Immune evasion and ACE2 binding affinity contribute to SARS-CoV-2 evolution

An evolutionary theory on virus mutation in COVID-19

With the rapid evolution of SARS-CoV-2, the emergence of new strains is an intriguing question. This paper presents an evolutionary theory to analyze the mutations of the virus and identify the conditions that lead to the generation of new strains. We represent the virus variants using a 4-letter sequence based on amino acid mutations on the spike protein and employ an n-distance algorithm to derive a variant phylogenetic tree. We show that the theoretically-derived tree aligns with experimental data on virus evolution. Additionally, we propose an A-X model, utilizing the set of existing mutation sites (A) and a set of randomly generated sites (X), to calculate the emergence of new strains. Our findings demonstrate that a sufficient number of random iterations can predict the generation of new macro-lineages when the number of sites in X is large enough. These results provide a crucial theoretical basis for understanding the evolution of SARS-CoV-2.

Proteomics Platform Reveals Broad-Spectrum Nanobodies for SARS-CoV-2 Variant Neutralization

The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the emergence of different variants of concerns with immune evasion that have been prevalent over the past three years. Nanobodies, the functional variable regions of camelid heavy-chain-only antibodies, have garnered interest in developing neutralizing antibodies due to their smaller size, structural stability, ease of production, high affinity, and low immunogenicity, among other characteristics. In this work, we describe an integrated proteomics platform for the high-throughput screening of nanobodies against different SARS-CoV-2 spike variants. To demonstrate this platform, we immunized a camel with subunit 1 (S1) of the wild-type spike protein and constructed a nanobody phage library. The binding and neutralizing activities of the nanobodies against 72 spike variants were then measured, resulting in the identification of two nanobodies (C-282 and C-39) with broad neutralizing activity against six non-Omicron variants (D614G, Alpha, Beta, Gamma, Delta, Kappa) and five Omicron variants (BA.1-5). Their neutralizing capability was validated using in vitro pseudovirus-based neutralization assays. All these results demonstrate the utility of our proteomics platform to identify new nanobodies with broad neutralizing capability and to develop a treatment for patients with SARS-CoV-2 variant infection in the future.

Ensemble-Based Mutational Profiling and Network Analysis of the SARS-CoV-2 Spike Omicron XBB Lineages for Interactions with the ACE2 Receptor and Antibodies: Cooperation of Binding Hotspots in Mediating Epistatic Couplings Underlies Binding Mechanism and Immune Escape

In this study, we performed a computational study of binding mechanisms for the SARS-CoV-2 spike Omicron XBB lineages with the host cell receptor ACE2 and a panel of diverse class one antibodies. The central objective of this investigation was to examine the molecular factors underlying epistatic couplings among convergent evolution hotspots that enable optimal balancing of ACE2 binding and antibody evasion for Omicron variants BA.1, BA2, BA.3, BA.4/BA.5, BQ.1.1, XBB.1, XBB.1.5, and XBB.1.5 + L455F/F456L. By combining evolutionary analysis, molecular dynamics simulations, and ensemble-based mutational scanning of spike protein residues in complexes with ACE2, we identified structural stability and binding affinity hotspots that are consistent with the results of biochemical studies. In agreement with the results of deep mutational scanning experiments, our quantitative analysis correctly reproduced strong and variant-specific epistatic effects in the XBB.1.5 and BA.2 variants. It was shown that Y453W and F456L mutations can enhance ACE2 binding when coupled with Q493 in XBB.1.5, while these mutations become destabilized when coupled with the R493 position in the BA.2 variant. The results provided a molecular rationale of the epistatic mechanism in Omicron variants, showing a central role of the Q493/R493 hotspot in modulating epistatic couplings between convergent mutational sites L455F and F456L in XBB lineages. The results of mutational scanning and binding analysis of the Omicron XBB spike variants with ACE2 receptors and a panel of class one antibodies provide a quantitative rationale for the experimental evidence that epistatic interactions of the physically proximal binding hotspots Y501, R498, Q493, L455F, and F456L can determine strong ACE2 binding, while convergent mutational sites F456L and F486P are instrumental in mediating broad antibody resistance. The study supports a mechanism in which the impact on ACE2 binding affinity is mediated through a small group of universal binding hotspots, while the effect of immune evasion could be more variant-dependent and modulated by convergent mutational sites in the conformationally adaptable spike regions.

SARS-CoV-2 Omicron Subvariants Do Not Differ Much in Binding Affinity to Human ACE2: A Molecular Dynamics Study

The emergence of the variant of concern Omicron (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exacerbates the COVID-19 pandemic due to its high contagious ability. Studies have shown that the Omicron binds human ACE2 more strongly than the wild type. The prevalence of Omicron in new cases of COVID-19 promotes novel lineages with improved receptor binding affinity and immune evasion. To shed light on this open problem, in this work, we investigated the binding free energy of the receptor binding domain of the Omicron lineages BA.2, BA.2.3.20, BA.3, BA4/BA5, BA.2.75, BA.2.75.2, BA.4.6, XBB.1, XBB.1.5, BJ.1, BN.1, BQ.1.1, and CH.1.1 to human ACE2 using all-atom molecular dynamics simulation and the molecular mechanics Poisson-Boltzmann surface area method. The results show that these lineages have increased binding affinity compared to the BA.1 lineage, and BA.2.75 and BA.2.75.2 subvariants bind ACE2 more strongly than others. However, in general, the binding affinities of the Omicron lineages do not differ significantly from each other. The electrostatic force dominates over the van der Waals force in the interaction between Omicron lineages and human cells. Based on our results, we argue that viral evolution does not further improve the affinity of SARS-CoV-2 for ACE2 but may increase immune evasion.

Key mechanistic features of the trade-off between antibody escape and host cell binding in the SARS-CoV-2 Omicron variant spike proteins

Since SARS-CoV-2 Omicron variant emerged, it is constantly evolving into multiple sub-variants, including BF.7, BQ.1, BQ.1.1, XBB, XBB.1.5 and the recently emerged BA.2.86 and JN.1. Receptor binding and immune evasion are recognized as two major drivers for evolution of the receptor binding domain (RBD) of the SARS-CoV-2 spike (S) protein. However, the underlying mechanism of interplay between two factors remains incompletely understood. Herein, we determined the structures of human ACE2 complexed with BF.7, BQ.1, BQ.1.1, XBB and XBB.1.5 RBDs. Based on the ACE2/RBD structures of these sub-variants and a comparison with the known complex structures, we found that R346T substitution in the RBD enhanced ACE2 binding upon an interaction with the residue R493, but not Q493, via a mechanism involving long-range conformation changes. Furthermore, we found that R493Q and F486V exert a balanced impact, through which immune evasion capability was somewhat compromised to achieve an optimal receptor binding. We propose a "two-steps-forward and one-step-backward" model to describe such a compromise between receptor binding affinity and immune evasion during RBD evolution of Omicron sub-variants.

CovEpiAb: a comprehensive database and analysis resource for immune epitopes and antibodies of human coronaviruses

Coronaviruses have threatened humans repeatedly, especially COVID-19 caused by SARS-CoV-2, which has posed a substantial threat to global public health. SARS-CoV-2 continuously evolves through random mutation, resulting in a significant decrease in the efficacy of existing vaccines and neutralizing antibody drugs. It is critical to assess immune escape caused by viral mutations and develop broad-spectrum vaccines and neutralizing antibodies targeting conserved epitopes. Thus, we constructed CovEpiAb, a comprehensive database and analysis resource of human coronavirus (HCoVs) immune epitopes and antibodies. CovEpiAb contains information on over 60 000 experimentally validated epitopes and over 12 000 antibodies for HCoVs and SARS-CoV-2 variants. The database is unique in (1) classifying and annotating cross-reactive epitopes from different viruses and variants; (2) providing molecular and experimental interaction profiles of antibodies, including structure-based binding sites and around 70 000 data on binding affinity and neutralizing activity; (3) providing virological characteristics of current and past circulating SARS-CoV-2 variants and in vitro activity of various therapeutics; and (4) offering site-level annotations of key functional features, including antibody binding, immunological epitopes, SARS-CoV-2 mutations and conservation across HCoVs. In addition, we developed an integrated pipeline for epitope prediction named COVEP, which is available from the webpage of CovEpiAb. CovEpiAb is freely accessible at https://pgx.zju.edu.cn/covepiab/.

AlphaFold2-Enabled Atomistic Modeling of Structure, Conformational Ensembles, and Binding Energetics of the SARS-CoV-2 Omicron BA.2.86 Spike Protein with ACE2 Host Receptor and Antibodies: Compensatory Functional Effects of Binding Hotspots in Modulating Mechanisms of Receptor Binding and Immune Escape

The latest wave of SARS-CoV-2 Omicron variants displayed a growth advantage and increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and efficient immune evasion. In this study, we combined AlphaFold2-based structural modeling approaches with atomistic simulations and mutational profiling of binding energetics and stability for prediction and comprehensive analysis of the structure, dynamics, and binding of the SARS-CoV-2 Omicron BA.2.86 spike variant with ACE2 host receptor and distinct classes of antibodies. We adapted several AlphaFold2 approaches to predict both the structure and conformational ensembles of the Omicron BA.2.86 spike protein in the complex with the host receptor. The results showed that the AlphaFold2-predicted structural ensemble of the BA.2.86 spike protein complex with ACE2 can accurately capture the main conformational states of the Omicron variant. Complementary to AlphaFold2 structural predictions, microsecond molecular dynamics simulations reveal the details of the conformational landscape and produced equilibrium ensembles of the BA.2.86 structures that are used to perform mutational scanning of spike residues and characterize structural stability and binding energy hotspots. The ensemble-based mutational profiling of the receptor binding domain residues in the BA.2 and BA.2.86 spike complexes with ACE2 revealed a group of conserved hydrophobic hotspots and critical variant-specific contributions of the BA.2.86 convergent mutational hotspots R403K, F486P, and R493Q. To examine the immune evasion properties of BA.2.86 in atomistic detail, we performed structure-based mutational profiling of the spike protein binding interfaces with distinct classes of antibodies that displayed significantly reduced neutralization against the BA.2.86 variant. The results revealed the molecular basis of compensatory functional effects of the binding hotspots, showing that BA.2.86 lineage may have evolved to outcompete other Omicron subvariants by improving immune evasion while preserving binding affinity with ACE2 via through a compensatory effect of R493Q and F486P convergent mutational hotspots. This study demonstrated that an integrative approach combining AlphaFold2 predictions with complementary atomistic molecular dynamics simulations and robust ensemble-based mutational profiling of spike residues can enable accurate and comprehensive characterization of structure, dynamics, and binding mechanisms of newly emerging Omicron variants.

Using big sequencing data to identify chronic SARS-Coronavirus-2 infections

The evolution of SARS-Coronavirus-2 (SARS-CoV-2) has been characterized by the periodic emergence of highly divergent variants. One leading hypothesis suggests these variants may have emerged during chronic infections of immunocompromised individuals, but limited data from these cases hinders comprehensive analyses. Here, we harnessed millions of SARS-CoV-2 genomes to identify potential chronic infections and used language models (LM) to infer chronic-associated mutations. First, we mined the SARS-CoV-2 phylogeny and identified chronic-like clades with identical metadata (location, age, and sex) spanning over 21 days, suggesting a prolonged infection. We inferred 271 chronic-like clades, which exhibited characteristics similar to confirmed chronic infections. Chronic-associated mutations were often high-fitness immune-evasive mutations located in the spike receptor-binding domain (RBD), yet a minority were unique to chronic infections and absent in global settings. The probability of observing high-fitness RBD mutations was 10-20 times higher in chronic infections than in global transmission chains. The majority of RBD mutations in BA.1/BA.2 chronic-like clades bore predictive value, i.e., went on to display global success. Finally, we used our LM to infer hundreds of additional chronic-like clades in the absence of metadata. Our approach allows mining extensive sequencing data and providing insights into future evolutionary patterns of SARS-CoV-2.

Classification of five SARS-CoV-2 serotypes based on RBD antigenicities

The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a significant number of variants, particularly with the emergence of Omicron with many sub-variants. These variants have exhibited increased immune escape, leading to reduced efficacy of existing vaccines and therapeutic antibodies. Given the diminished cross-neutralization observed among these variants, it is plausible that SARS-CoV-2 has developed multiple serotypes. As the major antigenic site, the receptor-binding domain (RBD) of viral spike (S) protein was chosen for serotyping. We selected 23 representative variants, including pre-Omicron variants and Omicron sub-variants, and classified them into five serotypes based on systematic evaluation of the antigenicities of their RBDs. Each serotype includes several genetically distinct variants. Serotype-I encompasses all pre-Omicron variants (with two subtypes), while the remaining four serotypes are all comprised of Omicron sub-variants at different stages of evolution. We propose that these serotypes can serve as a foundation for rapid classification of newly emerging SARS-CoV-2 variants, and guide the development of future broad-spectrum vaccines and neutralizing antibodies against the coronavirus disease 2019 (COVID-19).

AlphaFold2-Enabled Atomistic Modeling of Epistatic Binding Mechanisms for the SARS-CoV-2 Spike Omicron XBB.1.5, EG.5 and FLip Variants: Convergent Evolution Hotspots Cooperate to Control Stability and Conformational Adaptability in Balancing ACE2 Binding and Antibody Resistance

In this study, we combined AI-based atomistic structural modeling and microsecond molecular simulations of the SARS-CoV-2 Spike complexes with the host receptor ACE2 for XBB.1.5+L455F, XBB.1.5+F456L(EG.5) and XBB.1.5+L455F/F456L (FLip) lineages to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and physics-based rigorous computations of binding affinities, we identified binding energy hotspots and characterized molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of Q493 hotspot in synchronization of epistatic couplings between L455F and F456L mutations providing a quantitative insight into the mechanism underlying differences between XBB lineages. Mutational profiling is combined with network-based model of epistatic couplings showing that the Q493, L455 and F456 sites mediate stable communities at the binding interface with ACE2 and can serve as stable mediators of non-additive couplings. Structure-based mutational analysis of Spike protein binding with the class 1 antibodies quantified the critical role of F456L and F486P mutations in eliciting strong immune evasion response. The results of this analysis support a mechanism in which the emergence of EG.5 and FLip variants may have been dictated by leveraging strong epistatic effects between several convergent revolutionary hotspots that provide synergy between the improved ACE2 binding and broad neutralization resistance. This interpretation is consistent with the notion that functionally balanced substitutions which simultaneously optimize immune evasion and high ACE2 affinity may continue to emerge through lineages with beneficial pair or triplet combinations of RBD mutations involving mediators of epistatic couplings and sites in highly adaptable RBD regions.

Accurate Characterization of Conformational Ensembles and Binding Mechanisms of the SARS-CoV-2 Omicron BA.2 and BA.2.86 Spike Protein with the Host Receptor and Distinct Classes of Antibodies Using AlphaFold2-Augmented Integrative Computational Modeling

The latest wave SARS-CoV-2 Omicron variants displayed a growth advantage and the increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and efficient immune evasion. In this study, we combined AlphaFold2-based structural modeling approaches with all-atom MD simulations and mutational profiling of binding energetics and stability for prediction and comprehensive analysis of the structure, dynamics, and binding of the SARS-CoV-2 Omicron BA.2.86 spike variant with ACE2 host receptor and distinct classes of antibodies. We adapted several AlphaFold2 approaches to predict both structure and conformational ensembles of the Omicron BA.2.86 spike protein in the complex with the host receptor. The results showed that AlphaFold2-predicted conformational ensemble of the BA.2.86 spike protein complex can accurately capture the main dynamics signatures obtained from microscond molecular dynamics simulations. The ensemble-based dynamic mutational scanning of the receptor binding domain residues in the BA.2 and BA.2.86 spike complexes with ACE2 dissected the role of the BA.2 and BA.2.86 backgrounds in modulating binding free energy changes revealing a group of conserved hydrophobic hotspots and critical variant-specific contributions of the BA.2.86 mutational sites R403K, F486P and R493Q. To examine immune evasion properties of BA.2.86 in atomistic detail, we performed large scale structure-based mutational profiling of the S protein binding interfaces with distinct classes of antibodies that displayed significantly reduced neutralization against BA.2.86 variant. The results quantified specific function of the BA.2.86 mutations to ensure broad resistance against different classes of RBD antibodies. This study revealed the molecular basis of compensatory functional effects of the binding hotspots, showing that BA.2.86 lineage may have primarily evolved to improve immune escape while modulating binding affinity with ACE2 through cooperative effect of R403K, F486P and R493Q mutations. The study supports a hypothesis that the impact of the increased ACE2 binding affinity on viral fitness is more universal and is mediated through cross-talk between convergent mutational hotspots, while the effect of immune evasion could be more variant-dependent.

Neuroprotective Agents with Therapeutic Potential for COVID-19

COVID-19 patients can exhibit a wide range of clinical manifestations affecting various organs and systems. Neurological symptoms have been reported in COVID-19 patients, both during the acute phase of the illness and in cases of long-term COVID. Moderate symptoms include ageusia, anosmia, altered mental status, and cognitive impairment, and in more severe cases can manifest as ischemic cerebrovascular disease and encephalitis. In this narrative review, we delve into the reported neurological symptoms associated with COVID-19, as well as the underlying mechanisms contributing to them. These mechanisms include direct damage to neurons, inflammation, oxidative stress, and protein misfolding. We further investigate the potential of small molecules from natural products to offer neuroprotection in models of neurodegenerative diseases. Through our analysis, we discovered that flavonoids, alkaloids, terpenoids, and other natural compounds exhibit neuroprotective effects by modulating signaling pathways known to be impacted by COVID-19. Some of these compounds also directly target SARS-CoV-2 viral replication. Therefore, molecules of natural origin show promise as potential agents to prevent or mitigate nervous system damage in COVID-19 patients. Further research and the evaluation of different stages of the disease are warranted to explore their potential benefits.

Risk of SARS-CoV-2 Reinfection 3 Years after the Start of the Pandemic: A Population-Level Observational Study

The risk of SARS-CoV-2 reinfections changes as new variants emerge, but the follow-up time for most of the available evidence is shorter than two years. This study evaluated SARS-CoV-2 reinfection rates in the total population of an Italian province up to three years since the pandemic's start. This retrospective cohort study used official National Healthcare System data on SARS-CoV-2 testing and vaccinations, demographics, and hospitalizations in the Province of Pescara, Italy, from 2 March 2020 to 31 December 2022. A total of 6541 (5.4%) reinfections and 33 severe and 18 lethal COVID-19 cases were recorded among the 121,412 subjects who recovered from a primary infection. There were no severe events following reinfection in the young population, whereas 1.1% of reinfected elderly died. A significantly higher reinfection risk was observed among females; unvaccinated individuals; adults (30-59 y); and subjects with hypertension, COPD, and kidney disease. Up to three years after a primary SARS-CoV-2 infection, the majority of the population did not experience a reinfection. The risk of severe COVID-19 following a reinfection was very low for young and adult individuals but still high for the elderly. The subjects with hybrid immunity showed a lower reinfection risk than the unvaccinated.