Structure of the SARS-CoV-2 Frameshift Stimulatory Element with an Upstream Multibranch Loop.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) frameshift stimulatory element (FSE) is necessary for programmed -1 ribosomal frameshifting (-1 PRF) and optimized viral efficacy. The FSE has an abundance of context-dependent alternate conformations, but two of the structures most crucial to -1 PRF are an attenuator hairpin and a three-stem H-type pseudoknot structure. A crystal structure of the pseudoknot alone features three RNA stems in a helically stacked linear structure, whereas a 6.9 Å cryo-EM structure including the upstream heptameric slippery site resulted in a bend between two stems. Our previous research alluded to an extended upstream multibranch loop that includes both the attenuator hairpin and the slippery site-a conformation not previously modeled. We aim to provide further context to the SARS-CoV-2 FSE via computational and medium resolution cryo-EM approaches, by presenting a 6.1 Å cryo-EM structure featuring a linear pseudoknot structure and a dynamic upstream multibranch loop.

Isolation, Virtual Screening, and Evaluation of Hazelnut-Derived Immunoactive Peptides for the Inhibition of SARS-CoV-2 Main Protease.

The aim of this study is to validate the activity of hazelnut (Corylus avellana L.)-derived immunoactive peptides inhibiting the main protease (Mpro) of SARS-CoV-2 and further unveil their interaction mechanism using in vitro assays, molecular dynamics (MD) simulations, and binding free energy calculations. In general, the enzymatic hydrolysis components, especially molecular weight < 3 kDa, possess good immune activity as measured by the proliferation ability of mouse splenic lymphocytes and phagocytic activity of mouse peritoneal macrophages. Over 866 unique peptide sequences were isolated, purified, and then identified by nanohigh-performance liquid chromatography/tandem mass spectrometry (NANO-HPLC-MS/MS) from hazelnut protein hydrolysates, but Trp-Trp-Asn-Leu-Asn (WWNLN) and Trp-Ala-Val-Leu-Lys (WAVLK) in particular are found to increase the cell viability and phagocytic capacity of RAW264.7 macrophages as well as promote the secretion of the cytokines nitric oxide (NO), tumor necrosis factor-α (TNF-α), and interleukin-1ß (IL-1ß). Fluorescence resonance energy transfer assay elucidated that WWNLN and WAVLK exhibit excellent inhibitory potency against Mpro, with IC50 values of 6.695 and 16.750 µM, respectively. Classical all-atom MD simulations show that hydrogen bonds play a pivotal role in stabilizing the complex conformation and protein-peptide interaction. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation indicates that WWNLN has a lower binding free energy with Mpro than WAVLK. Furthermore, adsorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions illustrate favorable drug-likeness and pharmacokinetic properties of WWNLN compared to WAVLK. This study provides a new understanding of the immunomodulatory activity of hazelnut hydrolysates and sheds light on peptide inhibitors targeting Mpro.

AlphaFold2 Predictions of Conformational Ensembles and Atomistic Simulations of the SARS-CoV-2 Spike XBB Lineages Reveal Epistatic Couplings between Convergent Mutational Hotspots that Control ACE2 Affinity.

In this study, we combined AlphaFold-based atomistic structural modeling, microsecond molecular simulations, mutational profiling, and network analysis to characterize binding mechanisms of the SARS-CoV-2 spike protein with the host receptor ACE2 for a series of Omicron XBB variants including XBB.1.5, XBB.1.5+L455F, XBB.1.5+F456L, and XBB.1.5+L455F+F456L. AlphaFold-based structural and dynamic modeling of SARS-CoV-2 Spike XBB lineages can accurately predict the experimental structures and characterize conformational ensembles of the spike protein complexes with the ACE2. Microsecond molecular dynamics simulations identified important differences in the conformational landscapes and equilibrium ensembles of the XBB variants, suggesting that combining AlphaFold predictions of multiple conformations with molecular dynamics simulations can provide a complementary approach for the characterization of functional protein states and binding mechanisms. Using the ensemble-based mutational profiling of protein residues and physics-based rigorous calculations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of the Q493 hotspot in the synchronization of epistatic couplings between L455F and F456L mutations, providing a quantitative insight into the energetic determinants underlying binding differences between XBB lineages. We also proposed a network-based perturbation approach for mutational profiling of allosteric communications and uncovered the important relationships between allosteric centers mediating long-range communication and binding hotspots of epistatic couplings. The results of this study support a mechanism in which the binding mechanisms of the XBB variants may be determined by epistatic effects between convergent evolutionary hotspots that control ACE2 binding.

SARS-CoV-2 Mpro responds to oxidation by forming disulfide and NOS/SONOS bonds.

The main protease (Mpro) of SARS-CoV-2 is critical for viral function and a key drug target. Mpro is only active when reduced; turnover ceases upon oxidation but is restored by re-reduction. This suggests the system has evolved to survive periods in an oxidative environment, but the mechanism of this protection has not been confirmed. Here, we report a crystal structure of oxidized Mpro showing a disulfide bond between the active site cysteine, C145, and a distal cysteine, C117. Previous work proposed this disulfide provides the mechanism of protection from irreversible oxidation. Mpro forms an obligate homodimer, and the C117-C145 structure shows disruption of interactions bridging the dimer interface, implying a correlation between oxidation and dimerization. We confirm dimer stability is weakened in solution upon oxidation. Finally, we observe the protein's crystallization behavior is linked to its redox state. Oxidized Mpro spontaneously forms a distinct, more loosely packed lattice. Seeding with crystals of this lattice yields a structure with an oxidation pattern incorporating one cysteine-lysine-cysteine (SONOS) and two lysine-cysteine (NOS) bridges. These structures further our understanding of the oxidative regulation of Mpro and the crystallization conditions necessary to study this structurally.

Copper(II) coordination to the intrinsically disordered region of SARS-CoV-2 Nsp1.

The intrinsically disordered C-terminal peptide region of severe acute respiratory syndrome coronavirus 2 nonstructural protein-1 (Nsp1-CT) inhibits host protein synthesis by blocking messenger RNA (mRNA) access to the 40S ribosome entrance tunnel. Aqueous copper(II) ions bind to the disordered peptide with micromolar affinity, creating a possible strategy to restore protein synthesis during host infection. Electron paramagnetic resonance (EPR) and tryptophan fluorescence measurements on a 10-residue model of the disordered protein region (Nsp1-CT10), combined with advanced quantum mechanics calculations, suggest that the peptide binds to copper(II) as a multidentate ligand. Two optimized computational models of the copper(II)-peptide complexes were derived: One corresponding to pH 6.5 and the other describing the complex at pH 7.5 to 8.5. Simulated EPR spectra based on the calculated model structures are in good agreement with experimental spectra.

High frequency of transition to transversion ratio in the stem region of RNA secondary structure of untranslated region of SARS-CoV-2.

Introduction: The propensity of nucleotide bases to form pairs, causes folding and the formation of secondary structure in the RNA. Therefore, purine (R): pyrimidine (Y) base-pairing is vital to maintain uniform lateral dimension in RNA secondary structure. Transversions or base substitutions between R and Y bases, are more detrimental to the stability of RNA secondary structure, than transitions derived from substitutions between A and G or C and T. The study of transversion and transition base substitutions is important to understand evolutionary mechanisms of RNA secondary structure in the 5'  and 3'  untranslated (UTR) regions of SARS-CoV-2. In this work, we carried out comparative analysis of transition and transversion base substitutions in the stem and loop regions of RNA secondary structure of SARS-CoV-2. Methods: We have considered the experimentally determined and well documented stem and loop regions of 5' and 3' UTR regions of SARS-CoV-2 for base substitution analysis. The secondary structure comprising of stem and loop regions were visualized using the RNAfold web server. The GISAID repository was used to extract base sequence alignment of the UTR regions. Python scripts were developed for comparative analysis of transversion and transition frequencies in the stem and the loop regions. Results: The results of base substitution analysis revealed a higher transition (ti) to transversion (tv) ratio (ti/tv) in the stem region of UTR of RNA secondary structure of SARS-CoV-2 reported during the early stage of the pandemic. The higher ti/tv ratio in the stem region suggested the influence of secondary structure in selecting the pattern of base substitutions. This differential pattern of ti/tv values between stem and loop regions was not observed among the Delta and Omicron variants that dominated the later stage of the pandemic. It is noteworthy that the ti/tv values in the stem and loop regions were similar among the later dominant Delta and Omicron variant strains which is to be investigated to understand the rapid evolution and global adaptation of SARS-CoV-2. Conclusion: Our findings implicate the lower frequency of transversions than the transitions in the stem regions of UTRs of SARS-CoV-2. The RNA secondary structures are associated with replication, translation, and packaging, further investigations are needed to understand these base substitutions across different variants of SARS-CoV-2.

Production of native recombinant proteins using a novel split intein affinity technology.

Affinity tags are frequently engineered into recombinant proteins to facilitate purification. Although this technique is powerful, removal of the tag is desired because the tag can interfere with biological activity and can potentially increase the immunogenicity of therapeutic proteins. Tag removal is complex, as it requires adding expensive protease enzymes. To overcome this limitation, split intein based affinity purification systems have been developed in which a CC-intein tag is engineered into a protein of interest for binding to a NC-intein peptide ligand fixed to a chromatographic support. Tag removal in these systems is achieved by creating an active intein-complex during protein capture, which triggers a precise self-cleavage reaction. In this work, we show applications of a new split intein system, Cytiva™ ProteinSelect™. One advantage of the new system is that the NC-intein ligand can be robustly produced and conjugated to large volumes of resin for production of gram scale proteins. SARS-CoV-2 spike protein receptor binding domain and a Bispecific T Cell Engager in this work were successfully captured on the affinity resin and scaled 10-fold. Another advantage of this system is the ability to sanitize the resin with sodium hydroxide without loosing the 10-20 g/L binding capacity. Binding studies with IL-1b and IFNAR-1 ECD showed that the resin can be regenerated and sanitized for up to 50 cycles without loosing binding capacity. Additionally, after several cycles of sanitization, binding capacity was retained for the SARS-CoV-2 spike protein receptor binding domain and a Bispecific T Cell Engager. As with other split intein systems, optimization was needed to achieve ideal expression and recovery. The N-terminal amino acid sequence of the protein of interest required engineering to enable the cleavage reaction. Additionally, ensuring the stability of the CC-intein tag was important to prevent premature cleavage or truncation. Controlling the hold time of the expression product and the prevention of protease activity prior to purification was needed. These results demonstrate the feasibility of the Cytiva™ ProteinSelect™ system to be used in academic and industrial research and development laboratories for the purification of novel proteins expressed in either bacterial or mammalian systems.

Adenosine Triphosphate: The Primordial Molecule That Controls Protein Homeostasis and Shapes the Genome-Proteome Interface.

Adenosine triphosphate (ATP) acts as the universal energy currency that drives various biological processes, while nucleic acids function to store and transmit genetic information for all living organisms. Liquid-liquid phase separation (LLPS) represents the common principle for the formation of membrane-less organelles (MLOs) composed of proteins rich in intrinsically disordered regions (IDRs) and nucleic acids. Currently, while IDRs are well recognized to facilitate LLPS through dynamic and multivalent interactions, the precise mechanisms by which ATP and nucleic acids affect LLPS still remain elusive. This review summarizes recent NMR results on the LLPS of human FUS, TDP-43, and the viral nucleocapsid (N) protein of SARS-CoV-2, as modulated by ATP and nucleic acids, revealing the following: (1) ATP binds to folded domains overlapping with nucleic-acid-binding interfaces; (2) ATP and nucleic acids interplay to biphasically modulate LLPS by competitively binding to overlapping pockets of folded domains and Arg/Lys within IDRs; (3) ATP energy-independently induces protein folding with the highest efficiency known so far. As ATP likely emerged in the prebiotic monomeric world, while LLPS represents a pivotal mechanism to concentrate and compartmentalize rare molecules for forming primordial cells, ATP appears to control protein homeostasis and shape genome-proteome interfaces throughout the evolutionary trajectory, from prebiotic origins to modern cells.

Identification of a broad-spectrum high-affinity peptide ligand for the purification of spike proteins.

Since the outbreak of coronavirus disease 2019, the global demand for vaccines has increased rapidly to prevent infection and protect high-risk populations. However, identifying viral mutations poses an additional challenge for chromatographic purification of vaccines and subunit vaccines. In this study, a new affinity peptide model, X1VX2GLNX3WX4RYSK, was established, and a library of 612 peptides was generated for ligand screening. Based on a multistep strategy of ligand screening, 18 candidate peptides were obtained. The top ranking peptide, LP14 (YVYGLNIWLRYSK), and two other representative peptides, LP02 and LP06, with lower rankings were compared via molecular dynamics simulation. The results revealed that peptide binding to the receptor binding domain (RBD) was driven by hydrophobic interactions and the key residues involved in the binding were identified. Surface plasmon resonance analysis further confirmed that LP14 had the highest affinity for the wild RBD (Kd=0.520 µmol/L), and viral mutation had little influence on the affinity of LP14, demonstrating its great potential as a broad-spectrum ligand for RBD purification. Finally, chromatographic performance of LP14-coupled gel-packed column verified that both wild and omicron RBDs could be purified and were eluted by 0.1 mol/L Gly-HCl buffer (pH 3.0). This research identified a broad-spectrum peptide for RBD purification based on rational design and demonstrated its potential application in the purification of RBDs from complex feedstock.

Interface design of SARS-CoV-2 symmetrical nsp7 dimer and machine learning-guided nsp7 sequence prediction reveals physicochemical properties and hotspots for nsp7 stability, adaptation, and therapeutic design.

The COVID-19 pandemic, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates a profound understanding of the virus and its lifecycle. As an RNA virus with high mutation rates, SARS-CoV-2 exhibits genetic variability leading to the emergence of variants with potential implications. Among its key proteins, the RNA-dependent RNA polymerase (RdRp) is pivotal for viral replication. Notably, RdRp forms dimers via non-structural protein (nsp) subunits, particularly nsp7, crucial for efficient viral RNA copying. Similar to the main protease (Mpro) of SARS-CoV-2, there is a possibility that the nsp7 might also undergo mutational selection events to generate more stable and adaptable versions of nsp7 dimer during virus evolution. However, efforts to obtain such cohesive and comprehensive information are lacking. To address this, we performed this study focused on deciphering the molecular intricacies of nsp7 dimerization using a multifaceted approach. Leveraging computational protein design (CPD), machine learning (ML), AlphaFold v2.0-based structural analysis, and several related computational approaches, we aimed to identify critical residues and mutations influencing nsp7 dimer stability and adaptation. Our methodology involved identifying potential hotspot residues within the dimeric nsp7 interface using an interface-based CPD approach. Through Rosetta-based symmetrical protein design, we designed and modulated nsp7 dimerization, considering selected interface residues. Analysis of physicochemical features revealed acceptable structural changes and several structural and residue-specific insights emphasizing the intricate nature of such protein-protein complexes. Our ML models, particularly the random forest regressor (RFR), accurately predicted binding affinities and ML-guided sequence predictions corroborated CPD findings, elucidating potential nsp7 mutations and their impact on binding affinity. Validation against clinical sequencing data demonstrated the predictive accuracy of our approach. Moreover, AlphaFold v2.0 structural analyses validated optimal dimeric configurations of affinity-enhancing designs, affirming methodological precision. Affinity-enhancing designs exhibited favourable energetics and higher binding affinity as compared to their counterparts. The obtained physicochemical properties, molecular interactions, and sequence predictions advance our understanding of SARS-CoV-2 evolution and inform potential avenues for therapeutic intervention against COVID-19.

Computational investigation of the inhibitory interaction of IRF3 and SARS-CoV-2 accessory protein ORF3b.

ORF3b is one of the SARS-CoV-2 accessory proteins. Previous experimental study suggested that ORF3b prevents IRF3 translocating to nucleus. However, the biophysical mechanism of ORF3b-IRF3 interaction is elusive. Here, we explored the conformation ensemble of ORF3b using all-atom replica exchange molecular dynamics simulation. Disordered ORF3b has mixed α-helix, ß-turn and loop conformers. The potential ORF3b-IRF3 binding modes were searched by docking representative ORF3b conformers with IRF3, and 50 ORF3b-IRF3 complex poses were screened using molecular dynamics simulations ranging from 500 to 1000 ns. We found that ORF3b binds IRF3 predominantly on its CBP binding and phosphorylated pLxIS motifs, with CBP binding site has the highest binding affinity. The ORF3b-IRF3 binding residues are highly conserved in SARS-CoV-2. Our results provided biophysics insights into ORF3b-IRF3 interaction and explained its interferon antagonism mechanism.

The Development of Aptamer-Based Gold Nanoparticle Lateral Flow Test Strips for the Detection of SARS-CoV-2 S Proteins on the Surface of Cold-Chain Food Packaging.

The COVID-19 pandemic over recent years has shown a great need for the rapid, low-cost, and on-site detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, an aptamer-based colloidal gold nanoparticle lateral flow test strip was well developed to realize the visual detection of wild-type SARS-CoV-2 spike proteins (SPs) and multiple variants. Under the optimal reaction conditions, a low detection limit of SARS-CoV-2 S proteins of 0.68 nM was acquired, and the actual detection recovery was 83.3% to 108.8% for real-world samples. This suggests a potential tool for the prompt detection of SARS-CoV-2 with good sensitivity and accuracy, and a new method for the development of alternative antibody test strips for the detection of other viral targets.

Identification of mouse CD4+ T cell epitopes in SARS-CoV-2 BA.1 spike and nucleocapsid for use in peptide:MHCII tetramers.

Understanding adaptive immunity against SARS-CoV-2 is a major requisite for the development of effective vaccines and treatments for COVID-19. CD4+ T cells play an integral role in this process primarily by generating antiviral cytokines and providing help to antibody-producing B cells. To empower detailed studies of SARS-CoV-2-specific CD4+ T cell responses in mouse models, we comprehensively mapped I-Ab-restricted epitopes for the spike and nucleocapsid proteins of the BA.1 variant of concern via IFNγ ELISpot assay. This was followed by the generation of corresponding peptide:MHCII tetramer reagents to directly stain epitope-specific T cells. Using this rigorous validation strategy, we identified 6 immunogenic epitopes in spike and 3 in nucleocapsid, all of which are conserved in the ancestral Wuhan strain. We also validated a previously identified epitope from Wuhan that is absent in BA.1. These epitopes and tetramers will be invaluable tools for SARS-CoV-2 antigen-specific CD4+ T cell studies in mice.

RaptGen-Assisted Generation of an RNA/DNA Hybrid Aptamer against SARS-CoV-2 Spike Protein.

Optimization of aptamers in length and chemistry is crucial for industrial applications. Here, we developed aptamers against the SARS-CoV-2 spike protein and achieved optimization with a deep-learning-based algorithm, RaptGen. We conducted a primer-less SELEX against the receptor binding domain (RBD) of the spike with an RNA/DNA hybrid library, and the resulting sequences were subjected to RaptGen analysis. Based on the sequence profiling by RaptGen, a short truncation aptamer of 26 nucleotides was obtained and further optimized by a chemical modification of relevant nucleotides. The resulting aptamer is bound to RBD not only of SARS-CoV-2 wildtype but also of its variants, SARS-CoV-1, and Middle East respiratory syndrome coronavirus (MERS-CoV). We concluded that the RaptGen-assisted discovery is efficient for developing optimized aptamers.

Computationally Designed Epitope-Mediated Imprinted Polymers versus Conventional Epitope Imprints for the Detection of Human Adenovirus in Water and Human Serum Samples.

Detection of pathogenic viruses for point-of-care applications has attracted great attention since the COVID-19 pandemic. Current virus diagnostic tools are laborious and expensive, while requiring medically trained staff. Although user-friendly and cost-effective biosensors are utilized for virus detection, many of them rely on recognition elements that suffer major drawbacks. Herein, computationally designed epitope-imprinted polymers (eIPs) are conjugated with a portable piezoelectric sensing platform to establish a sensitive and robust biosensor for the human pathogenic adenovirus (HAdV). The template epitope is selected from the knob part of the HAdV capsid, ensuring surface accessibility. Computational simulations are performed to evaluate the conformational stability of the selected epitope. Further, molecular dynamics simulations are executed to investigate the interactions between the epitope and the different functional monomers for the smart design of eIPs. The HAdV epitope is imprinted via the solid-phase synthesis method to produce eIPs using in silico-selected ingredients. The synthetic receptors show a remarkable detection sensitivity (LOD: 102 pfu mL-1) and affinity (dissociation constant (Kd): 6.48 × 10-12 M) for HAdV. Moreover, the computational eIPs lead to around twofold improved binding behavior than the eIPs synthesized with a well-established conventional recipe. The proposed computational strategy holds enormous potential for the intelligent design of ultrasensitive imprinted polymer binders.

Epitope mapping of SARS-CoV-2 RBDs by hydroxyl radical protein footprinting reveals the importance of including negative antibody controls.

Understanding protein-protein interactions is crucial for drug design and investigating biological processes. Various techniques, such as CryoEM, X-ray spectroscopy, linear epitope mapping, and mass spectrometry-based methods, can be employed to map binding regions on proteins. Commonly used mass spectrometry-based techniques are cross-linking and hydrogen­deuterium exchange (HDX). Another approach, hydroxyl radical protein footprinting (HRPF), identifies binding residues on proteins but faces challenges due to high initial costs and complex setups. This study introduces a generally applicable method using Fenton chemistry for epitope mapping in a standard mass spectrometry laboratory. It emphasizes the importance of controls, particularly the inclusion of a negative antibody control, not widely utilized in HRPF epitope mapping. Quantification by TMT labelling is introduced to reduce false positives, enabling direct comparison between sample conditions and biological triplicates. Additionally, six technical replicates were incorporated to enhance the depth of analysis. Observations on the receptor-binding domain (RBD) of SARS-CoV-2 Spike Protein, Alpha and Delta variants, revealed both binding and opening regions. Significantly changed peptides upon mixing with a negative control antibody suggested structural alterations or nonspecific binding induced by the antibody alone. Integration of negative control antibody experiments and high overlap between biological triplicates led to the exclusion of 40% of significantly changed regions. The final identified binding region correlated with existing literature on neutralizing antibodies against RBD. The presented method offers a straightforward implementation for HRPF analysis in a generic mass spectrometry-based laboratory. Enhanced data reliability was achieved through increased technical and biological replicates alongside negative antibody controls.

Allosteric pathways of SARS and SARS-CoV-2 spike protein identified by neural relational inference.

The receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein must undergo a crucial conformational transition to invade human cells. It is intriguing that this transition is accompanied by a synchronized movement of the entire spike protein. Therefore, it is possible to design allosteric regulators targeting non-RBD but hindering the conformational transition of RBD. To understand the allosteric mechanism in detail, we establish a computational framework by integrating coarse-grained molecular dynamic simulations and a state-of-the-art neural network model called neural relational inference. Leveraging this framework, we have elucidated the allosteric pathway of the SARS-CoV-2 spike protein at the residue level and identified the molecular mechanisms involved in the transmission of allosteric signals. The movement of D614 is coupled with that of Q321. This interaction subsequently influences the movement of K528/K529, ultimately coupling with the movement of RBD during conformational changes. Mutations that weaken the interactions within this pathway naturally block the allosteric signal transmission, thereby modulating the conformational transitions. This observation also offers a rationale for the distinct allosteric patterns observed in the SARS-CoV spike protein. Our result provides a useful method for analyzing the dynamics of potential viral variants in the future.

Native Mass Spectrometry Dissects the Structural Dynamics of an Allosteric Heterodimer of SARS-CoV-2 Nonstructural Proteins.

Structure-based drug design, which relies on precise understanding of the target protein and its interaction with the drug candidate, is dramatically expedited by advances in computational methods for candidate prediction. Yet, the accuracy needs to be improved with more structural data from high throughput experiments, which are challenging to generate, especially for dynamic and weak associations. Herein, we applied native mass spectrometry (native MS) to rapidly characterize ligand binding of an allosteric heterodimeric complex of SARS-CoV-2 nonstructural proteins (nsp) nsp10 and nsp16 (nsp10/16), a complex essential for virus survival in the host and thus a desirable drug target. Native MS showed that the dimer is in equilibrium with monomeric states in solution. Consistent with the literature, well characterized small cosubstrate, RNA substrate, and product bind with high specificity and affinity to the dimer but not the free monomers. Unsuccessfully designed ligands bind indiscriminately to all forms. Using neutral gas collision, the nsp16 monomer with bound cosubstrate can be released from the holo dimer complex, confirming the binding to nsp16 as revealed by the crystal structure. However, we observed an unusual migration of the endogenous zinc ions bound to nsp10 to nsp16 after collisional dissociation. The metal migration can be suppressed by using surface collision with reduced precursor charge states, which presumably resulted in minimal gas-phase structural rearrangement and highlighted the importance of complementary techniques. With minimal sample input (∼µg), native MS can rapidly detect ligand binding affinities and locations in dynamic multisubunit protein complexes, demonstrating the potential of an "all-in-one" native MS assay for rapid structural profiling of protein-to-AI-based compound systems to expedite drug discovery.

Structural basis and analysis of hamster ACE2 binding to different SARS-CoV-2 spike RBDs.

Pet golden hamsters were first identified being infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant of concern (VOC) and transmitted the virus back to humans in Hong Kong in January 2022. Here, we studied the binding of two hamster (golden hamster and Chinese hamster) angiotensin-converting enzyme 2 (ACE2) proteins to the spike protein receptor-binding domains (RBDs) of SARS-CoV-2 prototype and eight variants, including alpha, beta, gamma, delta, and four omicron sub-variants (BA.1, BA.2, BA.3, and BA.4/BA.5). We found that the two hamster ACE2s present slightly lower affinity for the RBDs of all nine SARS-CoV-2 viruses tested than human ACE2 (hACE2). Furthermore, the similar infectivity to host cells expressing hamster ACE2s and hACE2 was confirmed with the nine pseudotyped SARS-CoV-2 viruses. Additionally, we determined two cryo-electron microscopy (EM) complex structures of golden hamster ACE2 (ghACE2)/delta RBD and ghACE2/omicron BA.3 RBD. The residues Q34 and N82, which exist in many rodent ACE2s, are responsible for the lower binding affinity of ghACE2 compared to hACE2. These findings suggest that all SARS-CoV-2 VOCs may infect hamsters, highlighting the necessity of further surveillance of SARS-CoV-2 in these animals.IMPORTANCESARS-CoV-2 can infect many domestic animals, including hamsters. There is an urgent need to understand the binding mechanism of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants to hamster receptors. Herein, we showed that two hamster angiotensin-converting enzyme 2s (ACE2s) (golden hamster ACE2 and Chinese hamster ACE2) can bind to the spike protein receptor-binding domains (RBDs) of SARS-CoV-2 prototype and eight variants and that pseudotyped SARS-CoV-2 viruses can infect hamster ACE2-expressing cells. The binding pattern of golden hamster ACE2 to SARS-CoV-2 RBDs is similar to that of Chinese hamster ACE2. The two hamster ACE2s present slightly lower affinity for the RBDs of all nine SARS-CoV-2 viruses tested than human ACE2. We solved the cryo-electron microscopy (EM) structures of golden hamster ACE2 in complex with delta RBD and omicron BA.3 RBD and found that residues Q34 and N82 are responsible for the lower binding affinity of ghACE2 compared to hACE2. Our work provides valuable information for understanding the cross-species transmission mechanism of SARS-CoV-2.

Prevalence of persistent SARS-CoV-2 in a large community surveillance study.

Persistent SARS-CoV-2 infections may act as viral reservoirs that could seed future outbreaks1-5, give rise to highly divergent lineages6-8 and contribute to cases with post-acute COVID-19 sequelae (long COVID)9,10. However, the population prevalence of persistent infections, their viral load kinetics and evolutionary dynamics over the course of infections remain largely unknown. Here, using viral sequence data collected as part of a national infection survey, we identified 381 individuals with SARS-CoV-2 RNA at high titre persisting for at least 30 days, of which 54 had viral RNA persisting at least 60 days. We refer to these as 'persistent infections' as available evidence suggests that they represent ongoing viral replication, although the persistence of non-replicating RNA cannot be ruled out in all. Individuals with persistent infection had more than 50% higher odds of self-reporting long COVID than individuals with non-persistent infection. We estimate that 0.1-0.5% of infections may become persistent with typically rebounding high viral loads and last for at least 60 days. In some individuals, we identified many viral amino acid substitutions, indicating periods of strong positive selection, whereas others had no consensus change in the sequences for prolonged periods, consistent with weak selection. Substitutions included mutations that are lineage defining for SARS-CoV-2 variants, at target sites for monoclonal antibodies and/or are commonly found in immunocompromised people11-14. This work has profound implications for understanding and characterizing SARS-CoV-2 infection, epidemiology and evolution.