Elucidating Interactions Between SARS-CoV-2 Trimeric Spike Protein and ACE2 Using Homology Modeling and Molecular Dynamics Simulations

Lectins in oncology and virology: Mechanisms of anticancer activity and SARS-CoV-2 inhibition

Lectins are proteins or glycoproteins of non-immune origin with carbohydrate-binding properties. They are found both prokaryotic and eukaryotic organisms. The most abundant source of the lectins are plants. Many lectins have anticancer effects by directly exerting cytotoxic effects on malignant cells or indirectly activating the immune system. Lectins also have antiviral activities. These proteins can recognise glycoproteins on the surface of enveloped viruses and bind to them. This creates a physical barrier between them and the corresponding receptors on the surface of the host cell, which prevents the virus from entering the cell and can thus effectively inhibit the replication of the virus. In this review, we focus on the anticancer activities of selected lectins and the underlying mechanisms. We also discuss different types of lectins with antiviral activity. We have paid special attention to lectins with inhibitory activity against SARS-CoV-2. Finally, we outline the challenges of using lectins in therapy and suggest future research directions.

Examining sialic acid derivatives as potential inhibitors of SARS-CoV-2 spike protein receptor binding domain

Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) has been the primary reason behind the COVID-19 global pandemic which has affected millions of lives worldwide. The fundamental cause of the infection is the molecular binding of the viral spike protein receptor binding domain (SP-RBD) with the human cell angiotensin-converting enzyme 2 (ACE2) receptor. The infection can be prevented if the binding of RBD-ACE2 is resisted by utilizing certain inhibitors or drugs that demonstrate strong binding affinity towards the SP RBD. Sialic acid based glycans found widely in human cells and tissues have notable propensity of binding to viral proteins of the coronaviridae family. Recent experimental literature have used N-acetyl neuraminic acid (Sialic acid) to create diagnostic sensors for SARS-CoV-2, but a detailed interrogation of the underlying molecular mechanisms is warranted. Here, we perform all atom molecular dynamics (MD) simulations for the complexes of certain Sialic acid-based molecules with that of SP RBD of SARS CoV-2. Our results indicate that Sialic acid not only reproduces a binding affinity comparable to the RBD-ACE2 interactions, it also assumes the longest time to dissociate completely from the protein binding pocket of SP RBD. Our predictions corroborate that a combination of electrostatic and van der Waals energies as well the polar hydrogen bond interactions between the RBD residues and the inhibitors influence free energy of binding.Communicated by Ramaswamy H. Sarma.

Decoding the κ Opioid Receptor (KOR): Advancements in Structural Understanding and Implications for Opioid Analgesic Development

The opioid crisis in the United States is a significant public health issue, with a nearly threefold increase in opioid-related fatalities between 1999 and 2014. In response to this crisis, society has made numerous efforts to mitigate its impact. Recent advancements in understanding the structural intricacies of the κ opioid receptor (KOR) have improved our knowledge of how opioids interact with their receptors, triggering downstream signaling pathways that lead to pain relief. This review concentrates on the KOR, offering crucial structural insights into the binding mechanisms of both agonists and antagonists to the receptor. Through comparative analysis of the atomic details of the binding site, distinct interactions specific to agonists and antagonists have been identified. These insights not only enhance our understanding of ligand binding mechanisms but also shed light on potential pathways for developing new opioid analgesics with an improved risk-benefit profile.

Cooperative and structural relationships of the trimeric Spike with infectivity and antibody escape of the strains Delta (B.1.617.2) and Omicron (BA.2, BA.5, and BQ.1)

Herein, we conducted simulations of trimeric Spike from several SARS-CoV-2 variants of concern (Delta and Omicron sub-variants BA.2, BA.5, and BQ.1) and investigated the mechanisms by which specific mutations confer resistance to neutralizing antibodies. We observed that the mutations primarily affect the cooperation between protein domains within and between protomers. The substitutions K417N and L452R expand hydrogen bonding interactions, reducing their interaction with neutralizing antibodies. By interacting with nearby residues, the K444T and N460K mutations in the SpikeBQ.1 variant potentially reduces solvent exposure, thereby promoting resistance to antibodies. We also examined the impact of D614G, P681R, and P681H substitutions on Spike protein structure that may be related to infectivity. The D614G substitution influences communication between a glycine residue and neighboring domains, affecting the transition between up- and -down RBD states. The P681R mutation, found in the Delta variant, enhances correlations between protein subunits, while the P681H mutation in Omicron sub-variants weakens long-range interactions that may be associated with reduced fusogenicity. Using a multiple linear regression model, we established a connection between inter-protomer communication and loss of sensitivity to neutralizing antibodies. Our findings underscore the importance of structural communication between protein domains and provide insights into potential mechanisms of immune evasion by SARS-CoV-2. Overall, this study deepens our understanding of how specific mutations impact SARS-CoV-2 infectivity and shed light on how the virus evades the immune system.

Low-Entropy Hydration Shells at the Spike RBD's Binding Site May Reveal the Contagiousness of SARS-CoV-2 Variants

The infectivity of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is primarily determined by the binding affinity between the receptor-binding domain (RBD) of the spike protein and the angiotensin-converting enzyme 2 (ACE2) receptor. Here, through screening off pseudo hydrophilic groups on protein surfaces, the distribution of low-entropy regions on hydration shells of the ACE2 receptor and the RBDs of multiple SARS-CoV-2 variants was demonstrated. Shape matching between the low-entropy hydration shells of multiple SARS-CoV-2 variants and the ACE2 receptor has been identified as a mechanism that drives hydrophobic attraction between the RBDs and the ACE2 receptor, which estimates the binding affinity. Low-entropy regions of the hydration shells, which play important roles in determining the binding of other viruses and their receptors, are demonstrated. The RBD-ACE2 binding is thus found to be guided by hydrophobic collapse between the shape-matched low-entropy regions of the hydration shells of the proteins. A measure of the low-entropy status of the hydration shells can be estimated by calculating genuine hydrophilic groups within the binding sites. An important indicator of the contagiousness of SARS-CoV-2 variants is the low-entropy level of its hydration shells at the spike protein binding site.

Molecular dynamics simulations of the spike trimeric ectodomain of the SARS-CoV-2 Omicron variant: structural relationships with infectivity, evasion to immune system and transmissibility

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron is currently the most prevalent SARS-CoV-2 variant worldwide. Herein, we calculated molecular dynamics simulations of the trimeric spikeWT and SpikeBA.1 for 300 ns. Our results show that SpikeBA.1 has more conformational flexibility than SpikeWT. Our principal component analysis (PCA) allowed us to observe a broader spectrum of different conformations for SpikeBA.1, mainly at N-terminal domain (NTD) and receptor-binding domain (RBD). Such increased flexibility could contribute to decreased neutralizing antibody recognition of this variant. Our molecular dynamics data show that the RBDBA.1 easily visits an up-conformational state and the prevalent D614G mutation is pivotal to explain molecular dynamics results for this variant because to lost hydrogen bonding interactions between the residue pairs K854SC/D614SC, Y837MC/D614MC, K835SC/D614SC, T859SC/D614SC. In addition, SpikeBA.1 residues near the furin cleavage site are more flexible than in SpikeWT, probably due to P681H and D614G substitutions. Finally, dynamical cross-correlation matrix (DCCM) analysis reveals that D614G and P681H may allosterically affect the cleavage site S1/S2. Conversely, S2' site may be influenced by residues located between NTD and RBD of a neighboring protomer of the SpikeWT. Such communication may be lost in SpikeBA.1, explaining the changes of the cell tropism in the viral infection. In addition, the movements of the NTDWT and NTDBA.1 may modulate the RBD conformation through allosteric effects. Taken together, our results explain how the structural aspects may explain the observed gains in infectivity, immune system evasion and transmissibility of the Omicron variant.Communicated by Ramaswamy H. Sarma.

Three-Dimensional Structural Insights Have Revealed the Distinct Binding Interactions of Agonists, Partial Agonists, and Antagonists with the µ Opioid Receptor

The United States is experiencing the most profound and devastating opioid crisis in history, with the number of deaths involving opioids, including prescription and illegal opioids, continuing to climb over the past two decades. This severe public health issue is difficult to combat as opioids remain a crucial treatment for pain, and at the same time, they are also highly addictive. Opioids act on the opioid receptor, which in turn activates its downstream signaling pathway that eventually leads to an analgesic effect. Among the four types of opioid receptors, the µ subtype is primarily responsible for the analgesic cascade. This review describes available 3D structures of the µ opioid receptor in the protein data bank and provides structural insights for the binding of agonists and antagonists to the receptor. Comparative analysis on the atomic details of the binding site in these structures was conducted and distinct binding interactions for agonists, partial agonists, and antagonists were observed. The findings in this article deepen our understanding of the ligand binding activity and shed some light on the development of novel opioid analgesics which may improve the risk benefit balance of existing opioids.

Thermodynamic analysis of the interactions between human ACE2 and spike RBD of Betacoronaviruses (SARS-CoV-1 and SARS-CoV-2)

There are many scientific reports on the interaction of the SARS-CoV-2 virus S protein (and its RBD) with the human ACE2 receptor protein. However, there are no reliable data on how this interaction differs from the interaction of the receptor binding domain of SARS-CoV-1 with ACE2, in terms of binding strength and changes in reaction enthalpy and entropy. Our studies have revealed these differences and the impact of zinc ions on this interaction. Intriguingly, the binding affinity of both RBDs (of SARS-CoV-1 and of SARS-CoV-2) to the ACE2 receptor protein is almost identical; however, there are some differences in the entropic and enthalpic contributions to these interactions.

Structural Analysis of the Spike Protein of SARS-CoV-2 Variants and Other Betacoronaviruses Using Molecular Dynamics

A structural analysis over various spike proteins from three highly pathogenic Betacoronavirus was done to understand their structural differences. The proteins were modeled using crystal structures from SARS-CoV, MERS-CoV, and other Betacoronavirus that infect bats and pangolins. The group was split in two sets; the first set corresponds to the non-mutated spike proteins, while the second set corresponds to mutated spike variants alpha, beta, gamma, delta, omicron and mu; five of them classified as variants of concern and the last one as variant of interest. A conformational space exploration was carried out for every protein by using molecular dynamic simulations. Root mean square fluctuations, principal component and cross-correlation analysis were carried out over the dynamics to analyze the flexibility and rigidity of every protein in comparison to the wild type Spike protein from the SARS-CoV-2. The obtained results indicate that the proteins, which are not spread among humans, have smooth movements compared to those of SARS-CoV-2 and its variants. In addition, a relationship between the speed of the virulence and the movement of the protein can explain the behavior of delta and omicron variants.

Deep Learning Models for Predicting Gas Adsorption Capacity of Nanomaterials

Metal-organic frameworks (MOFs), a class of porous nanomaterials, have been widely used in gas adsorption-based applications due to their high porosities and chemical tunability. To facilitate the discovery of high-performance MOFs for different applications, a variety of machine learning models have been developed to predict the gas adsorption capacities of MOFs. Most of the predictive models are developed using traditional machine learning algorithms. However, the continuously increasing sizes of MOF datasets and the complicated relationships between MOFs and their gas adsorption capacities make deep learning a suitable candidate to handle such big data with increased computational power and accuracy. In this study, we developed models for predicting gas adsorption capacities of MOFs using two deep learning algorithms, multilayer perceptron (MLP) and long short-term memory (LSTM) networks, with a hypothetical set of about 130,000 structures of MOFs with methane and carbon dioxide adsorption data at different pressures. The models were evaluated using 10 iterations of 10-fold cross validations and 100 holdout validations. The MLP and LSTM models performed similarly with high prediction accuracy. The models for predicting gas adsorption at a higher pressure outperformed the models for predicting gas adsorption at a lower pressure. The deep learning models are more accurate than the random forest models reported in the literature, especially for predicting gas adsorption capacities at low pressures. Our results demonstrated that deep learning algorithms have a great potential to generate models that can accurately predict the gas adsorption capacities of MOFs.

Computational investigation of the increased virulence and pathogenesis of SARS-CoV-2 lineage B.1.1.7

New variants of SARS-CoV-2 are being reported worldwide. The World Health Organization has reported Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2) and Omicron (B.1.1.529) as the variants of concern. There are speculations that the variants might evade the host immune responses induced by currently available vaccines and develop resistance to drugs under consideration. The first step of viral infection in COVID-19 occurs through the interaction of the spike protein's receptor-binding domain (RBD) with the peptidase domain of the human ACE-2 (hACE-2) receptor. This study aims to get a molecular-level understanding of the mechanism behind the increased infection rate in the alpha variant. We have computationally studied the spike protein interaction in both the wild-type and B.1.1.7 variant with the hACE-2 receptor using molecular dynamics and MM-GBSA based binding free energy calculations. The binding free energy difference shows that the mutant variant of the spike protein has increased binding affinity for the hACE-2 receptor (i.e. ΔG(N501Y,A570D) is in the range -7.2 to -7.6 kcal mol^-1) and the results were validated using Density functional theory. We demonstrate that with the use of state-of-the-art computational approaches, we can, in advance, predict the virulent nature of variants of SARS-CoV-2 and alert the world healthcare system.

Severe Acute Respiratory Syndrome Coronavirus 2 Variants of Concern: A Perspective for Emerging More Transmissible and Vaccine-Resistant Strains

Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC) are constantly threatening global public health. With no end date, the pandemic persists with the emergence of novel variants that threaten the effectiveness of diagnostic tests and vaccines. Mutations in the Spike surface protein of the virus are regularly observed in the new variants, potentializing the emergence of novel viruses with different tropism from the current ones, which may change the severity and symptoms of the disease. Growing evidence has shown that mutations are being selected in favor of variants that are more capable of evading the action of neutralizing antibodies. In this context, the most important factor guiding the evolution of SARS-CoV-2 is its interaction with the host's immune system. Thus, as current vaccines cannot block the transmission of the virus, measures complementary to vaccination, such as the use of masks, hand hygiene, and keeping environments ventilated remain essential to delay the emergence of new variants. Importantly, in addition to the involvement of the immune system in the evolution of the virus, we highlight several chemical parameters that influence the molecular interactions between viruses and host cells during invasion and are also critical tools making novel variants more transmissible. In this review, we dissect the impacts of the Spike mutations on biological parameters such as (1) the increase in Spike binding affinity to hACE2; (2) bound time for the receptor to be cleaved by the proteases; (3) how mutations associate with the increase in RBD up-conformation state in the Spike ectodomain; (4) expansion of uncleaved Spike protein in the virion particles; (5) increment in Spike concentration per virion particles; and (6) evasion of the immune system. These factors play key roles in the fast spreading of SARS-CoV-2 variants of concern, including the Omicron.

Cold atmospheric pressure plasma for attenuation of SARS-CoV-2 spike protein binding to ACE2 protein and the RNA deactivation

Cold atmospheric pressure (CAP) plasma has a profound effect on protein-protein interactions. In this work, we have highlighted the deactivation of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spike protein by CAP plasma treatment. Complete deactivation of spike protein binding to the human ACE2 protein was observed within an exposure time of 5 minutes which is correlated to the higher concentration of hydrogen peroxide formation due to the interaction with the reactive oxygen species present in the plasma. On the other hand, we have established that CAP plasma is also capable of degrading RNA of SARS-CoV-2 virus which is also linked to hydrogen peroxide concentration. The reactive oxygen species is produced in the plasma by using noble gases such as helium, in the absence of any other chemicals. Therefore, it is a green process with no chemical waste generated and highly advantageous from the environmental safety prospects. Results of this work could be useful in designing plasma-based disinfection systems over those based on environmentally hazardous chemical-based disinfection and biomedical applications.

Systems analysis shows that thermodynamic physiological and pharmacological fundamentals drive COVID-19 and response to treatment

Why a systems analysis view of this pandemic? The current pandemic has inflicted almost unimaginable grief, sorrow, loss, and terror at a global scale. One of the great ironies with the COVID‐19 pandemic, particularly early on, is counter intuitive. The speed at which specialized basic and clinical sciences described the details of the damage to humans in COVID‐19 disease has been impressive. Equally, the development of vaccines in an amazingly short time interval has been extraordinary. However, what has been less well understood has been the fundamental elements that underpin the progression of COVID‐19 in an individual and in populations. We have used systems analysis approaches with human physiology and pharmacology to explore the fundamental underpinnings of COVID‐19 disease. Pharmacology powerfully captures the thermodynamic characteristics of molecular binding with an exogenous entity such as a virus and its consequences on the living processes well described by human physiology. Thus, we have documented the passage of SARS‐CoV‐2 from infection of a single cell to species jump, to tropism, variant emergence and widespread population infection. During the course of this review, the recurrent observation was the efficiency and simplicity of one critical function of this virus. The lethality of SARS‐CoV‐2 is due primarily to its ability to possess and use a variable surface for binding to a specific human target with high affinity. This binding liberates Gibbs free energy (GFE) such that it satisfies the criteria for thermodynamic spontaneity. Its binding is the prelude to human host cellular entry and replication by the appropriation of host cell constituent molecules that have been produced with a prior energy investment by the host cell. It is also a binding that permits viral tropism to lead to high levels of distribution across populations with newly formed virions. This thermodynamic spontaneity is repeated endlessly as infection of a single host cell spreads to bystander cells, to tissues, to humans in close proximity and then to global populations. The principal antagonism of this process comes from SARS‐CoV‐2 itself, with its relentless changing of its viral surface configuration, associated with the inevitable emergence of variants better configured to resist immune sequestration and importantly with a greater affinity for the host target and higher infectivity. The great value of this physiological and pharmacological perspective is that it reveals the fundamental thermodynamic underpinnings of SARS‐CoV‐2 infection.

Molecular modeling of the interaction of ligands with ACE2-SARS-CoV-2 spike protein complex

COVID-19 is a new communicable disease with a widespread outbreak that affects all populations worldwide triggering a rush of scientific interest in coronavirus research globally. In silico molecular docking experiment was utilized to determine interactions of available compounds with SARS-CoV-2 and angiotensin-converting enzyme 2 (ACE2) complex. Chimera and AutoDock Vina were used for protein-ligand interaction structural analysis. Ligands were chosen based on the known characteristics and indications of the drugs as ACE inhibitors (captopril, enalapril, quinapril, moexipril, benazepril, ramipril, perindopril, zofenopril, fosinopril), as ACE2 blockers (losartan, olmesartan), as blood thinning agent (clopidogrel), as cholesterol-lowering prescriptions (simvastatin, atorvastatin), repurposed medications (dexamethasone, hydroxychloroquine, chloroquine), and as investigational drug (remdesivir). Experimental ACE/ACE2 inhibitors are also included: Sigma ACEI, N-(2-aminoethyl)-1-aziridine-ethanamine (NAAE), nicotianamine (NAM), and MLN-4760 (ACE2 inhibitor). The best docked conformations were all located in the ACE2 protein, 50% docked at the interface with lower scores and only clopidogrel and hydroxychloroquine docked at the spike protein. Captopril, moexipril, benazepril, fosinopril, losartan, remdesivir, Sigma ACEI, NAA, and NAM interacted and docked at the interface of ACE2 and SARS-CoV-2 spike protein complex. This may have significant implication in enhancing our understanding of the mechanism to hinder viral entry into the host organism during infection.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40203-021-00114-w.

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.

Understanding the molecular interaction of SARS-CoV-2 spike mutants with ACE2 (angiotensin converting enzyme 2)

Covid-19 is a viral disease caused by the virus SARS-CoV-2 that spread worldwide and caused more than 4.3 million deaths. Moreover, SARS-CoV-2 still continues to evolve, and specifically the E484K, N501Y, and South Africa triple (K417N + E484K + N501Y) spike protein mutants remain as the 'escape' phenotypes. The aim of this study was to compare the interaction between the receptor binding domain (RBD) of the E484K, N501Y and South Africa triple spike variants and ACE2 with the interaction between wild-type spike RBD-ACE2 and to show whether the obtained binding affinities and conformations corraborate clinical findings. The structures of the RBDs of the E484K, N501Y and South Africa triple variants were generated with DS Studio v16 and energetically minimized using the CHARMM22 force field. Protein-protein dockings were performed in the HADDOCK server and the obtained wild-type and mutant spike-ACE2 complexes were submitted to 200-ns molecular dynamics simulations with subsequent free energy calculations using GROMACS. Based on docking binding affinities and free energy calculations the E484K, N501Y and triple mutant variants were found to interact stronger with the ACE2 than the wild-type spike. Interestingly, molecular dynamics and MM-PBSA results showed that E484K and spike triple mutant complexes were more stable than the N501Y one. Moreover, the E484K and South Africa triple mutants triggered greater conformational changes in the spike glycoprotein than N501Y. The E484K variant alone, or the combination of K417N + E484K + N501Y mutations induce significant conformational transitions in the spike glycoprotein, while increasing the spike-ACE2 binding affinity.Communicated by Ramaswamy H. Sarma.

Recent Developments in Free Energy Calculations for Drug Discovery

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

Structural Decoding of a Small Molecular Inhibitor on the Binding of SARS-CoV-2 to the ACE 2 Receptor

Inhibition of the interaction of the receptor-binding domain (RBD) of the spike protein and the human angiotensin-converting enzyme 2 (ACE 2) receptor is the most effective therapeutic formulation to restrict the contagious respiratory illness and multiple organ failure caused by the novel SARS-CoV-2 virus. Based on the structural decoding of the RBD of the spike protein, here we have generated a new set of small molecules that have strong inhibiting properties on the binding of the spike protein to ACE 2 receptors. These small-molecule inhibitors surprisingly show binding to the main protease, nucleoprotein, and RNA-dependent RNA polymerase, which are the other responsible factors for the viral infection. The newly designed molecules show better performance than several existing repurposed drugs. Conformational changes from closed to closed lock and open conformations of the SARS-CoV-2 binding to the ACE 2 receptor were observed in the presence of these small molecular inhibitors, suggesting their strong abilities to counteract the SARS-CoV-2 infection.

In Silico, In Vitro and In Cellulo Models for Monitoring SARS-CoV-2 Spike/Human ACE2 Complex, Viral Entry and Cell Fusion

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent responsible for the recent coronavirus disease 2019 (COVID-19) pandemic. Productive SARS-CoV-2 infection relies on viral entry into cells expressing angiotensin-converting enzyme 2 (ACE2). Indeed, viral entry into cells is mostly mediated by the early interaction between the viral spike protein S and its ACE2 receptor. The S/ACE2 complex is, thus, the first contact point between the incoming virus and its cellular target; consequently, it has been considered an attractive therapeutic target. To further characterize this interaction and the cellular processes engaged in the entry step of the virus, we set up various in silico, in vitro and in cellulo approaches that allowed us to specifically monitor the S/ACE2 association. We report here a computational model of the SARS-CoV-2 S/ACE2 complex, as well as its biochemical and biophysical monitoring using pulldown, AlphaLISA and biolayer interferometry (BLI) binding assays. This led us to determine the kinetic parameters of the S/ACE2 association and dissociation steps. In parallel to these in vitro approaches, we developed in cellulo transduction assays using SARS-CoV-2 pseudotyped lentiviral vectors and HEK293T-ACE2 cell lines generated in-house. This allowed us to recapitulate the early replication stage of the infection mediated by the S/ACE2 interaction and to detect cell fusion induced by the interaction. Finally, a cell imaging system was set up to directly monitor the S/ACE2 interaction in a cellular context and a flow cytometry assay was developed to quantify this association at the cell surface. Together, these different approaches are available for both basic and clinical research, aiming to characterize the entry step of the original SARS-CoV-2 strain and its variants as well as to investigate the possible chemical modulation of this interaction. All these models will help in identifying new antiviral agents and new chemical tools for dissecting the virus entry step.