Key interaction networks: Identifying evolutionarily conserved non-covalent interaction networks across protein families.

Protein structure (and thus function) is dictated by non-covalent interaction networks. These can be highly evolutionarily conserved across protein families, the members of which can diverge in sequence and evolutionary history. Here we present KIN, a tool to identify and analyze conserved non-covalent interaction networks across evolutionarily related groups of proteins. KIN is available for download under a GNU General Public License, version 2, from https://www.github.com/kamerlinlab/KIN. KIN can operate on experimentally determined structures, predicted structures, or molecular dynamics trajectories, providing insight into both conserved and missing interactions across evolutionarily related proteins. This provides useful insight both into protein evolution, as well as a tool that can be exploited for protein engineering efforts. As a showcase system, we demonstrate applications of this tool to understanding the evolutionary-relevant conserved interaction networks across the class A ß-lactamases.

The ACE2 receptor accelerates but is not biochemically required for SARS-CoV-2 membrane fusion.

The SARS-CoV-2 coronavirus infects human cells via the ACE2 receptor. Structural evidence suggests that ACE2 may not just serve as an attachment factor but also conformationally activate the SARS-CoV-2 spike protein for membrane fusion. Here, we test that hypothesis directly, using DNA-lipid tethering as a synthetic attachment factor in place of ACE2. We find that SARS-CoV-2 pseudovirus and virus-like particles are capable of membrane fusion without ACE2 if activated with an appropriate protease. Thus, ACE2 is not biochemically required for SARS-CoV-2 membrane fusion. However, addition of soluble ACE2 speeds up the fusion reaction. On a per-spike level, ACE2 appears to promote activation for fusion and then subsequent inactivation if an appropriate protease is not present. Kinetic analysis suggests at least two rate-limiting steps for SARS-CoV-2 membrane fusion, one of which is ACE2 dependent and one of which is not. Since ACE2 serves as a high-affinity attachment factor on human cells, the possibility to replace it with other factors implies a flatter fitness landscape for host adaptation by SARS-CoV-2 and future related coronaviruses.

Single-Virus Fusion Measurements Reveal Multiple Mechanistically Equivalent Pathways for SARS-CoV-2 Entry.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to cell surface receptors and is activated for membrane fusion and cell entry via proteolytic cleavage. Phenomenological data have shown that SARS-CoV-2 can be activated for entry at either the cell surface or in endosomes, but the relative roles in different cell types and mechanisms of entry have been debated. Here, we used single-virus fusion experiments and exogenously controlled proteases to probe activation directly. We found that plasma membrane and an appropriate protease are sufficient to support SARS-CoV-2 pseudovirus fusion. Furthermore, fusion kinetics of SARS-CoV-2 pseudoviruses are indistinguishable no matter which of a broad range of proteases is used to activate the virus. This suggests that the fusion mechanism is insensitive to protease identity or even whether activation occurs before or after receptor binding. These data support a model for opportunistic fusion by SARS-CoV-2 in which the subcellular location of entry likely depends on the differential activity of airway, cellsurface, and endosomal proteases, but all support infection. Inhibition of any single host protease may thus reduce infection in some cells but may be less clinically robust. IMPORTANCE SARS-CoV-2 can use multiple pathways to infect cells, as demonstrated recently when new viral variants switched dominant infection pathways. Here, we used single-virus fusion experiments together with biochemical reconstitution to show that these multiple pathways coexist simultaneously and specifically that the virus can be activated by different proteases in different cellular compartments with mechanistically identical effects. The consequences of this are that the virus is evolutionarily plastic and that therapies targeting viral entry should address multiple pathways at once to achieve optimal clinical effects.

KIF-Key Interactions Finder: A program to identify the key molecular interactions that regulate protein conformational changes.

Simulation datasets of proteins (e.g., those generated by molecular dynamics simulations) are filled with information about how a non-covalent interaction network within a protein regulates the conformation and, thus, function of the said protein. Most proteins contain thousands of non-covalent interactions, with most of these being largely irrelevant to any single conformational change. The ability to automatically process any protein simulation dataset to identify non-covalent interactions that are strongly associated with a single, defined conformational change would be a highly valuable tool for the community. Furthermore, the insights generated from this tool could be applied to basic research, in order to improve understanding of a mechanism of action, or for protein engineering, to identify candidate mutations to improve/alter the functionality of any given protein. The open-source Python package Key Interactions Finder (KIF) enables users to identify those non-covalent interactions that are strongly associated with any conformational change of interest for any protein simulated. KIF gives the user full control to define the conformational change of interest as either a continuous variable or categorical variable, and methods from statistics or machine learning can be applied to identify and rank the interactions and residues distributed throughout the protein, which are relevant to the conformational change. Finally, KIF has been applied to three diverse model systems (protein tyrosine phosphatase 1B, the PDZ3 domain, and the KE07 series of Kemp eliminases) in order to illustrate its power to identify key features that regulate functionally important conformational dynamics.

Structural prediction of chimeric immunogens to elicit targeted antibodies against betacoronaviruses.

Betacoronaviruses pose an ongoing pandemic threat. Antigenic evolution of the SARS-CoV-2 virus has shown that much of the spontaneous antibody response is narrowly focused rather than broadly neutralizing against even SARS-CoV-2 variants, let alone future threats. One way to overcome this is by focusing the antibody response against better-conserved regions of the viral spike protein. Here, we present a design approach to predict stable chimeras between SARS-CoV-2 and other coronaviruses, creating synthetic spike proteins that display a desired conserved region and vary other regions. We leverage AlphaFold to predict chimeric structures and create a new metric for scoring chimera stability based on AlphaFold outputs. We evaluated 114 candidate spike chimeras using this approach. Top chimeras were further evaluated using molecular dynamics simulation as an intermediate validation technique, showing good stability compared to low-scoring controls. This demonstrates the feasibility of the underlying approach, which can be used to design custom immunogens to focus the immune response against a desired viral glycoprotein epitope.

Mechanistic dissection of antibody inhibition of influenza entry yields unexpected heterogeneity.

Neutralizing antibodies against influenza have generally been classified according to their recognition sites, with antibodies against the head domain of hemagglutinin thought to inhibit attachment and antibodies against the stalk region thought to inhibit fusion. Here, we report the development of a microfluidic assay to measure neutralization of viral entry that can clearly differentiate between effects on attachment and fusion. Testing multiple broadly neutralizing antibodies against the hemagglutinin stalk domain, we obtain a surprising result: some broadly neutralizing antibodies inhibit fusion only, while others inhibit both fusion and viral attachment. Antibodies binding the globular head domain primarily inhibit attachment but can also reduce the fusogenic capability of viral particles that nonetheless bind the receptor. These findings shed light on the unexpectedly heterogeneous mechanisms of antibody neutralization even within similar recognition sites. The assay we have developed also provides a tool to optimize vaccine design by permitting assessment of the elicited antibody response with greater mechanistic resolution.

Influenza Virus Membrane Fusion Is Promoted by the Endosome-Resident Phospholipid Bis(monoacylglycero)phosphate.

The phospholipid bis(monoacylglycero)phosphate (BMP) is enriched in late endosomal and endolysosomal membranes and is believed to be involved in membrane deformation and generation of intralumenal vesicles within late endosomes. Previous studies have demonstrated that BMP promotes membrane fusion of several enveloped viruses, but a limited effect has been found on influenza virus. Here, we report the use of single-virus fusion assays to dissect BMP's effect on influenza virus fusion in greater depth. In agreement with prior reports, we found that hemifusion kinetics and efficiency were unaffected by the addition of 10-20 mol % BMP to the target membrane. However, using an assay for fusion pore formation and genome exposure, we found full fusion efficiency to be substantially enhanced by the addition of 10-20 mol % BMP to the target membrane, while the kinetics remained unaffected. By comparing BMP to other negatively charged phospholipids, we found the effect on fusion efficiency mainly attributable to headgroup charge, although we also hypothesize a role for BMP's unusual chemical structure. Our results suggest that BMP function as a permissive factor for a wider range of viruses than previously reported. We hypothesize that BMP may be a general cofactor for endosomal entry of enveloped viruses.

Measuring single-virus fusion kinetics using an assay for nucleic acid exposure.

The kinetics by which individual enveloped viruses fuse with membranes provide an important window into viral-entry mechanisms. We have developed a real-time assay using fluorescent probes for single-virus genome exposure than can report on stages of viral entry including or subsequent to fusion pore formation and prior to viral genome trafficking. We accomplish this using oxazole yellow nucleic-acid-binding dyes, which can be encapsulated in the lumen of target membranes to permit specific detection of fusion events. Since increased fluorescence of the dye occurs only when it encounters viral genome via a fusion pore and binds, this assay excludes content leakage without fusion. Using this assay, we show that influenza virus fuses with liposomes of different sizes with indistinguishable kinetics by both testing liposomes extruded through pores of different radii and showing that the fusion kinetics of individual liposomes are uncorrelated with the size of the liposome. These results suggest that the starting curvature of such liposomes does not control the rate-limiting steps in influenza entry.

gmxapi: A GROMACS-native Python interface for molecular dynamics with ensemble and plugin support.

Gmxapi provides an integrated, native Python API for both standard and advanced molecular dynamics simulations in GROMACS. The Python interface permits multiple levels of integration with the core GROMACS libraries, and legacy support is provided via an interface that mimics the command-line syntax, so that all GROMACS commands are fully available. Gmxapi has been officially supported since the GROMACS 2019 release and is enabled by default in current versions of the software. Here we describe gmxapi 0.3 and later. Beyond simply wrapping GROMACS library operations, the API permits several advanced operations that are not feasible using the prior command-line interface. First, the API allows custom user plugin code within the molecular dynamics force calculations, so users can execute custom algorithms without modifying the GROMACS source. Second, the Python interface allows tasks to be dynamically defined, so high-level algorithms for molecular dynamics simulation and analysis can be coordinated with loop and conditional operations. Gmxapi makes GROMACS more accessible to custom Python scripting while also providing support for high-level data-flow simulation algorithms that were previously feasible only in external packages.

Modeling biomolecular kinetics with large-scale simulation.

The molecular details of biomolecular kinetics present a challenging estimation problem because the identities of relevant intermediates and the rates of exchange between them must be determined. These can be derived from prior knowledge, but in recent years, great advances have been made in the development and application of methods to systematically determine states and rates using biomolecular simulation. Doing this for biological systems of reasonable complexity requires substantial computational power, and contemporary methods leverage distributed computing or leadership-class computing resources to accomplish this. The result has been substantial insight into pressing contemporary problems, including structural activation of pandemic viruses. Here, we highlight recent developments in both methodology and exciting applications.

Development of COVID-19 vaccine using a dual Toll-like receptor ligand liposome adjuvant.

We developed a SARS-CoV-2 spike subunit vaccine formulation containing dual TLR ligand liposome adjuvant. The vaccine-induced robust systemic neutralizing antibodies and completely protected mice from a lethal challenge. Two immunizations protected against lung injury and cleared the virus from lungs upon challenge. The adjuvanted vaccine also elicited systemic and local anti-Spike IgA which can be an important feature for a COVID-19 vaccine.

Computational methods to study enveloped viral entry.

The protein-membrane interactions that mediate viral infection occur via loosely ordered, transient assemblies, creating challenges for high-resolution structure determination. Computational methods and in particular molecular dynamics simulation have thus become important adjuncts for integrating experimental data, developing mechanistic models, and suggesting testable hypotheses regarding viral function. However, the large molecular scales of virus-host interaction also create challenges for detailed molecular simulation. For this reason, continuum membrane models have played a large historical role, although they have become less favored for high-resolution models of protein assemblies and lipid organization. Here, we review recent progress in the field, with an emphasis on the insight that has been gained using a mixture of coarse-grained and atomic-resolution molecular dynamics simulations. Based on successes and challenges to date, we suggest a multiresolution strategy that should yield the best mixture of computational efficiency and physical fidelity. This strategy may facilitate further simulations of viral entry by a broader range of viruses, helping illuminate the diversity of viral entry strategies and the essential common elements that can be targeted for antiviral therapies.

The N-terminal Helix-Turn-Helix Motif of Transcription Factors MarA and Rob Drives DNA Recognition.

DNA-binding proteins play an important role in gene regulation and cellular function. The transcription factors MarA and Rob are two homologous members of the AraC/XylS family that regulate multidrug resistance. They share a common DNA-binding domain, and Rob possesses an additional C-terminal domain that permits binding of low-molecular weight effectors. Both proteins possess two helix-turn-helix (HTH) motifs capable of binding DNA; however, while MarA interacts with its promoter through both HTH-motifs, prior studies indicate that Rob binding to DNA via a single HTH-motif is sufficient for tight binding. In the present work, we perform microsecond time scale all-atom simulations of the binding of both transcription factors to different DNA sequences to understand the determinants of DNA recognition and binding. Our simulations characterize sequence-dependent changes in dynamical behavior upon DNA binding, showcasing the role of Arg40 of the N-terminal HTH-motif in allowing for specific tight binding. Finally, our simulations demonstrate that an acidic C-terminal loop of Rob can control the DNA binding mode, facilitating interconversion between the distinct DNA binding modes observed in MarA and Rob. In doing so, we provide detailed molecular insight into DNA binding and recognition by these proteins, which in turn is an important step toward the efficient design of antivirulence agents that target these proteins.

Inference of Joint Conformational Distributions from Separately Acquired Experimental Measurements.

Flexible proteins serve vital roles in a multitude of biological processes. However, determining their full conformational ensembles is extremely difficult because this requires detailed knowledge about the heterogeneity of the protein's degrees of freedom. Label-based experiments such as double electron-electron resonance (DEER) are very useful in studying flexible proteins, as they provide distributional data on heterogeneity. These experiments are typically performed separately, so information about correlation between distributions is lost. We have developed a method to recover correlation information using nonequilibrium work estimates in molecular dynamics refinement. We tested this method on a simple model of an alternating-access transporter for which the true joint distributions are known, and it successfully recovered the true joint distribution. We also applied our method to the protein syntaxin-1a, where it discarded physically implausible conformations. Our method thus provides a way to recover correlation structure in separate experimental measurements of conformational ensembles and refines the resulting structural ensemble.

Precise Triggering and Chemical Control of Single-Virus Fusion within Endosomes.

Many enveloped viruses infect cells within endocytic compartments. The pH drop that accompanies endosomal maturation, often in conjunction with proteolysis, triggers viral proteins to insert into the endosomal membrane and drive fusion. Fusion dynamics have been studied by tracking viruses within living cells, which limits the precision with which fusion can be synchronized and controlled, and reconstituting viral fusion to synthetic membranes, which introduces nonphysiological membrane curvature and composition. To overcome these limitations, we report chemically controllable triggering of single-virus fusion within endosomes. We isolated influenza (A/Aichi/68; H3N2) virus:endosome conjugates from cells, immobilized them in a microfluidic flow cell, and rapidly and controllably triggered fusion. Observed lipid-mixing kinetics were surprisingly similar to those of influenza virus fusion with model membranes of opposite curvature: 80% of single-virus events had indistinguishable kinetics. This result suggests that endosomal membrane curvature is not a key permissive feature for viral entry, at least lipid mixing. The assay preserved endosomal membrane asymmetry and protein composition, providing a platform to test how cellular restriction factors and altered endosomal trafficking affect viral membrane fusion.IMPORTANCE Many enveloped viruses infect cells via fusion to endosomes, but controlling this process within living cells has been challenging. We studied the fusion of influenza virus virions to endosomes in a chemically controllable manner. Extracting virus:endosome conjugates from cells and exogenously triggering fusion permits precise study of virus:endosome fusion kinetics. Surprisingly, endosomal curvature does not grossly alter fusion kinetics, although membrane deformability does. This supports a model for influenza virus entry where cells restrict or permit membrane fusion by changing deformability, for instance, using interferon-induced proteins.

SARS-CoV-2 receptor networks in diabetic and COVID-19-associated kidney disease.

COVID-19 morbidity and mortality are increased via unknown mechanisms in patients with diabetes and kidney disease. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Because ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of kidney biopsies from healthy living donors and patients with diabetic kidney disease revealed ACE2 expression primarily in proximal tubular epithelial cells. This cell-specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin-angiotensin-aldosterone system inhibitors in diabetic kidney disease. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing proximal tubular epithelial cells in diabetic kidney disease (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The diabetic kidney disease ACE2-positive proximal tubular epithelial cell module overlapped with expression patterns seen in SARS-CoV-2-infected cells. Similar cellular programs were seen in ACE2-positive proximal tubular epithelial cells obtained from urine samples of 13 hospitalized patients with COVID-19, suggesting a consistent ACE2-coregulated proximal tubular epithelial cell expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19-related kidney damage.

Bilayer-Coated Nanoparticles Reveal How Influenza Viral Entry Depends on Membrane Deformability but Not Curvature.

Enveloped viruses infect cells via fusion between the viral envelope and a cellular membrane. This membrane fusion process is driven by viral proteins, but slow stochastic protein activation dominates the fusion kinetics, making it challenging to probe the role of membrane mechanics in viral entry directly. Furthermore, many changes to the interacting membranes alter the curvature, deformability, and spatial organization of membranes simultaneously. We have used bilayer-coated silica nanoparticles to restrict the deformability of lipid membranes in a controllable manner. The single-event kinetics for fusion of influenza virus to coated nanoparticles permits independent testing of how the membrane curvature and deformability control the free energy barriers to fusion. Varying the free energy of membrane deformation, but not membrane curvature, causes a corresponding response in the fusion kinetics and fusion protein stoichiometry. Thus, the main free energy barrier to lipid mixing by influenza virus is controlled by membrane deformability and not the initial membrane curvature.

Managing Coronavirus Disease 2019 Spread With Voluntary Public Health Measures: Sweden as a Case Study for Pandemic Control.

BACKGROUND: The coronavirus disease 19 (COVID-19) pandemic has spread globally, causing extensive illness and mortality. In advance of effective antiviral therapies, countries have applied different public health strategies to control spread and manage healthcare need. Sweden has taken a unique approach of not implementing strict closures, instead urging personal responsibility. We analyze the results of this and other potential strategies for pandemic control in Sweden. METHODS: We implemented individual-based modeling of COVID-19 spread in Sweden using population, employment, and household data. Epidemiological parameters for COVID-19 were validated on a limited date range; where substantial uncertainties remained, multiple parameters were tested. The effects of different public health strategies were tested over a 160-day period, analyzed for their effects on intensive care unit (ICU) demand and death rate, and compared with Swedish data for April 2020. RESULTS: Swedish mortality rates are intermediate between rates for European countries that quickly imposed stringent public health controls and those for countries that acted later. Models most closely reproducing reported mortality data suggest that large portions of the population voluntarily self-isolate. Swedish ICU use rates remained lower than predicted, but a large fraction of deaths occurred in non-ICU patients. This suggests that patient prognosis was considered in ICU admission, reducing healthcare load at a cost of decreased survival in patients not admitted. CONCLUSIONS: The Swedish COVID-19 strategy has thus far yielded a striking result: mild mandates overlaid with voluntary measures can achieve results highly similar to late-onset stringent mandates. However, this policy causes more healthcare demand and more deaths than early stringent control and depends on continued public will.

SARS-CoV-2 receptor networks in diabetic and COVID-19 associated kidney disease.

COVID-19 morbidity and mortality is increased in patients with diabetes and kidney disease via unknown mechanisms. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Since ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease (DKD) and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of healthy living donor (LD) and DKD kidney biopsies revealed ACE2 expression primarily in proximal tubular epithelial cells (PTEC). This cell specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin angiotensin aldosterone system inhibitors in DKD. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing PTEC in DKD (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The DKD ACE2-positive PTEC module overlapped with expression patterns seen in SARS-CoV-2 infected cells. Similar cellular programs were seen in ACE2-positive PTEC obtained from urine samples of 13 COVID-19 patients who were hospitalized, suggesting a consistent ACE2-coregulated PTEC expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19 related kidney damage.

Acquired Functional Capsid Structures in Metazoan Totivirus-like dsRNA Virus.

Non-enveloped icosahedral double-stranded RNA (dsRNA) viruses possess multifunctional capsids required for their proliferation. Whereas protozoan/fungal dsRNA viruses have a relatively simple capsid structure, which suffices for the intracellular phase in their life cycle, metazoan dsRNA viruses have acquired additional structural features as an adaptation for extracellular cell-to-cell transmission in multicellular hosts. Here, we present the first atomic model of a metazoan dsRNA totivirus-like virus and the structure reveals three unique structural traits: a C-terminal interlocking arm, surface projecting loops, and an obstruction at the pore on the 5-fold symmetry axis. These traits are keys to understanding the capsid functions of metazoan dsRNA viruses, such as particle stability and formation, cell entry, and endogenous intraparticle transcription of mRNA. On the basis of molecular dynamics simulations of the obstructed pore, we propose a possible mechanism of intraparticle transcription in totivirus-like viruses, which dynamically switches between open and closed states of the pore(s).