many of the hydrogen bond motifs present in static protein structures tend to be robust, and can be part of larger hydrogen-bond clusters that recruit additional hydrogen bonds.

Frontiers in Multiscale Modeling of Photoreceptor Proteins.

This perspective article highlights the challenges in the theoretical description of photoreceptor proteins using multiscale modeling, as discussed at the CECAM workshop in Tel Aviv, Israel. The participants have identified grand challenges and discussed the development of new tools to address them. Recent progress in understanding representative proteins such as green fluorescent protein, photoactive yellow protein, phytochrome, and rhodopsin is presented, along with methodological developments.

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.

Graphs of dynamic H-bond networks: from model proteins to protein complexes in cell signaling.

Proton transfer reactions are ubiquitous in biology, as they are involved in the functioning of numerous proteins. Studies of model proteins have revealed mechanisms by which proteins use hydrogen-bond networks for proton transfers, and couple proton transfers with protein and water dynamics. In this review we focus on graph-based analyses of dynamic hydrogen-bond networks at membrane interfaces, protein H-bond networks for allosteric conformational coupling and pH sensitivity, and challenges in extrapolating from knowledge acquired from studies of model membrane proteins to computational studies of macro-molecular protein complexes that are part of cell signaling networks directly relevant to the development of new therapeutics.

Coating of magnetic nanoparticles affects their interactions with model cell membranes.

BACKGROUND: The use of functionalized iron oxide nanoparticles of various chemical properties and architectures offers a new promising direction in theranostic applications. The increasing applications of nanoparticles in medicine require that these engineered nanomaterials will contact human cells without damaging essential tissues. Thus, efficient delivery must be achieved, while minimizing cytotoxicity during passage through cell membranes to reach intracellular target compartments. METHODS: Differential Scanning Calorimetry (DSC), molecular modeling, and atomistic Molecular Dynamics (MD) simulations were performed for two magnetite nanoparticles coated with polyvinyl alcohol (PVA) and polyarabic acid (ARA) in order to assess their interactions with model DPPC membranes. RESULTS: DSC experiments showed that both nanoparticles interact strongly with DPPC lipid head groups, albeit to a different degree, which was further confirmed and quantified by MD simulations. The two systems were simulated, and dynamical and structural properties were monitored. A bimodal diffusion was observed for both nanoparticles, representing the diffusion in the water phase and in the proximity of the lipid bilayer. Nanoparticles did not enter the bilayer, but caused ordering of the head groups and reduced the area per lipid compared to the pure bilayer, with MAG-PVA interacting more strongly and being closer to the lipid bilayer. CONCLUSIONS: Results of DSC experiments and MD simulations were in excellent agreement. Our findings demonstrate that the external coating is a key factor that affects nanoparticle-membrane interactions. Magnetite nanoparticles coated with PVA and ARA did not destabilize the model membrane and can be considered promising platforms for biomedical applications. GENERAL SIGNIFICANCE: Understanding the physico-chemical interactions of different nanoparticle coatings in contact with model cell membranes is the first step for assessing toxic response and could lead to predictive models for estimating toxicity. DSC in combination with MD simulations is an effective strategy to assess physico-chemical interactions of coated nanoparticles with lipid bilayers.

Mechanism of Inward Proton Transport in an Antarctic Microbial Rhodopsin.

Although the outward-directed proton transport across biological membranes is well studied and its importance for bioenergetics is clearly understood, inward-directed light-driven proton pumping by microbial rhodopsins has remained a mystery both physiologically and mechanistically. A new family of Antarctic rhodopsins, which is a subgroup within a novel class of schizorhodopsins reported recently, includes a member, denoted as AntR, which proved amenable to extensive characterization with experiments and computation. Phylogenetic analyses identify AntR as distinct from the well-studied microbial rhodopsins that function as outward-directed ion pumps, and bioinformatics sequence analyses reveal amino acid substitutions at conserved sites essential for outward proton pumping. Modeling and numerical simulations of AntR, combined with advanced analyses using the graph theory and centrality measures from social sciences, identify the dynamic three-dimensional network of hydrogen-bonded water molecules and amino acid residues that function as communication hubs in AntR. This network undergoes major rearrangement upon retinal isomerization, showing important changes in the connectivity of the active center, retinal Schiff base, to the opposing sides of the membrane, as required for proton transport. Numerical simulations and experimental studies of the photochemical cycle of AntR by spectroscopy and site-directed mutagenesis allowed us to identify pathways that could conduct protons in the direction opposite to that commonly known for outward-directed pumps.

Bridge: A Graph-Based Algorithm to Analyze Dynamic H-Bond Networks in Membrane Proteins.

Membrane proteins that function as transporters or receptors must communicate with both sides of the lipid bilayer in which they sit. This long distance communication enables transporters to move protons or other ions and small molecules across the bilayer and receptors to transmit an external signal to the cell. Hydrogen bonds, hydrogen-bond networks, and lipid-protein interactions are essential for the motions and functioning of the membrane protein and, consequently, of outmost interest to structural biology and numerical simulations. We present here Bridge, an algorithm tailored for efficient analyses of hydrogen-bond networks in membrane transporter and receptor proteins. For channelrhodopsin, a membrane protein whose functioning involves proton-transfer reactions, Bridge identifies extensive networks of protein-water hydrogen bonds and an unanticipated network that can bridge transiently two proton donors across a distance of ∼20 Å. Graphs of the protein hydrogen bonds reveal rapid propagation of structural changes within hydrogen-bond networks of mutant transporters and identify protein groups potentially important for the proton transfer activity. The algorithm is made available as a plugin for PyMol.