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

Dynamics of Hydrogen Bonds between Water and Intrinsically Disordered and Structured Regions of Proteins

Recent studies indicate more restricted dynamics of water around intrinsically disordered proteins (IDPs) than structured proteins. We examine here the dynamics of hydrogen bonds between water molecules and two proteins, small ubiquitin-related modifier-1 (SUMO-1) and ubiquitin-conjugating enzyme E2I (UBC9), which we compare around intrinsically disordered regions (IDRs) and structured regions of these proteins. It has been recognized since some time that excluded volume effects, which influence access of water molecules to hydrogen-bonding sites, and the strength of hydrogen bonds between water and protein affect hydrogen bond lifetimes. While we find those two properties to mediate lifetimes of hydrogen bonds between water and protein residues in this study, we also find that the lifetimes are affected by the concentration of charged groups on other nearby residues. These factors are more important in determining the hydrogen bond lifetimes than whether a residue hydrogen bonding with water belongs to an IDR or to a structured region.

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.

Graph-Based Analyses of Dynamic Water-Mediated Hydrogen-Bond Networks in Phosphatidylserine: Cholesterol Membranes

Phosphatidylserine lipids are anionic molecules present in eukaryotic plasma membranes, where they have essential physiological roles. The altered distribution of phosphatidylserine in cells such as apoptotic cancer cells, which, unlike healthy cells, expose phosphatidylserine, is of direct interest for the development of biomarkers. We present here applications of a recently implemented Depth-First-Search graph algorithm to dissect the dynamics of transient water-mediated lipid clusters at the interface of a model bilayer composed of 1-palmytoyl-2-oleoyl-sn-glycero-2-phosphatidylserine (POPS) and cholesterol. Relative to a reference POPS bilayer without cholesterol, in the POPS:cholesterol bilayer there is a somewhat less frequent sampling of relatively complex and extended water-mediated hydrogen-bond networks of POPS headgroups. The analysis protocol used here is more generally applicable to other lipid:cholesterol bilayers.

The Solvation of the E. coli CheY Phosphorylation Site Mapped by XFMS

The Escherichia coli CheY protein belongs to a large bacterial response regulator superfamily. X-ray hydroxy radical foot-printing with mass spectroscopy (XFMS) has shown that allosteric activation of CheY by its motor target triggers a concerted internalization of aromatic sidechains. We reanalyzed the XFMS data to compare polar versus non-polar CheY residue positions. The polar residues around and including the 57D phosphorylated site had an elevated hydroxy radical reactivity. Bioinformatic measures revealed that a water-mediated hydrogen bond network connected this ring of residues with the central 57D. These residues solvated 57D to energetically stabilize the apo-CheY fold. The abundance of these reactive residues was reduced upon activation. This result was supported by the bioinformatics and consistent with the previously reported activation-induced increase in core hydrophobicity. It further illustrated XFMS detection of structural waters. Direct contacts between the ring residues and the phosphorylation site would stabilize the aspartyl phosphate. In addition, we report that the ring residue, 18R, is a constant central node in the 57D solvation network and that 18R non-polar substitutions determine CheY diversity as assessed by its evolutionary trace in bacteria with well-studied chemotaxis. These results showcase the importance of structured water dynamics for phosphorylation-mediated signal transduction.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Graphs of Hydrogen-Bond Networks to Dissect Protein Conformational Dynamics

Dynamic hydrogen bonds and hydrogen-bond networks are ubiquitous in proteins and protein complexes. Functional roles that have been assigned to hydrogen-bond networks include structural plasticity for protein function, allosteric conformational coupling, long-distance proton transfers, and transient storage of protons. Advances in structural biology provide invaluable insights into architectures of large proteins and protein complexes of direct interest to human physiology and disease, including G Protein Coupled Receptors (GPCRs) and the SARS-Covid-19 spike protein S, and give rise to the challenge of how to identify those interactions that are more likely to govern protein dynamics. This Perspective discusses applications of graph-based algorithms to dissect dynamical hydrogen-bond networks of protein complexes, with illustrations for GPCRs and spike protein S. H-bond graphs provide an overview of sites in GPCR structures where hydrogen-bond dynamics would be required to assemble longer-distance networks between functionally important motifs. In the case of spike protein S, graphs identify regions of the protein where hydrogen bonds rearrange during the reaction cycle and where local hydrogen-bond networks likely change in a virus variant of concern.

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.

Algorithm to catalogue topologies of dynamic lipid hydrogen-bond networks

Lipid membrane interfaces host reactions essential for the functioning of cells. The hydrogen-bonding environment at the membrane interface is particularly important for binding of proteins, drug molecules, and ions. We present here the implementation and applications of a depth-first search algorithm that analyzes dynamic lipid interaction networks. Lipid hydrogen-bond networks sampled transiently during simulations of lipid bilayers are clustered according to main types of topologies that characterize three-dimensional arrangements of lipids connected to each other via short water bridges. We characterize the dynamics of hydrogen-bonded lipid clusters in simulations of model POPE and POPE:POPG membranes that are often used for bacterial membrane proteins, in a model of the Escherichia coli membrane with six different lipid types, and in POPS membranes. We find that all lipids sample dynamic hydrogen-bonded networks with linear, star, or circular arrangements of the lipid headgroups, and larger networks with combinations of these three types of topologies. Overall, linear lipid-water bridges tend to be short. Water-mediated lipid clusters in all membranes with PE lipids tend to be somewhat small, with about four lipids in all membranes studied here. POPS membranes allow circular arrangements of three POPS lipids to be sampled frequently, and complex arrangements of linear, star, and circular paths may also be sampled. These findings suggest a molecular picture of the membrane interface whereby lipid molecules transiently connect in clusters with somewhat small spatial extension.

Development of a recombinant nucleocapsid protein-based ELISA for the detection of IgM and IgG antibodies to SARS-CoV-2

Coronavirus 2019 (COVID-19) is a global concern for public health. Thus, early and accurate diagnosis is a critical step in management of this infectious disease. Currently, RT-PCR is routine diagnosis test for COVID-19, but it has some limitations and false negative results. enzyme-linked immunosorbent assay (ELISA) against SARS-CoV-2 antigens seems to be an appropriate approach for serodiagnosis of COVID-19. In the current study, an ELISA system, using a recombinant nucleocapsid (N) protein, was developed for the detection of IgM and IgG antibodies to SARS-CoV-2. The related protein was expressed, purified, and used in an ELISA system. Sera samples (67) for COVID-19 patients, as well as sera samples from healthy volunteers (112), along with sera samples from non-COVID-19 patients were examined by the ELISA system. The expression and purity of the recombinant N protein were approved by SDS-PAGE and Western blotting. The sensitivity of ELISA system was 91.04 and 92.53% for the detection of IgG and IgM antibodies, respectively. Moreover, the specificity of the developed ELISA system for IgG and IgM were 98.21 and 97.32%, respectively. Our developed ELISA system showed satisfactory sensitivity and specificity for the detection of antiSARS-CoV-2 IgM and IgG antibodies and could be used as a complementary approach for proper diagnosis of COVID-19.

Structural insights in cell-type specific evolution of intra-host diversity by SARS-CoV-2

As the global burden of SARS-CoV-2 infections escalates, so does the evolution of viral variants with increased transmissibility and pathology. In addition to this entrenched diversity, RNA viruses can also display genetic diversity within single infected hosts with co-existing viral variants evolving differently in distinct cell types. The BriSΔ variant, originally identified as a viral subpopulation from SARS-CoV-2 isolate hCoV-19/England/02/2020, comprises in the spike an eight amino-acid deletion encompassing a furin recognition motif and S1/S2 cleavage site. We elucidate the structure, function and molecular dynamics of this spike providing mechanistic insight into how the deletion correlates to viral cell tropism, ACE2 receptor binding and infectivity of this SARS-CoV-2 variant. Our results reveal long-range allosteric communication between functional domains that differ in the wild-type and the deletion variant and support a view of SARS-CoV-2 probing multiple evolutionary trajectories in distinct cell types within the same infected host.

Significance of the RBD mutations in the SARS-CoV-2 Omicron: from spike opening to antibody escape and cell attachment

We computationally investigated the role of the Omicron RBD mutations on its structure and interactions with surrounding domains in the spike trimer as well as with ACE2. Our results suggest...

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.

Factors underlying asymmetric pore dynamics of disaggregase and microtubule-severing AAA+ machines

Disaggregation and microtubule-severing nanomachines from the AAA+ (ATPases associated with various cellular activities) superfamily assemble into ring-shaped hexamers that enable protein remodeling by coupling large-scale conformational changes with application of mechanical forces within a central pore by loops protruding within the pore. We probed the asymmetric pore motions and intraring interactions that support them by performing extensive molecular dynamics simulations of single-ring severing proteins and the double-ring disaggregase ClpB. Simulations reveal that dynamic stability of hexameric pores of severing proteins and of the nucleotide-binding domain 1 (NBD1) ring of ClpB, which belong to the same clade, involves a network of salt bridges that connect conserved motifs of central pore loops. Clustering analysis of ClpB highlights correlated motions of domains of neighboring protomers supporting strong interprotomer collaboration. Severing proteins have weaker interprotomer coupling and stronger intraprotomer stabilization through salt bridges involving pore loops. Distinct mechanisms are identified in the NBD2 ring of ClpB involving weaker interprotomer coupling through salt bridges formed by noncanonical loops and stronger intraprotomer coupling. Analysis of collective motions of PL1 loops indicates that the largest amplitude motions in the spiral complex of spastin and ClpB involve axial excursions of the loops, whereas for katanin they involve opening and closing of the central pore. All three motors execute primarily axial excursions in the ring complex. These results suggest distinct substrate processing mechanisms of remodeling and translocation by ClpB and spastin compared to katanin, thus providing dynamic support for the differential action of the two severing proteins. Relaxation dynamics of the distance between the PL1 loops and the center of mass of protomers reveals observation-time-dependent dynamics, leading to predicted relaxation times of tens to hundreds of microseconds on millisecond experimental timescales. For ClpB, the predicted relaxation time is in excellent agreement with the extracted time from smFRET experiments.

Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants

The SARS-CoV-2 Spike protein needs to be in an open-state conformation to interact with ACE2 to initiate viral entry. We utilise coarse-grained normal mode analysis to model the dynamics of Spike and calculate transition probabilities between states for 17081 variants including experimentally observed variants. Our results correctly model an increase in open-state occupancy for the more infectious D614G via an increase in flexibility of the closed-state and decrease of flexibility of the open-state. We predict the same effect for several mutations on glycine residues (404, 416, 504, 252) as well as residues K417, D467 and N501, including the N501Y mutation recently observed within the B.1.1.7, 501.V2 and P1 strains. This is, to our knowledge, the first use of normal mode analysis to model conformational state transitions and the effect of mutations on such transitions. The specific mutations of Spike identified here may guide future studies to increase our understanding of SARS-CoV-2 infection mechanisms and guide public health in their surveillance efforts.

The present work explores the molecular mechanisms underlying and potentially helping new strains of SARS-CoV-2 to gain an evolutionary advantage during the ongoing COVID-19 pandemics. We show how a computational method called normal mode analysis that treats protein dynamics in a simplified manner is capable to predict the higher propensity of the Spike protein to be in the open state in which it is capable to interact with the human ACE2 receptor and thus facilitate cell entry. Because the simulation of the simplified computational model is relatively less demanding on resources than alternative methods, we were able to simulate over 17000 mutations in the SARS-CoV-2 Spike protein to identify multiple mutations that if they were to appear as the virus continues to evolve, could confer an evolutionary advantage. As a matter of fact, our predictions foresaw the emergence of particular mutations such as N501Y that appeared in several variants of concern. Our results can inform public health regarding new variants and serves as a proof of concept for the application of normal mode analysis to study the effect of mutations on both, protein dynamics and conformational transitions in a high-throughput manner.

Activation-Induced Reorganization of Energy Transport Networks in the β2 Adrenergic Receptor

We compute energy exchange networks (EENs) through the β₂ adrenergic receptor (β₂AR), a G-protein coupled receptor (GPCR), in inactive and active states, based on the results of molecular dynamics simulations of this membrane bound protein. We introduce a new definition for the reorganization of EENs upon activation that depends on the relative change in rates of energy transfer across noncovalent contacts throughout the protein. On the basis of the reorganized network that we obtain for β₂AR upon activation, we identify a branched pathway between the agonist binding site and the cytoplasmic region, where a G-protein binds to the receptor when activated. The pathway includes all of the motifs containing molecular switches previously identified as contributing to the allosteric transition of β₂AR upon agonist binding. EENs and their reorganization upon activation are compared with structure-based contact networks computed for the inactive and active states of β₂AR.

Proton-Binding Motifs of Membrane-Bound Proteins: From Bacteriorhodopsin to Spike Protein S

Membrane-bound proteins that change protonation during function use specific protein groups to bind and transfer protons. Knowledge of the identity of the proton-binding groups is of paramount importance to decipher the reaction mechanism of the protein, and protonation states of prominent are studied extensively using experimental and computational approaches. Analyses of model transporters and receptors from different organisms, and with widely different biological functions, indicate common structure-sequence motifs at internal proton-binding sites. Proton-binding dynamic hydrogen-bond networks that are exposed to the bulk might provide alternative proton-binding sites and proton-binding pathways. In this perspective article I discuss protonation coupling and proton binding at internal and external carboxylate sites of proteins that use proton transfer for function. An inter-helical carboxylate-hydroxyl hydrogen-bond motif is present at functionally important sites of membrane proteins from archaea to the brain. External carboxylate-containing H-bond clusters are observed at putative proton-binding sites of protonation-coupled model proteins, raising the question of similar functionality in spike protein S.

Interactive Interface for Graph-Based Analyses of Dynamic H-Bond Networks: Application to Spike Protein S

Dynamic hydrogen-bond networks are key determinants of protein conformational dynamics. In the case of macromolecular protein complexes, which can have a large number of hydrogen bonds giving rise to extensive hydrogen-bond networks, efficient algorithms are required to analyze interactions that could be important for the dynamics and biological function of the complex. We present here a highly efficient, standalone interface designed for analyses of dynamical hydrogen-bond networks of biomolecules and macromolecular complexes. To facilitate a comprehensive description of protein dynamics, the interface includes analyses of hydrophobic interactions. We illustrate the usefulness and workflow of the interface by dissecting the dynamics of the ectodomain of SARS-CoV-2 protein S in its closed conformation. We find that protein S contains numerous local clusters of dynamic hydrogen bonds and identify hydrogen bonds that are sampled persistently. The receptor binding domain of the spike protein hosts only a handful of persistent hydrogen-bond clusters, suggesting structural plasticity. Our data analysis interface is released here for open use.

Phosphatidylglyerol Lipid Binding at the Active Site of an Intramembrane Protease

Transmembrane substrate cleavage by the small Escherichia coli rhomboid protease GlpG informs on mechanisms by which lipid interactions shape reaction coordinates of membrane-embedded enzymes. Here, I review and discuss new work on the molecular picture of protein-lipid interactions that might govern the formation of the substrate-enzyme complex in fluid lipid membranes. Negatively charged PG-type lipids are of particular interest, because they are a major component of bacterial membranes. Atomistic computer simulations indicate POPG and DOPG lipids bridge remote parts of GlpG and might pre-occupy the substrate-docking site. Inhibition of catalytic activity by PG lipids could arise from ligand-like lipid binding at the active site, which could delay or prevent substrate docking. Dynamic protein-lipid H-bond networks, water access to the active site, and fluctuations in the orientation of GlpG suggest that GlpG has lipid-coupled dynamics that could shape the energy landscape of transmembrane substrate docking.

Tuning Proton Transfer Thermodynamics in SARS-Cov-2 Main Protease: Implications for Catalysis and Inhibitor Design

In this comutational work a hybrid quantum mechanics/molecular mechanics approach, the MD-PMM approach, is used to investigate the proton transfer reaction the activates the catalytic activity of SARS-CoV-2 main protease. The proton transfer thermodynamics is investigated for the apo ensyme (i.e., without any bound substrate or inhibitor) and in the presence of a inhibitor, N3, which was previously shown to covalently bind SARS-CoV-2 main protease.