Progressive membrane-binding mechanism of SARS-CoV-2 variant spike proteins

Bottom-up Assembled Synthetic SARS-CoV-2 Miniviruses Reveal Lipid Membrane Affinity of Omicron Variant Spike Glycoprotein

The ongoing COVID-19 pandemic has been brought on by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spike glycoprotein (S), which decorates the viral envelope forming a corona, is responsible for the binding to the angiotensin-converting enzyme 2 (ACE2) receptor and initiating the infection. In comparison to previous variants, Omicron S presents additional binding sites as well as a more positive surface charge. These changes hint at additional molecular targets for interactions between virus and cell, such as the cell membrane or proteoglycans on the cell surface. Herein, bottom-up assembled synthetic SARS-CoV-2 miniviruses (MiniVs), with a lipid composition similar to that of infectious particles, are implemented to study and compare the binding properties of Omicron and Alpha variants. Toward this end, a systematic functional screening is performed to study the binding ability of Omicron and Alpha S proteins to ACE2-functionalized and nonfunctionalized planar supported lipid bilayers. Moreover, giant unilamellar vesicles are used as a cell membrane model to perform competitive interaction assays of the two variants. Finally, two cell lines with and without presentation of the ACE2 receptor are used to confirm the binding properties of the Omicron and Alpha MiniVs to the cellular membrane. Altogether, the results reveal a significantly higher affinity of Omicron S toward both the lipid membrane and ACE2 receptor. The research presented here highlights the advantages of creating and using bottom-up assembled SARS-CoV-2 viruses to understand the impact of changes in the affinity of S for ACE2 in infection studies.

Identification of critical SARS-CoV-2 amino acids associated with COVID-19 hospitalization rate using machine learning and statistical modeling: An observational study in the United States

BACKGROUND

The COVID-19 pandemic has put many medical systems on the verge of collapse in the last two years. Virus mutation was one of the important factors affecting the COVID-19 infection severity and hospitalizations. Although over ten thousand SARS-CoV-2 mutations being reported since the beginning of the COVID-19 pandemic, only a small percentage of mutations are likely to affect the virus phenotype and change its severity. Finding out which amino acids have the greatest impact on COVID-19 hospitalization rate is an important research question.

METHODS

This observational study used the COVID-19 case hospitalization ratio (CHR) to represent the virus severity related with hospitalization. The database is based on the daily state-level epidemiological and genomic sequential data in the United States from the Alpha wave to the first Omicron wave. The critical amino acids that mostly affected the CHR were determined by using four types of models including extreme gradient boosting decision trees (XGBoost), artificial neural networks (ANNs), logistic regression and Lasso regression models.

RESULTS

The XGBoost, ANN, logistic regression, and Lasso regression models all produce excellent results (mean square error for all state-level models does not exceed 0.0008 using the testing dataset). Based on the rank of importance of all covariates, the critical amino acids most affecting the CHR were identified, including T19, L24, P25, P26, A27, A67, H69, V70, T95, G142, V143, Y145, E156, F157, N211, L212, V213, R214, D215, G339, R346, S373, L452, S477, T478, E484, N501, A570, P681, and T716.

CONCLUSION

This study identified critical amino acids that are most likely to affect the hospitalization rate, allowing public health workers to monitor these highly risky amino acids and raise an alarm immediately when more severe mutations occur. Furthermore, the methodology and results may be extended to other regions.

Ghosts of the past: Elemental composition, biosynthesis reactions and thermodynamic properties of Zeta P.2, Eta B.1.525, Theta P.3, Kappa B.1.617.1, Iota B.1.526, Lambda C.37 and Mu B.1.621 variants of SARS-CoV-2

From the perspectives of molecular biology, genetics and biothermodynamics, SARS-CoV-2 is the among the best characterized viruses. Research on SARS-CoV-2 has shed a new light onto driving forces and molecular mechanisms of viral evolution. This paper reports results on empirical formulas, biosynthesis reactions and thermodynamic properties of biosynthesis (multiplication) for the Zeta P.2, Eta B.1.525, Theta P.3, Kappa B.1.617.1, Iota B.1.526, Lambda C.37 and Mu B.1.621 variants of SARS-CoV-2. Thermodynamic analysis has shown that the physical driving forces for evolution of SARS-CoV-2 are Gibbs energy of biosynthesis and Gibbs energy of binding. The driving forces have led SARS-CoV-2 through the evolution process from the original Hu-1 to the newest variants in accordance with the expectations of the evolution theory.

Comprehensive classification of proteins based on structures that engage lipids by COMPOSEL

Structures can now be predicted for any protein using programs like AlphaFold and Rosetta, which rely on a foundation of experimentally determined structures of architecturally diverse proteins. The accuracy of such artificial intelligence and machine learning (AI/ML) approaches benefits from the specification of restraints which assist in navigating the universe of folds to converge on models most representative of a given protein's physiological structure. This is especially pertinent for membrane proteins, with structures and functions that depend on their presence in lipid bilayers. Structures of proteins in their membrane environments could conceivably be predicted from AI/ML approaches with user-specificized parameters that describe each element of the architecture of a membrane protein accompanied by its lipid environment. We propose the Classification Of Membrane Proteins based On Structures Engaging Lipids (COMPOSEL), which builds on existing nomenclature types for monotopic, bitopic, polytopic and peripheral membrane proteins as well as lipids. Functional and regulatory elements are also defined in the scripts, as shown with membrane fusing synaptotagmins, multidomain PDZD8 and Protrudin proteins that recognize phosphoinositide (PI) lipids, the intrinsically disordered MARCKS protein, caveolins, the β barrel assembly machine (BAM), an adhesion G-protein coupled receptor (aGPCR) and two lipid modifying enzymes - diacylglycerol kinase DGKε and fatty aldehyde dehydrogenase FALDH. This demonstrates how COMPOSEL communicates lipid interactivity as well as signaling mechanisms and binding of metabolites, drug molecules, polypeptides or nucleic acids to describe the operations of any protein. Moreover COMPOSEL can be scaled to express how genomes encode membrane structures and how our organs are infiltrated by pathogens such as SARS-CoV-2.

SARS-CoV-2 Omicron Subvariants Balance Host Cell Membrane, Receptor, and Antibody Docking via an Overlapping Target Site

Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging rapidly and offer surfaces that are optimized for recognition of host cell membranes while also evading antibodies arising from vaccinations and previous infections. Host cell infection is a multi-step process in which spike heads engage lipid bilayers and one or more angiotensin-converting enzyme 2 (ACE-2) receptors. Here, the membrane binding surfaces of Omicron subvariants are compared using cryo-electron microscopy (cEM) structures of spike trimers from BA.2, BA.2.12.1, BA.2.13, BA.2.75, BA.3, BA.4, and BA.5 viruses. Despite significant differences around mutated sites, they all maintain strong membrane binding propensities that first appeared in BA.1. Both their closed and open states retain elevated membrane docking capacities, although the presence of more closed than open states diminishes opportunities to bind receptors while enhancing membrane engagement. The electrostatic dipoles are generally conserved. However, the BA.2.75 spike dipole is compromised, and its ACE-2 affinity is increased, and BA.3 exhibits the opposite pattern. We propose that balancing the functional imperatives of a stable, readily cleavable spike that engages both lipid bilayers and receptors while avoiding host defenses underlies betacoronavirus evolution. This provides predictive criteria for rationalizing future pandemic waves and COVID-19 transmissibility while illuminating critical sites and strategies for simultaneously combating multiple variants.

Role of cholesterol-recognition motifs in the infectivity of SARS-CoV-2 variants

The presence of linear amino acid motifs with the capacity to recognize the neutral lipid cholesterol, known as Cholesterol Recognition/interaction Amino acid Consensus sequence (CRAC), and its inverse or mirror image, CARC, has recently been reported in the primary sequence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike S homotrimeric glycoprotein. These motifs also occur in the two other pathogenic coronaviruses, SARS-CoV, and Middle-East respiratory syndrome CoV (MERS-CoV), most conspicuously in the transmembrane domain, the fusion peptide, the amino-terminal domain, and the receptor binding domain of SARS-CoV-2 S protein. Here we analyze the presence of cholesterol-recognition motifs in these key regions of the spike glycoprotein in the pathogenic CoVs. We disclose the inherent pathophysiological implications of the cholesterol motifs in the virus-host cell interactions and variant infectivity.

Transmembrane Membrane Readers form a Novel Class of Proteins That Include Peripheral Phosphoinositide Recognition Domains and Viral Spikes

Membrane proteins are broadly classified as transmembrane (TM) or peripheral, with functions that pertain to only a single bilayer at a given time. Here, we explicate a class of proteins that contain both transmembrane and peripheral domains, which we dub transmembrane membrane readers (TMMRs). Their transmembrane and peripheral elements anchor them to one bilayer and reversibly attach them to another section of bilayer, respectively, positioning them to tether and fuse membranes while recognizing signals such as phosphoinositides (PIs) and modifying lipid chemistries in proximity to their transmembrane domains. Here, we analyze full-length models from AlphaFold2 and Rosetta, as well as structures from nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography, using the Membrane Optimal Docking Area (MODA) program to map their membrane-binding surfaces. Eukaryotic TMMRs include phospholipid-binding C1, C2, CRAL-TRIO, FYVE, GRAM, GTPase, MATH, PDZ, PH, PX, SMP, StART and WD domains within proteins including protrudin, sorting nexins and synaptotagmins. The spike proteins of SARS-CoV-2 as well as other viruses are also TMMRs, seeing as they are anchored into the viral membrane while mediating fusion with host cell membranes. As such, TMMRs have key roles in cell biology and membrane trafficking, and include drug targets for diseases such as COVID-19.

Cytoplasmic tail determines the membrane trafficking and localization of SARS-CoV-2 spike protein

The spike (S) glycoprotein of SARS-CoV-2 mediates viral entry through associating with ACE2 on host cells. Intracellular trafficking and palmitoylation of S protein are required for its function. The short cytoplasmic tail of S protein plays a key role in the intracellular trafficking, which contains the binding site for the host trafficking proteins such as COPI, COPII and SNX27. This cytoplasmic tail also contains the palmitoylation sites of S protein. Protein palmitoylation modification of S protein could be catalyzed by a family of zinc finger DHHC domain-containing protein palmitoyltransferases (ZDHHCs). The intracellular trafficking and membrane location facilitate surface expression of S protein and assembly of progeny virions. In this review, we summarize the function of S protein cytoplasmic tail in transportation and localization. S protein relies on intracellular trafficking pathways and palmitoylation modification to facilitate the life cycle of SARS-CoV-2, meanwhile it could interfere with the host transport pathways. The interplay between S protein and intracellular trafficking proteins could partially explain the acute symptoms or Long-COVID complications in multiple organs of COVID-19 patients.