Molecular basis for higher affinity of SARS-CoV-2 spike RBD for human ACE2 receptor

Structural Adaptation of Secondary p53 Binding Sites on MDM2 and MDMX

The thermodynamics of secondary p53 binding sites on MDM2 and MDMX were evaluated using p53 peptides containing residues 16-29, 17-35, and 1-73. All the peptides had large, negative heat capacity (ΔCp), consistent with the burial of p53 residues F19, W23, and L26 in the primary binding sites of MDM2 and MDMX. MDMX has a higher affinity and more negative ΔCp than MDM2 for p5317-35, which is due to MDMX stabilization and not additional interactions with the secondary binding site. ΔCp measurements show binding to the secondary site is inhibited by the disordered tails of MDM2 for WT p53 but not a more helical mutant where proline 27 is changed to alanine. This result is supported by all-atom molecular dynamics simulations showing that p53 residues 30-35 turn away from the disordered tails of MDM2 in P27A17-35 and make direct contact with this region in p5317-35. Molecular dynamics simulations also suggest that an intramolecular methionine-aromatic motif found in both MDM2 and MDMX structurally adapts to support multiple p53 binding modes with the secondary site. ΔCp measurements also show that tighter binding of the P27A mutant to MDM2 and MDMX is due to increased helicity, which reduces the energetic penalty associated with coupled folding and binding. Our results will facilitate the design of selective p53 inhibitors for MDM2 and MDMX.

The Role of Extracellular Vesicles in Pandemic Viral Infections

Extracellular vesicles (EVs), of diverse origin and content, are membranous structures secreted by a broad range of cell types. Recent advances in molecular biology have highlighted the pivotal role of EVs in mediating intercellular communication, facilitated by their ability to transport a diverse range of biomolecules, including proteins, lipids, DNA, RNA and metabolites. A striking feature of EVs is their ability to exert dual effects during viral infections, involving both proviral and antiviral effects. This review explores the dual roles of EVs, particularly in the context of pandemic viruses such as HIV-1 and SARS-CoV-2. On the one hand, EVs can enhance viral replication and exacerbate pathogenesis by transferring viral components to susceptible cells. On the other hand, they have intrinsic antiviral properties, including activation of immune responses and direct inhibition of viral infection. By exploring these contrasting functions, our review emphasizes the complexity of EV-mediated interactions in viral pathogenesis and highlights their potential as targets for therapeutic intervention. The insights obtained from investigating EVs in the context of HIV-1 and SARS-CoV-2 provide a deeper understanding of viral mechanisms and pathologies, and offer a new perspective on managing and mitigating the impact of these global health challenges.

Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments

The GEMS method enables molecular dynamics simulations of large heterogeneous systems at ab initio quality.

Many Roles of Carbohydrates: A Computational Spotlight on the Coronavirus S Protein Binding

Glycosylation is one of the post-translational modifications with more than 50% of human proteins being glycosylated. The exact nature and chemical composition of glycans are inaccessible to X-ray or cryo-electron microscopy imaging techniques. Therefore, computational modeling studies and molecular dynamics must be used as a "computational microscope". The spike (S) protein of SARS-CoV-2 is heavily glycosylated, and a few glycans play a more functional role "beyond shielding". In this mini-review, we discuss computational investigations of the roles of specific S-protein and ACE2 glycans in the overall ACE2-S protein binding. We highlight different functions of specific glycans demonstrated in myriad computational models and simulations in the context of the SARS-CoV-2 virus binding to the receptor. We also discuss interactions between glycocalyx and the S protein, which may be utilized to design prophylactic polysaccharide-based therapeutics targeting the S protein. In addition, we underline the recent emergence of coronavirus variants and their impact on the S protein and its glycans.

Polarizable AMOEBA Model for Simulating Mg2+·Protein·Nucleotide Complexes

Molecular mechanics (MM) simulations have the potential to provide detailed insights into the mechanisms of enzymes that utilize nucleotides as cofactors. In most cases, the activities of these enzymes also require the binding of divalent cations to catalytic sites. However, modeling divalent cations in MM simulations has been challenging. The inclusion of explicit polarization was considered promising, but despite improvements over nonpolarizable force fields and despite the inclusion of "Nonbonded-fix (NB-fix)" corrections, errors in interaction energies of divalent cations with proteins remain large. Importantly, the application of these models fails to reproduce the experimental structural data on Mg2+·Protein·ATP complexes. Focusing on these complexes, here we provide a systematic assessment of the polarizable AMOEBA model and recommend critical changes that substantially improve its predictive performance. Our key results are as follows. We first show that our recent revision of the AMOEBA protein model (AMOEBABIO18-HFC), which contains high field corrections (HFCs) to induced dipoles, dramatically improves Mg2+-protein interaction energies, reducing the mean absolute error (MAE) from 17 to 10 kcal/mol. This further supports the general applicability of AMOEBABIO18-HFC. The inclusion of many-body NB-fix corrections further reduces MAE to 6 kcal/mol, which amounts to less than 2% error. The errors are estimated with respect to vdW-inclusive density functional theory that we benchmark against CCSD(T) calculations and experiments. We also present a new model of ATP with revised polarization parameters to better capture its high field response, as well as new vdW and dihedral parameters. The ATP model accurately predicts experimental Mg2+-ATP binding free energy in the aqueous phase and provides new insights into how Mg2+ associates with ATP. Finally, we show that molecular dynamics (MD) simulations of Mg2+·Kinase·ATP complexes carried out with these improvements lead to a better agreement in global and local catalytic site structures between MD and X-ray crystallography.

How helpful were molecular dynamics simulations in shaping our understanding of SARS-CoV-2 spike protein dynamics?

The SARS-CoV-2 spike protein (S) represents an important viral component that is required for successful viral infection in humans owing to its essential role in recognition of and entry to host cells. The spike is also an appealing target for drug designers who develop vaccines and antivirals. This article is important as it summarizes how molecular simulations successfully shaped our understanding of spike conformational behavior and its role in viral infection. MD simulations found that the higher affinity of SARS-CoV-2-S to ACE2 is linked to its unique residues that add extra electrostatic and van der Waal interactions in comparison to the SARS-CoV S. This illustrates the spread potential of the pandemic SARS-CoV-2 relative to the epidemic SARS-CoV. Different mutations at the S-ACE2 interface, which is believed to increase the transmission of the new variants, affected the behavior and binding interactions in different simulations. The contributions of glycans to the opening of S were revealed via simulations. The immune evasion of S was linked to the spatial distribution of glycans. This help the virus to escape the immune system recognition. This article is important as it summarizes how molecular simulations successfully shaped our understanding of spike conformational behavior and its role in viral infection. This will pave the way to us preparing for the next pandemic as the computational tools are tailored to help fight new challenges.

Machine learning and protein allostery

The fundamental biological importance and complexity of allosterically regulated proteins stem from their central role in signal transduction and cellular processes. Recently, machine-learning approaches have been developed and actively deployed to facilitate theoretical and experimental studies of protein dynamics and allosteric mechanisms. In this review, we survey recent developments in applications of machine-learning methods for studies of allosteric mechanisms, prediction of allosteric effects and allostery-related physicochemical properties, and allosteric protein engineering. We also review the applications of machine-learning strategies for characterization of allosteric mechanisms and drug design targeting SARS-CoV-2. Continuous development and task-specific adaptation of machine-learning methods for protein allosteric mechanisms will have an increasingly important role in bridging a wide spectrum of data-intensive experimental and theoretical technologies.

Identifying promising druggable binding sites and their flexibility to target the receptor-binding domain of SARS-CoV-2 spike protein

The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for viral infection. The interaction of its receptor-binding domain (RBD) with the human angiotensin-converting enzyme 2 (ACE2) protein is required for the virus to enter the host cell. We identified RBD binding sites to block its function with inhibitors by combining the protein structural flexibility with machine learning analysis. Molecular dynamics simulations were performed on unbound or ACE2-bound RBD conformations. Pockets estimation, tracking and druggability prediction were performed on a large sample of simulated RBD conformations. Recurrent druggable binding sites and their key residues were identified by clustering pockets based on their residue similarity. This protocol successfully identified three druggable sites and their key residues, aiming to target with inhibitors for preventing ACE2 interaction. One site features key residues for direct ACE2 interaction, highlighted using energetic computations, but can be affected by several mutations of the variants of concern. Two highly druggable sites, located between the spike protein monomers interface are promising. One weakly impacted by only one Omicron mutation, could contribute to stabilizing the spike protein in its closed state. The other, currently not affected by mutations, could avoid the activation of the spike protein trimer.

Detection of COVID-19-related biomarkers by electrochemical biosensors and potential for diagnosis, prognosis, and prediction of the course of the disease in the context of personalized medicine

As a more efficient and effective way to address disease diagnosis and intervention, cutting-edge technologies, devices, therapeutic approaches, and practices have emerged within the personalized medicine concept depending on the particular patient's biology and the molecular basis of the disease. Personalized medicine is expected to play a pivotal role in assessing disease risk or predicting response to treatment, understanding a person's health status, and, therefore, health care decision-making. This work discusses electrochemical biosensors for monitoring multiparametric biomarkers at different molecular levels and their potential to elucidate the health status of an individual in a personalized manner. In particular, and as an illustration, we discuss several aspects of the infection produced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a current health care concern worldwide. This includes SARS-CoV-2 structure, mechanism of infection, biomarkers, and electrochemical biosensors most commonly explored for diagnostics, prognostics, and potentially assessing the risk of complications in patients in the context of personalized medicine. Finally, some concluding remarks and perspectives hint at the use of electrochemical biosensors in the frame of other cutting-edge converging/emerging technologies toward the inauguration of a new paradigm of personalized medicine.

Polymer modification of SARS-CoV-2 spike protein impacts its ability to bind key receptor

The global spread of SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) has caused the loss of many human lives and severe economic losses. SARS-CoV-2 mediates its infection in humans via the spike glycoprotein. The receptor binding domain of the SARS-CoV-2 spike protein binds to its cognate receptor, angiotensin converting enzyme-2 (ACE2) to initiate viral entry. In this study, we examine how polymer modification of the spike protein receptor binding domain impacts binding to ACE2. The horseradish peroxidase conjugated receptor binding domain was modified with a range of polymers including hydrophilic N,N-dimethylacrylamide, hydrophobic N-isopropylacrylamide, cationic 3-(N,N-dimethylamino)propylacrylamide, and anionic 2-acrylamido-2-methylpropane sulfonic acid polymers. The effect of polymer chain length was observed using N,N-dimethylacrylamide polymers with degrees of polymerization of 5, 10 and 25. Polymer conjugation of the receptor binding domain significantly reduced the interaction with ACE2 protein, as determined by an enzyme-linked immunosorbent assay. Stability analysis showed that these conjugates remained highly stable even after seven days incubation at physiological temperature. Hence, this study provides a detailed view of the effect specific type of modification using a library of polymers with different functionalities in interrupting RBD-ACE2 interaction.

S Protein, ACE2 and Host Cell Proteases in SARS-CoV-2 Cell Entry and Infectivity; Is Soluble ACE2 a Two Blade Sword? A Narrative Review

Since the spread of the deadly virus SARS-CoV-2 in late 2019, researchers have restlessly sought to unravel how the virus enters the host cells. Some proteins on each side of the interaction between the virus and the host cells are involved as the major contributors to this process: (1) the nano-machine spike protein on behalf of the virus, (2) angiotensin converting enzyme II, the mono-carboxypeptidase and the key component of renin angiotensin system on behalf of the host cell, (3) some host proteases and proteins exploited by SARS-CoV-2. In this review, the complex process of SARS-CoV-2 entrance into the host cells with the contribution of the involved host proteins as well as the sequential conformational changes in the spike protein tending to increase the probability of complexification of the latter with angiotensin converting enzyme II, the receptor of the virus on the host cells, are discussed. Moreover, the release of the catalytic ectodomain of angiotensin converting enzyme II as its soluble form in the extracellular space and its positive or negative impact on the infectivity of the virus are considered.

The Development of Pharmacophore Models for the Search of New Natural Inhibitors of SARS-CoV-2 Spike RBD-ACE2 Binding Interface

To date, some succeeding variants of SARS-CoV-2 have become more contagious. This virus is known to enter human cells by binding the receptor-binding domain (RBD) of spike protein with the angiotensin-converting enzyme 2 (ACE2), the latter being a membrane protein that regulates the renin-angiotensin system. Since the host cell receptor plays a critical role in viral entry, inhibition of the RBD-ACE2 complex is a promising strategy for preventing COVID-19 infection. In the present communication, we propose and utilize an approach based on the generation of a complex of pharmacophore models and subsequent Induced Fit Docking (IFD) to identify potential inhibitors of the main binding sites of the Omicron SARS-CoV-2 RBD(S1)-ACE2 complex (PDB ID: 7T9L) among a number of natural products of various types and origins. Several natural compounds have been found to provide a high affinity for the receptor of interest. It is expected that the present results will stimulate further research aimed at the development of specialized drugs against this virus.

Electrostatic Interactions Are the Primary Determinant of the Binding Affinity of SARS-CoV-2 Spike RBD to ACE2: A Computational Case Study of Omicron Variants

To explore the mechanistic origin that determines the binding affinity of SARS-CoV-2 spike receptor binding domain (RBD) to human angiotensin converting enzyme 2 (ACE2), we constructed the homology models of RBD-ACE2 complexes of four Omicron subvariants (BA.1, BA.2, BA.3 and BA.4/5), and compared them with wild type complex (RBD_WT-ACE2) in terms of various structural dynamic properties by molecular dynamics (MD) simulations and binding free energy (BFE) calculations. The results of MD simulations suggest that the RBDs of all the Omicron subvariants (RBD_OMIs) feature increased global structural fluctuations when compared with RBD_WT. Detailed comparison of BFE components reveals that the enhanced electrostatic attractive interactions are the main determinant of the higher ACE2-binding affinity of RBD_OMIs than RBD_WT, while the weakened electrostatic attractive interactions determine RBD of BA.4/5 subvariant (RBD_BA.4/5) lowest ACE2-binding affinity among all Omicron subvariants. The per-residue BFE decompositions and the hydrogen bond (HB) networks analyses indicate that the enhanced electrostatic attractive interactions are mainly through gain/loss of the positively/negatively charged residues, and the formation or destruction of the interfacial HBs and salt bridges can also largely affect the ACE2-binding affinity of RBD. It is worth pointing out that since Q493R plays the most important positive contribution in enhancing binding affinity, the absence of this mutation in RBD_BA.4/5 results in a significantly weaker binding affinity to ACE2 than other Omicron subvariants. Our results provide insight into the role of electrostatic interactions in determining of the binding affinity of SARS-CoV-2 RBD to human ACE2.

ACE2 N-glycosylation modulates interactions with SARS-CoV-2 spike protein in a site-specific manner

SARS-CoV-2 has evolved continuously and accumulated spike mutations with each variant having a different binding for the cellular ACE2 receptor. It is not known whether the interactions between such mutated spikes and ACE2 glycans are conserved among different variant lineages. Here, we focused on three ACE2 glycosylation sites (53, 90 and 322) that are geometrically close to spike binding sites and investigated the effect of their glycosylation pattern on spike affinity. These glycosylation deletions caused distinct site-specific changes in interactions with the spike and acted cooperatively. Of note, the particular interaction profiles were conserved between the SARS-CoV-2 parental virus and the variants of concern (VOCs) Delta and Omicron. Our study provides insights for a better understanding of the importance of ACE2 glycosylation on ACE2/SARS-CoV-2 spike interaction and guidance for further optimization of soluble ACE2 for therapeutic use.

Longitudinal antibody titer, avidity, and neutralizing responses after SARS-CoV-2 infection

While waning immunity and SARS-CoV-2 variant immune escape continue to result in high infection rates worldwide, associations between longitudinal quantitative, qualitative, and functional humoral immune responses after SARS-CoV-2 infection remain unclear. In this study, we found significant waning of antibody against Spike S1 (R = -0.32, p = 0.035) and N protein (R = -0.39, p = 0.008), while RBD antibody moderately decreased (R = -0.19, p = 0.203). Likewise, neutralizing antibody titer (ND50) waned over time (R = -0.46, p = 0.001). In contrast, antibody avidity increased significantly over time for Spike S1 (R = 0.62, p = 6.0e-06), RBD (R = 0.54, p = 2.0e-04), and N (R = 0.33, p = 0.025) antibodies. Across all humoral responses, ND50 strongly associated with Spike S1 (R = 0.85, p = 2.7e-13) and RBD (R = 0.78, p = 2.9e-10) antibodies. Our findings provide longitudinal insight into humoral immune responses after infection and imply the potential of Spike S1/RBD antibody titer as surrogate correlates of protection.

Regional Association between Mean Air Temperature and Case Numbers of Multiple SARS-CoV-2 Lineages throughout the Pandemic

The association between mean air temperature and new SARS-CoV-2 case numbers throughout the ongoing coronavirus disease 2019 (COVID-19) pandemic was investigated to identify whether diverse SARS-CoV-2 lineages may exhibit diverse environmental behaviors. The number of new COVID-19 daily cases in the province of Verona was obtained from the Veneto Regional Healthcare Service, whilst the mean daily air temperature during the same period was retrieved from the Regional Agency for Ambient Prevention and Protection of Veneto. A significant inverse correlation was found between new COVID-19 daily cases and mean air temperature in Verona up to Omicron BA.1/BA.2 predominance (correlation coefficients between −0.79 and −0.41). The correlation then became positive when the Omicron BA.4/BA.5 lineages were prevalent (r = 0.32). When the median value (and interquartile range; IQR) of new COVID-19 daily cases recorded during the warmer period of the year in Verona (June–July) was compared across the three years of the pandemic, a gradual increase could be seen over time, from 1 (IQR, 0–2) in 2020, to 22 (IQR, 11–113) in 2021, up to 890 (IQR, 343–1345) in 2022. These results suggest that measures for preventing SARS-CoV-2 infection should not be completely abandoned during the warmer periods of the year.

All-Atom Simulations of Human ACE2-Spike Protein RBD Complexes for SARS-CoV-2 and Some of its Variants: Nature of Interactions and Free Energy Diagrams for Dissociation of the Protein Complexes

The spike protein of SARS-CoV-2 is known to interact with the human ACE2 protein via its receptor binding domain (RBD). We have investigated the molecular nature of this interprotein interaction and the associated free energy diagrams for the unbinding of the two proteins for SARS-CoV-2 and some of its known variants through all-atom simulations. The present work involves generation and analysis of 2.5 μs of unbiased and 4.2 μs of biased molecular dynamics trajectories in total for five explicitly solvated RBD-ACE2 systems at full atomic level. First, we have made a comparative analysis of the details of residue-wise specific interactions of the spike protein with ACE2 for SARS-CoV-1 and SARS-CoV-2. It is found that the average numbers of both direct interprotein and water-bridged hydrogen bonds between the RBD and ACE2 are higher for SARS-CoV-2 than SARS-CoV-1. These higher hydrogen bonded interactions are further aided by enhanced nonspecific electrostatic attractions between the two protein surfaces for SARS-CoV-2. The free energy calculations reveal that there is an increase in the free energy barrier by ∼1.5 kcal/mol for the unbinding of RBD from ACE2 for SARS-CoV-2 compared to that for SARS-CoV-1. Subsequently, we considered the RBDs of three variants of SARS-CoV-2, namely N501Y, E484Q/L452R, and N440K. The free energy barrier of protein unbinding for the N501Y variant is found to be ∼4 kcal/mol higher than the wild type SARS-CoV-2 which can be attributed to additional specific interactions involving Tyr501 of RBD and Lys353 and Tyr42 of ACE2 and also enhanced nonspecific electrostatic interaction between the protein surfaces. For the other two mutant variants of E484Q/L452R and N440K, the free energy barrier for protein unbinding increases by ∼2 and ∼1 kcal/mol, respectively, compared with the wild type SARS-CoV-2, which can be attributed to an increase in the number of interprotein hydrogen bonds for the former and also to enhanced positive electrostatic potential on the RBD surfaces for both of the variants. The successive breaking of interprotein hydrogen bonds along the free energy pathway of the unbinding process is also found out for all five systems studied here.

SARS-CoV-2 electrochemical immunosensor based on the spike-ACE2 complex

Rapid, straightforward, and massive diagnosis of coronavirus disease 2019 (COVID-19) is one of the more important measures to mitigate the current pandemics. This work reports on an immunosensor to rapidly detect the spike protein from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The immunosensing device entraps the spike protein linked to angiotensin-converting enzyme host receptor (ACE2) protein in a sandwich between carboxylated magnetic beads functionalized with an anti-spike antibody and an anti-ACE2 antibody, further labeled with streptavidin (poly)horseradish peroxidase (HRP) reporter enzyme. The particles were confined at the surface of screen-printed gold electrodes, whose signal resulting from the interaction of the enzyme with a mediator was recorded in a portable potentiostat. The immunosensor showed a sensitivity of 0.83 μA∗mL/μg and a limit of detection of 22.5 ng/mL of spike protein, with high reproducibility. As a proof-of-concept, it detected commercial spike protein-supplemented buffer solutions, pseudovirions, isolated viral particles and ten nasopharyngeal swab samples from infected patients compared to samples from three healthy individuals paving the way to detect the virus closer to the patient.

Mechanistic Origin of Different Binding Affinities of SARS-CoV and SARS-CoV-2 Spike RBDs to Human ACE2

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein (RBD_CoV2) has a higher binding affinity to the human receptor angiotensin-converting enzyme 2 (ACE2) than the SARS-CoV RBD (RBD_CoV). Here, we performed molecular dynamics (MD) simulations, binding free energy (BFE) calculations, and interface residue contact network (IRCN) analysis to explore the mechanistic origin of different ACE2-binding affinities of the two RBDs. The results demonstrate that, when compared to the RBD_CoV2-ACE2 complex, RBD_CoV-ACE2 features enhanced dynamicsand inter-protein positional movements and increased conformational entropy and conformational diversity. Although the inter-protein electrostatic attractive interactions are the primary determinant for the high ACE2-binding affinities of both RBDs, the significantly enhanced electrostatic attractive interactions between ACE2 and RBD_CoV2 determine the higher ACE2-binding affinity of RBD_CoV2 than of RBD_CoV. Comprehensive comparative analyses of the residue BFE components and IRCNs between the two complexes reveal that it is the residue changes at the RBD interface that lead to the overall stronger inter-protein electrostatic attractive force in RBD_CoV2-ACE2, which not only tightens the interface packing and suppresses the dynamics of RBD_CoV2-ACE2, but also enhances the ACE2-binding affinity of RBD_CoV2. Since the RBD residue changes involving gain/loss of the positively/negatively charged residues can greatly enhance the binding affinity, special attention should be paid to the SARS-CoV-2 variants carrying such mutations, particularly those near or at the binding interfaces with the potential to form hydrogen bonds and/or salt bridges with ACE2.

Structure-guided glyco-engineering of ACE2 for improved potency as soluble SARS-CoV-2 decoy receptor

Infection and viral entry of SARS-CoV-2 crucially depends on the binding of its Spike protein to angiotensin converting enzyme 2 (ACE2) presented on host cells. Glycosylation of both proteins is critical for this interaction. Recombinant soluble human ACE2 can neutralize SARS-CoV-2 and is currently undergoing clinical tests for the treatment of COVID-19. We used 3D structural models and molecular dynamics simulations to define the ACE2 N-glycans that critically influence Spike-ACE2 complex formation. Engineering of ACE2 N-glycosylation by site-directed mutagenesis or glycosidase treatment resulted in enhanced binding affinities and improved virus neutralization without notable deleterious effects on the structural stability and catalytic activity of the protein. Importantly, simultaneous removal of all accessible N-glycans from recombinant soluble human ACE2 yields a superior SARS-CoV-2 decoy receptor with promise as effective treatment for COVID-19 patients.

AI-driven prediction of SARS-CoV-2 variant binding trends from atomistic simulations

We present a novel technique to predict binding affinity trends between two molecules from atomistic molecular dynamics simulations. The technique uses a neural network algorithm applied to a series of images encoding the distance between two molecules in time. We demonstrate that our algorithm is capable of separating with high accuracy non-hydrophobic mutations with low binding affinity from those with high binding affinity. Moreover, we show high accuracy in prediction using a small subset of the simulation, therefore requiring a much shorter simulation time. We apply our algorithm to the binding between several variants of the SARS-CoV-2 spike protein and the human receptor ACE2.

Evaluation of Inhibitory Activity In Silico of In-House Thiomorpholine Compounds between the ACE2 Receptor and S1 Subunit of SARS-CoV-2 Spike

At the end of 2019, the world was struck by the COVID-19 pandemic, which resulted in dire repercussions of unimaginable proportions. From the beginning, the international scientific community employed several strategies to tackle the spread of this disease. Most notably, these consisted of the development of a COVID-19 vaccine and the discovery of antiviral agents through the repositioning of already known drugs with methods such as de novo design. Previously, methylthiomorphic compounds, designed by our group as antihypertensive agents, have been shown to display an affinity with the ACE2 (angiotensin converting enzyme) receptor, a key mechanism required for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) entry into target cells. Therefore, the objective of this work consists of evaluating, in silico, the inhibitory activity of these compounds between the ACE2 receptor and the S1 subunit of the SARS-CoV-2 spike protein. Supported by the advances of different research groups on the structure of the coronavirus spike and the interaction of the latter with its receptor, ACE2, we carried out a computational study that examined the effect of in-house designed compounds on the inhibition of said interaction. Our results indicate that the polyphenol LQM322 is one of the candidates that should be considered as a possible anti-COVID-19 agent.

Host variations in SARS-CoV-2 infection

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the zoonotic pathogen that causes the "Coronavirus Disease of 2019 (COVID-19)", and COVID-19 itself is yet to be thoroughly understood. Both the disease as well as the mechanisms by which the host interacts with the SARS-CoV-2 have not been fully enlightened. The epidemiological factors -e.g. age, sex, race-, the polymorphisms of the host proteins, the blood types and individual differences have all been in discussions about affecting the progression and the course of COVID-19 both individually and collectively, as their effects are mostly interwoven. We focused mainly on the effect of polymorphic variants of the host proteins that have been shown to take part in and/or affect the pathogenesis of COVID-19. Additionally, how the procedures of diagnosing and treating COVID-19 are affected by these variants and what possible changes can be implemented are the other questions, which are sought to be answered.

Anchor-Locker Binding Mechanism of the Coronavirus Spike Protein to Human ACE2: Insights from Computational Analysis

COVID-19 has emerged as the most serious international pandemic in early 2020 and the lack of comprehensive knowledge in the recognition and transmission mechanisms of this virus hinders the development of suitable therapeutic strategies. The specific recognition during the binding of the spike glycoprotein (S protein) of coronavirus to the angiotensin-converting enzyme 2 (ACE2) in the host cell is widely considered the first step of infection. However, detailed insights on the underlying mechanism of dynamic recognition and binding of these two proteins remain unknown. In this work, molecular dynamics simulation and binding free energy calculation were carried out to systematically compare and analyze the receptor-binding domain (RBD) of six coronavirus' S proteins. We found that affinity and stability of the RBD from SARS-CoV-2 under the binding state with ACE2 are stronger than those of other coronaviruses. The solvent-accessible surface area (SASA) and binding free energy of different RBD subunits indicate an "anchor-locker" recognition mechanism involved in the binding of the S protein to ACE2. Loop 2 (Y473-F490) acts as an anchor for ACE2 recognition, and Loop 3 (G496-V503) locks ACE2 at the other nonanchoring end. Then, the charged or long-chain residues in the β-sheet 1 (N450-F456) region reinforce this binding. The proposed binding mechanism was supported by umbrella sampling simulation of the dissociation process. The current computational study provides important theoretical insights for the development of new vaccines against SARS-CoV-2.

Metagenomic identification of a new sarbecovirus from horseshoe bats in Europe

The source of the COVID-19 pandemic is unknown, but the natural host of the progenitor sarbecovirus is thought to be Asian horseshoe (rhinolophid) bats. We identified and sequenced a novel sarbecovirus (RhGB01) from a British horseshoe bat, at the western extreme of the rhinolophid range. Our results extend both the geographic and species ranges of sarbecoviruses and suggest their presence throughout the horseshoe bat distribution. Within the spike protein receptor binding domain, but excluding the receptor binding motif, RhGB01 has a 77% (SARS-CoV-2) and 81% (SARS-CoV) amino acid homology. While apparently lacking hACE2 binding ability, and hence unlikely to be zoonotic without mutation, RhGB01 presents opportunity for SARS-CoV-2 and other sarbecovirus homologous recombination. Our findings highlight that the natural distribution of sarbecoviruses and opportunities for recombination through intermediate host co-infection are underestimated. Preventing transmission of SARS-CoV-2 to bats is critical with the current global mass vaccination campaign against this virus.

Identification of potential plant bioactive as SARS-CoV-2 Spike protein and human ACE2 fusion inhibitors

The Spike receptor binding domain (S-RBD) from SARS-CoV-2, a crucial protein for the entrance of the virus into target cells is known to cause infection by binding to a cell surface protein. Hence, reckoning therapeutics for the S-RBD of SARS-CoV-2 may address a significant way to target viral entry into the host cells. Herein, through in-silico approaches (Molecular docking, molecular dynamics (MD) simulations, and end-state thermodynamics), we aimed to screen natural molecules from different plants for their ability to inhibit S-RBD of SARS-CoV-2. We prioritized the best interacting molecules (Diacetylcurcumin and Dicaffeoylquinic acid) by analysis of protein-ligand interactions and subjected them for long-term MD simulations. We found that Dicaffeoylquinic acid interacted prominently with essential residues (Lys417, Gln493, Tyr489, Phe456, Tyr473, and Glu484) of S-RBD. These residues are involved in interactions between S-RBD and ACE2 and could inhibit the viral entry into the host cells. The in-silico analyses indicated that Dicaffeoylquinic acid and Diacetylcurcumin might have the potential to act as inhibitors of SARS-CoV-2 S-RBD. The present study warrants further in-vitro and in-vivo studies of Dicaffeoylquinic acid and Diacetylcurcumin for validation and acceptance of their inhibitory potential against S-RBD of SARS-CoV-2.

ACE2 glycans preferentially interact with SARS-CoV-2 over SARS-CoV

We report a distinct difference in the interactions of the glycans of the host-cell receptor, ACE2, with SARS-CoV-2 and SARS-CoV S-protein receptor-binding domains (RBDs). Our analysis demonstrates that the ACE2 glycan at N322 enhances interactions with the SARS-CoV-2 RBD while the ACE2 glycan at N90 may offer protection against infections of both coronaviruses depending on its composition. The interactions of the ACE2 glycan at N322 with SARS-CoV RBD are blocked by the presence of the RBD glycan at N357 of the SARS-CoV RBD. The absence of this glycosylation site on SARS-CoV-2 RBD may enhance its binding with ACE2.

Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2

SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD-ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.