Supervised molecular dynamics for exploring the druggability of the SARS-CoV-2 spike protein

Diverse bioactive secondary metabolites from Aspergillus terreus: antimicrobial, anticancer, and anti-SARS-CoV-2 activity studies

Owing to its high interest as prolific source of diverse bioactive compounds referred in our previous research work, we have scaled-up the fermentation of the marine Aspergillus terreus LGO13 on a liquid culture medium to isolate and identify the very minor/further promising bioactive secondary metabolites and to study their antibacterial, cytotoxic, and antiviral properties. Twenty-three known bioactive metabolites, including the recently discovered microbial natural product N-benzoyl-tryptophan (1), were obtained herein. Their structures were determined using HR-ESI-MS 1D/2D NMR spectroscopy and data from the literature. The biological properties of the microbial extract and the resulting compounds were examined using a set of microorganisms, cervix carcinoma KB-3-1, nonsmall cell lung cancer (NSCLC) A549, and coronavirus (SARS-CoV-2), respectively. Molecular docking (MD) simulations were used to investigate the potential targets of the separated metabolites as anti-SARS-CoV-2 drugs. According to the current study, a viral protein that may be the target of anticovid drugs is a papain-like protease (PLpro), and chaetominine (2) appears to be a viable choice against this protein. We evaluated the antiviral efficacy of chaetominine (2), fumitremorgin C (6), and azaspirofuran A (9) against SARS-CoV-2 based on MD data. Chaetominine (2) and azaspirofuran A (9) displayed intermediate selectivity indices (SI = 6.6 and 3.2, respectively), while fumitremorgin C (6) displayed a high selectivity index (SI = 19.77). These findings show that fumitremorgin C has promising antiviral action against SARS-CoV-2.

The Recognition Pathway of the SARS-CoV-2 Spike Receptor-Binding Domain to Human Angiotensin-Converting Enzyme 2

COVID-19 caused by SARS-CoV-2 has spread around the world. The receptor-binding domain (RBD) of the spike protein of SARS-CoV-2 is a critical component that directly interacts with host ACE2. Here, we simulate the ACE2 recognition processes of RBD of the WT, Delta, and OmicronBA.2 variants using our recently developed supervised Gaussian accelerated molecular dynamics (Su-GaMD) approach. We show that RBD recognizes ACE2 through three contact regions (regions I, II, and III), which aligns well with the anchor-locker mechanism. The higher binding free energy in State d of the RBDOmicronBA.2-ACE2 system correlates well with the increased infectivity of OmicronBA.2 in comparison with other variants. For RBDDelta, the T478K mutation affects the first step of recognition, while the L452R mutation, through its nearby Y449, affects the RBDDelta-ACE2 binding in the last step of recognition. For RBDOmicronBA.2, the E484A mutation affects the first step of recognition, the Q493R, N501Y, and Y505H mutations affect the binding free energy in the last step of recognition, mutations in the contact regions affect the recognition directly, and other mutations indirectly affect recognition through dynamic correlations with the contact regions. These results provide theoretical insights for RBD-ACE2 recognition and may facilitate drug design against SARS-CoV-2.

Comparative Study of the Mutations Observed in the SARS-CoV-2 RBD Variants of Concern and Their Impact on the Interaction with the ACE2 Protein

SARS-CoV-2 strains have made an appearance across the globe, causing over 757 million cases and over 6.85 million deaths at the time of writing. The emergence of these variants shows the amplitude of genetic variation to which the wild-type strains have been subjected. The rise of the different SARS-CoV-2 variants resulting from such genetic modification has significantly affected COVD-19's major impact on proliferation, virulence, and clinics. With the emergence of the variants of concern, the spike protein has been identified as a possible therapeutic target due to its critical role in binding to human cells and pathogenesis. These mutations could be linked to functional heterogeneity and use a different infection strategy. For example, the Omicron variant's multiple mutations should be carefully examined, as they represent one of the most widely spread strains and hint to us that there may be more genetic changes in the virus. As a result, we applied a common protocol where we reconstructed SARS-CoV-2 variants of concern and performed molecular dynamics simulations to study the stability of the ACE2-RBD complex in each variant. We also carried out free energy calculations to compare the binding and biophysical properties of the different SARS-CoV-2 variants when they interact with ACE2. Therefore, we were able to obtain consistent results and uncover new crucial residues that were essential for preserving a balance between maintaining a high affinity for ACE2 and the capacity to evade RBD-targeted antibodies. Our detailed structural analysis showed that SARS-CoV-2 variants of concern show a higher affinity for ACE2 compared to the Wuhan strain. Additionally, residues K417N and E484K/A might play a crucial role in antibody evasion, whereas Q498R and N501Y are specifically mutated to strengthen RBD affinity to ACE2 and, thereby, increase the viral effect of the COVID-19 virus.

Multi-structural molecular docking (MOD) combined with molecular dynamics reveal the structural requirements of designing broad-spectrum inhibitors of SARS-CoV-2 entry to host cells

New variants of SARS-CoV-2 that can escape immune response continue to emerge. Consequently, there is an urgent demand to design small molecule therapeutics inhibiting viral entry to host cells to reduce infectivity rate. Despite numerous in silico and in situ studies, the structural requirement of designing viral-entry inhibitors effective against multiple variants of SARS-CoV-2 has yet to be described. Here we systematically screened the binding of various natural products (NPs) to six different SARS-CoV-2 receptor-binding domain (RBD) structures. We demonstrate that Multi-structural Molecular Docking (MOD) combined with molecular dynamics calculations allowed us to predict a vulnerable site of RBD and the structural requirement of ligands binding to this vulnerable site. We expect that our findings lay the foundation for in silico screening and identification of lead molecules to guide drug discovery into designing new broad-spectrum lead molecules to counter the threat of future variants of SARS-CoV-2.

An In Silico Design of Peptides Targeting the S1/S2 Cleavage Site of the SARS-CoV-2 Spike Protein

SARS-CoV-2, responsible for the COVID-19 pandemic, invades host cells via its spike protein, which includes critical binding regions, such as the receptor-binding domain (RBD), the S1/S2 cleavage site, the S2 cleavage site, and heptad-repeat (HR) sections. Peptides targeting the RBD and HR1 inhibit binding to host ACE2 receptors and the formation of the fusion core. Other peptides target proteases, such as TMPRSS2 and cathepsin L, to prevent the cleavage of the S protein. However, research has largely ignored peptides targeting the S1/S2 cleavage site. In this study, bioinformatics was used to investigate the binding of the S1/S2 cleavage site to host proteases, including furin, trypsin, TMPRSS2, matriptase, cathepsin B, and cathepsin L. Peptides targeting the S1/S2 site were designed by identifying binding residues. Peptides were docked to the S1/S2 site using HADDOCK (High-Ambiguity-Driven protein-protein DOCKing). Nine peptides with the lowest HADDOCK scores and strong binding affinities were selected, which was followed by molecular dynamics simulations (MDSs) for further investigation. Among these peptides, BR582 and BR599 stand out. They exhibited relatively high interaction energies with the S protein at -1004.769 ± 21.2 kJ/mol and -1040.334 ± 24.1 kJ/mol, respectively. It is noteworthy that the binding of these peptides to the S protein remained stable during the MDSs. In conclusion, this research highlights the potential of peptides targeting the S1/S2 cleavage site as a means to prevent SARS-CoV-2 from entering cells, and contributes to the development of therapeutic interventions against COVID-19.

A Computational Pipeline to Identify and Characterize Binding Sites and Interacting Chemotypes in SARS-CoV-2

Minimizing the human and economic costs of the COVID-19 pandemic and future pandemics requires the ability to develop and deploy effective treatments for novel pathogens as soon as possible after they emerge. To this end, we introduce a new computational pipeline for the rapid identification and characterization of binding sites in viral proteins along with the key chemical features, which we call chemotypes, of the compounds predicted to interact with those same sites. The composition of source organisms for the structural models associated with an individual binding site is used to assess the site's degree of structural conservation across different species, including other viruses and humans. We propose a search strategy for novel therapeutics that involves the selection of molecules preferentially containing the most structurally rich chemotypes identified by our algorithm. While we demonstrate the pipeline on SARS-CoV-2, it is generalizable to any new virus, as long as either experimentally solved structures for its proteins are available or sufficiently accurate predicted structures can be constructed.

Molecular Modeling of Viral Type I Fusion Proteins: Inhibitors of Influenza Virus Hemagglutinin and the Spike Protein of Coronavirus

The fusion of viral and cell membranes is one of the basic processes in the life cycles of viruses. A number of enveloped viruses confer fusion of the viral envelope and the cell membrane using surface viral fusion proteins. Their conformational rearrangements lead to the unification of lipid bilayers of cell membranes and viral envelopes and the formation of fusion pores through which the viral genome enters the cytoplasm of the cell. A deep understanding of all the stages of conformational transitions preceding the fusion of viral and cell membranes is necessary for the development of specific inhibitors of viral reproduction. This review systematizes knowledge about the results of molecular modeling aimed at finding and explaining the mechanisms of antiviral activity of entry inhibitors. The first section of this review describes types of viral fusion proteins and is followed by a comparison of the structural features of class I fusion proteins, namely influenza virus hemagglutinin and the S-protein of the human coronavirus.

Triterpene Derivatives as Potential Inhibitors of the RBD Spike Protein from SARS-CoV-2: An In Silico Approach

The appearance of a new coronavirus, SARS-CoV-2, in 2019 kicked off an international public health emergency. Although rapid progress in vaccination has reduced the number of deaths, the development of alternative treatments to overcome the disease is still necessary. It is known that the infection begins with the interaction of the spike glycoprotein (at the virus surface) and the angiotensin-converting enzyme 2 cell receptor (ACE2). Therefore, a straightforward solution for promoting virus inhibition seems to be the search for molecules capable of abolishing such attachment. In this work, we tested 18 triterpene derivatives as potential inhibitors of SARS-CoV-2 against the receptor-binding domain (RBD) of the spike protein by means of molecular docking and molecular dynamics simulations, modeling the RBD S1 subunit from the X-ray structure of the RBD-ACE2 complex (PDB ID: 6M0J). Molecular docking revealed that at least three triterpene derivatives of each type (i.e., oleanolic, moronic and ursolic) present similar interaction energies as the reference molecule, i.e., glycyrrhizic acid. Molecular dynamics suggest that two compounds from oleanolic and ursolic acid, OA5 and UA2, can induce conformational changes capable of disrupting the RBD-ACE2 interaction. Finally, physicochemical and pharmacokinetic properties simulations revealed favorable biological activity as antivirals.

Identifying SARS-CoV-2 Drugs Binding to the Spike Fatty Acid Binding Pocket Using In Silico Docking and Molecular Dynamics

Drugs against novel targets are needed to treat COVID-19 patients, especially as SARS-CoV-2 is capable of rapid mutation. Structure-based de novo drug design and repurposing of drugs and natural products is a rational approach to discovering potentially effective therapies. These in silico simulations can quickly identify existing drugs with known safety profiles that can be repurposed for COVID-19 treatment. Here, we employ the newly identified spike protein free fatty acid binding pocket structure to identify repurposing candidates as potential SARS-CoV-2 therapies. Using a validated docking and molecular dynamics protocol effective at identifying repurposing candidates inhibiting other SARS-CoV-2 molecular targets, this study provides novel insights into the SARS-CoV-2 spike protein and its potential regulation by endogenous hormones and drugs. Some of the predicted repurposing candidates have already been demonstrated experimentally to inhibit SARS-CoV-2 activity, but most of the candidate drugs have yet to be tested for activity against the virus. We also elucidated a rationale for the effects of steroid and sex hormones and some vitamins on SARS-CoV-2 infection and COVID-19 recovery.

Virtual screening and molecular dynamics simulations provide insight into repurposing drugs against SARS-CoV-2 variants Spike protein/ACE2 interface

After over two years of living with Covid-19 and hundreds of million cases worldwide there is still an unmet need to find proper treatments for the novel coronavirus, due also to the rapid mutation of its genome. In this context, a drug repositioning study has been performed, using in silico tools targeting Delta Spike protein/ACE2 interface. To this aim, it has been virtually screened a library composed by 4388 approved drugs through a deep learning-based QSAR model to identify protein-protein interactions modulators for molecular docking against Spike receptor binding domain (RBD). Binding energies of predicted complexes were calculated by Molecular Mechanics/Generalized Born Surface Area from docking and molecular dynamics simulations. Four out of the top twenty ranking compounds showed stable binding modes on Delta Spike RBD and were evaluated also for their effectiveness against Omicron. Among them an antihistaminic drug, fexofenadine, revealed very low binding energy, stable complex, and interesting interactions with Delta Spike RBD. Several antihistaminic drugs were found to exhibit direct antiviral activity against SARS-CoV-2 in vitro, and their mechanisms of action is still debated. This study not only highlights the potential of our computational methodology for a rapid screening of variant-specific drugs, but also represents a further tool for investigating properties and mechanisms of selected drugs.

A Pathway Model to Understand the Evolution of Spike Protein Binding to ACE2 in SARS-CoV-2 Variants

After the SARS-CoV-2 Wuhan variant that gave rise to the pandemic, other variants named Delta, Omicron, and Omicron-2 sequentially became prevalent, with mutations spread around the viral genome, including on the spike (S) protein; in order to understand the resultant in gains in infectivity, we interrogated in silico both the equilibrium binding and the binding pathway of the virus' receptor-binding domain (RBD) to the angiotensin-converting enzyme 2 (ACE2) receptor. We interrogated the molecular recognition between the RBD of different variants and ACE2 through supervised molecular dynamics (SuMD) and classic molecular dynamics (MD) simulations to address the effect of mutations on the possible S protein binding pathways. Our results indicate that compensation between binding pathway efficiency and stability of the complex exists for the Omicron BA.1 receptor binding domain, while Omicron BA.2's mutations putatively improved the dynamic recognition of the ACE2 receptor, suggesting an evolutionary advantage over the previous strains.

The role of herbal plants in the inhibition of SARS-CoV-2 main protease: A computational approach

COVID-19 has quickly spread across the globe, becoming a pandemic. This disease has a variable impact in different countries depending on their cultural norms, mitigation efforts and health infrastructure. This study aims to assess the herbal plants in the pursuit of potential SARS-CoV-2 M^pro inhibitors using in silico approaches. We have considered 16 extracted compounds of 10 different species of these plants. In order to explain their inhibition properties and chemical reactivity pattern, we have performed the density functional theory based calculations of frontier molecular orbitals, molecular electrostatic potential surface and chemical reactivity descriptors. Our calculated lipophilicity, aqueous solubility and binding affinity of the extracted compounds suggest that the inhibition potentials in the order; harsingar > aloe vera > giloy > turmeric > neem > ginger > red onion > tulsi > cannabis > black pepper. On comparing the binding affinity with hydroxychloroquine, we note that the inhibition potentials of the extracts of harsingar, aloe vera and giloy are very promising. In order to validate this, we have also performed MD simulation and MM-PBSA binding free energy analysis. Therefore, we believe that these findings will open further possibilities and accelerate the works towards finding an antidote for this malady.

Molecular dynamics studies reveal structural and functional features of the SARS-CoV-2 spike protein

The SARS-CoV-2 virus is responsible for the COVID-19 pandemic the world experience since 2019. The protein responsible for the first steps of cell invasion, the spike protein, has probably received the most attention in light of its central role during infection. Computational approaches are among the tools employed by the scientific community in the enormous effort to study this new affliction. One of these methods, namely molecular dynamics (MD), has been used to characterize the function of the spike protein at the atomic level and unveil its structural features from a dynamic perspective. In this review, we focus on these main findings, including spike protein flexibility, rare S protein conformational changes, cryptic epitopes, the role of glycans, drug repurposing, and the effect of spike protein variants.

The impacts of 13 novel mutations of SARS-CoV-2 on protein dynamics: In silico analysis from Turkey

SARS-CoV-2 inherits a high rate of mutations making it better suited to the host since its fundamental role in evolution is to provide diversity into the genome. This research aims to identify variations in Turkish isolates and predict their impacts on proteins. To identify novel variations and predict their impacts on protein dynamics, in silico methodology was used. The 411 sequences from Turkey were analysed. Secondary structure prediction by Garnier-Osguthorpe-Robson (GOR) was used. To find the effects of identified Spike mutations on protein dynamics, the SARS-CoV-2 structures (PDB:6VYB, 6M0J) were uploaded and predicted by Cutoff Scanning Matrix (mCSM), DynaMut and MutaBind2. To understand the effects of these mutations on Spike protein molecular dynamics (MD) simulation was employed. Turkish sequences were aligned with sequences worldwide by MUSCLE, and phylogenetic analysis was performed via MegaX. The 13 novel mutations were identified, and six of them belong to spike glycoprotein. Ten of these variations revealed alteration in the secondary structure of the protein. Differences of free energy between the reference sequence and six mutants were found below zero for each of six isolates, demonstrating these variations have stabilizing effects on protein structure. Differences in vibrational entropy calculation revealed that three variants have rigidification, while the other three have a flexibility effect. MD simulation revealed that point mutations in spike glycoprotein and RBD:ACE-2 complex cause changes in protein dynamics compared to the wild-type, suggesting possible alterations in binding affinity. The phylogenetic analysis showed Turkish sequences distributed throughout the tree, revealing multiple entrances to Turkey.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Singular Interface Dynamics of the SARS-CoV-2 Delta Variant Explained with Contact Perturbation Analysis

Emerging SARS-CoV-2 variants raise concerns about our ability to withstand the Covid-19 pandemic, and therefore, understanding mechanistic differences of those variants is crucial. In this study, we investigate disparities between the SARS-CoV-2 wild type and five variants that emerged in late 2020, focusing on the structure and dynamics of the spike protein interface with the human angiotensin-converting enzyme 2 (ACE2) receptor, by using crystallographic structures and extended analysis of microsecond molecular dynamics simulations. Dihedral angle principal component analysis (PCA) showed the strong similarities in the spike receptor binding domain (RBD) dynamics of the Alpha, Beta, Gamma, and Delta variants, in contrast with those of WT and Epsilon. Dynamical perturbation networks and contact PCA identified the peculiar interface dynamics of the Delta variant, which cannot be directly imputable to its specific L452R and T478K mutations since those residues are not in direct contact with the human ACE2 receptor. Our outcome shows that in the Delta variant the L452R and T478K mutations act synergistically on neighboring residues to provoke drastic changes in the spike/ACE2 interface; thus a singular mechanism of action eventually explains why it dominated over preceding variants.

Molecular dynamics simulation approach for discovering potential inhibitors against SARS-CoV-2: A structural review

Since the commencement of the novel Coronavirus, the disease has quickly turned into a worldwide crisis so that there has been growing attention in discovering possible hit compounds for tackling this pandemic. Discovering standard treatment strategies is a serious challenge because little information is available about this emerged infectious virus. Regarding the high impact of time, applying computational procedures to choose promising drugs from a catalog of licensed medications provides a precious chance for combat against the life-threatening disorder of COVID-19. Molecular dynamics (MD) simulation is a promising approach for assessing the binding affinity of ligand-receptor as well as observing the conformational trajectory of docked complexes over time. Given that many computational studies are performed using MD along with the molecular docking on various candidates as antiviral inhibitors of COVID-19 protease, there is a demand to conduct a comprehensive review of the most important studies to reveal and compare the potential introduced agents that this study covers this defect. In this context, the present review intends to prepare an overview of these studies by considering RMSD, RMSF, radius of gyration, binding free energy, and Solvent-Accessible Surface Area (SASA) as effective parameters for evaluation. The outcomes will offer a road map for adjusting antiviral inhibitors, which can facilitate the selection and development of drug candidates for use in the medical therapy. Finally, the molecular modeling approaches rendered by this study may be valuable for future computational studies.

Molecular Dynamics Studies on the Structural Stability Prediction of SARS-CoV-2 Variants Including Multiple Mutants

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused the Coronavirus Disease (COVID-19) pandemic worldwide. The spike protein in SARS-CoV-2 fuses with and invades cells in the host respiratory system by binding to angiotensin-converting enzyme 2 (ACE2). The spike protein, however, undergoes continuous mutation from a D614G single mutant to an omicron variant, including multiple mutants. In this study, variants, including multiple mutants (double, triple mutants, B.1.620, delta, alpha, delta_E484Q, mu, and omicron) were investigated in patients. The 3D structure of the full-length spike protein was used in conformational analysis depending on the SARS-CoV-2 variants. The structural stability of the variant types was analyzed based on the distance between the receptor-binding domain (RBD) of each chain in the spike protein and the binding free energy between the spike protein and bound ACE2 in the one-, two-, and three-open-complex forms using molecular dynamics (MD) simulation. Omicron variants, the most prevalent in the recent history of the global pandemic, which consist of 32 mutations, showed higher stability in all open-complex forms compared with that of the wild type and other variants. We suggest that the conformational stability of the spike protein is the one of the important determinants for the differences in viral infectivity among variants, including multiple mutants.

Mutational scanning of spike RBD protein for enhanced ACE2 affinity emerging Southeast Asia in the late transmission phase

The COVID-19 pandemic has changed the quality of life and economic systems all over the world, as the virus can be transmitted from human to human via air-droplets. Since the SARS-CoV-2 virus was first identified in 2019, the virus has naturally mutated over time. Southeast Asia is one of the areas in the world that has implemented various procedures and measures to slow down the disease outbreaks. The first cluster of COVID-19 was identified from the tourist-travel history, and then the diversity of coronavirus victims has posed a serious issue of human security on a massive scale. To evaluate whether or not naturally occurring mutations have strengthened the infectivity of SARS-CoV-2, we computed in silico the structural dynamics of the RBD-spike protein mutation enhancing ACE2-binding. When considering emerging variations in Southeast Asia, 14 dominant mutations were analyzed by applying the structural and energetic characterization using MD simulations. The ones in the RBD region displayed higher affinity to ACE2 due to the improved interfacial stability of the RBD β-strand surrounding the ACE2 across salt bridge hotspots. The binding hotspots and structurally conserved conformational-epitopes have been identified, which are deleterious for RBD mutation and ACE2 binding. We present an interactive visualization to facilitate the development of effective neutralizing agents for vaccination, prevention and treatment.

Computational studies suggest compounds restoring function of p53 cancer mutants can bind SARS-CoV-2 spike protein

It is reasonable to think that cancer patients undergoing chemotherapy or immunotherapy may have a more aggressive course if they are positive for the novel coronavirus disease. Their compulsive condition requires investigation into effective drugs. We applied computational techniques to a series of compounds known for restoring the function of p53 cancer mutant p53^R175H and p53^G245S. Two potent inhibitors, 1-(3-chlorophenyl)-3-(1, 3 -thiazol-2-yl) urea (CTU, PubChem NSC321792) with the highest binding affinity -6.92 kcal/mol followed by a thiosemicarbazone compound N'-(1-(Pyridin-2-yl)ethylidene) azetidine - 1 -carbothiohydrazide (NPC, PubChem NSC319726) with -6.75 kcal/mol were subjected to Molecular Dynamics simulation with receptor binding domain (RBD) and compared with control ligand dexamethasone. In particular, CTU adheres to pocket 1 with an average free energy of binding -21.65 ± 2.89 kcal/mol at the RBD - angiotensin-converting enzyme 2 binding region with the highest frequency of amino acid residues after reaching a local equilibrium in 100 ns MD simulation trajectory. A significant enthalpy contribution from the independent simulations unfolds the possibility of dual binding sites for NPC as shifted pocket 1 (-15.59 ± 5.98 kcal/mol) and pocket 2 (-18.90 ± 5.02 kcal/mol). The obtained results for these two compounds are in good agreement with dexamethasone (-18.45 ± 2.42 kcal/mol). Taken together our findings could facilitate the discovery of small molecules that restore the function of p53 cancer mutants newly against COVID-19 in cancer patients.

The inherent flexibility of receptor binding domains in SARS-CoV-2 spike protein

Spike (S) protein is the primary antigenic target for neutralization and vaccine development for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It decorates the virus surface and undergoes large motions of its receptor binding domains (RBDs) to enter the host cell. Here, we observe Down, one-Up, one-Open, and two-Up-like structures in enhanced molecular dynamics simulations, and characterize the transition pathways via inter-domain interactions. Transient salt-bridges between RBDA and RBDC and the interaction with glycan at N343B support RBDA motions from Down to one-Up. Reduced interactions between RBDA and RBDB in one-Up induce RBDB motions toward two-Up. The simulations overall agree with cryo-electron microscopy structure distributions and FRET experiments and provide hidden functional structures, namely, intermediates along Down-to-one-Up transition with druggable cryptic pockets as well as one-Open with a maximum exposed RBD. The inherent flexibility of S-protein thus provides essential information for antiviral drug rational design or vaccine development.

Accelerating the discovery of the beyond rule of five compounds that have high affinities toward SARS-CoV-2 spike RBD

The battle against SARS-CoV-2 coronavirus is the focal point for the global pandemic that has affected millions of lives worldwide. The need for effective and selective therapeutics for the treatment of the disease caused by SARS-CoV-2 is critical. Herein, we performed a hierarchical computational approach incorporating molecular docking studies, molecular dynamics simulations, absolute binding energy calculations, and steered molecular dynamics simulations for the discovery of potential compounds with high affinity towards SARS-CoV-2 spike RBD. By leveraging ZINC15 database, a total of 1282 in-clinical and FDA approved drugs were filtered out from nearly 0.5 million protomers of relatively large compounds (MW > 500, and LogP ≤ 5). Our results depict plausible mechanistic aspects related to the blockage of SARS-CoV-2 spike RBD by the top hits discovered. We found that the most promising candidates, namely, ZINC95628821, ZINC95617623, ZINC3979524, and ZINC261494658, strongly bind to the spike RBD and interfere with the human ACE2 receptor. These findings accelerate the rational design of selective inhibitors targeting the spike RBD protein of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

In silico evaluation of the interaction between ACE2 and SARS-CoV-2 Spike protein in a hyperglycemic environment

The worse outcome of COVID-19 in people with diabetes mellitus could be related to the non-enzymatic glycation of human ACE2, leading to a more susceptible interaction with virus Spike protein. We aimed to evaluate, through a computational approach, the interaction between human ACE2 receptor and SARS-CoV-2 Spike protein under different conditions of hyperglycemic environment. A computational analysis was performed, based on the X-ray crystallographic structure of the Spike Receptor-Binding Domain (RBD)-ACE2 system. The possible scenarios of lysine aminoacid residues on surface transformed by glycation were considered: (1) on ACE2 receptor; (2) on Spike protein; (3) on both ACE2 receptor and Spike protein. In comparison to the native condition, the number of polar bonds (comprising both hydrogen bonds and salt bridges) in the poses considered are 10, 6, 6, and 4 for the states ACE2/Spike both native, ACE2 native/Spike glycated, ACE2 glycated/Spike native, ACE2/Spike both glycated, respectively. The analysis highlighted also how the number of non-polar contacts (in this case, van der Waals and aromatic interactions) significantly decreases when the lysine aminoacid residues undergo glycation. Following non-enzymatic glycation, the number of interactions between human ACE2 receptor and SARS-CoV-2 Spike protein is decreased in comparison to the unmodified model. The reduced affinity of the Spike protein for ACE2 receptor in case of non-enzymatic glycation may shift the virus to multiple alternative entry routes.

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.

Accelerating COVID-19 Research Using Molecular Dynamics Simulation

The COVID-19 pandemic has emerged as a global medico-socio-economic disaster. Given the lack of effective therapeutics against SARS-CoV-2, scientists are racing to disseminate suggestions for rapidly deployable therapeutic options, including drug repurposing and repositioning strategies. Molecular dynamics (MD) simulations have provided the opportunity to make rational scientific breakthroughs in a time of crisis. Advancements in these technologies in recent years have become an indispensable tool for scientists studying protein structure, function, dynamics, interactions, and drug discovery. Integrating the structural data obtained from high-resolution methods with MD simulations has helped in comprehending the process of infection and pathogenesis, as well as the SARS-CoV-2 maturation in host cells, in a short duration of time. It has also guided us to identify and prioritize drug targets and new chemical entities, and to repurpose drugs. Here, we discuss how MD simulation has been explored by the scientific community to accelerate and guide translational research on SARS-CoV-2 in the past year. We have also considered future research directions for researchers, where MD simulations can help fill the existing gaps in COVID-19 research.

Molecular Dynamics Studies on the Structural Characteristics for the Stability Prediction of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) affects the COVID-19 pandemic in the world. The spike protein of the various proteins encoded in SARS-CoV-2 binds to human ACE2, fuses, and enters human cells in the respiratory system. Spike protein, however, is highly variable, and many variants were identified continuously. In this study, Korean mutants for spike protein (D614G and D614A-C terminal domain, L455F and F456L-RBD, and Q787H-S2 domain) were investigated in patients. Because RBD in spike protein is related to direct interaction with ACE2, almost all researches were focused on the RBD region or ACE2-free whole domain region. The 3D structure for spike protein complexed with ACE2 was recently released. The stability analysis through RBD distance among each spike protein chain and the binding free energy calculation between spike protein and ACE2 were performed using MD simulation depending on mutant types in 1-, 2-, and 3-open-complex forms. D614G mutant of CT2 domain, showing to be the most prevalent in the global pandemic, showed higher stability in all open-complex forms than the wild type and other mutants. We hope this study will provide an insight into the importance of conformational fluctuation in the whole domain, although RBD is involved in the direct interaction with ACE2.

Perturbation of ACE2 Structural Ensembles by SARS-CoV-2 Spike Protein Binding

The human ACE2 enzyme serves as a critical first recognition point of coronaviruses, including SARS-CoV-2. In particular, the extracellular domain of ACE2 interacts directly with the S1 tailspike protein of the SARS-CoV-2 virion through a broad protein-protein interface. Although this interaction has been characterized by X-ray crystallography, these structures do not reveal significant differences in the ACE2 structure upon S1 protein binding. In this work, using several all-atom molecular dynamics simulations, we show persistent differences in the ACE2 structure upon binding. These differences are determined with the linear discriminant analysis (LDA) machine learning method and validated using independent training and testing datasets, including long trajectories generated by D. E. Shaw Research on the Anton 2 supercomputer. In addition, long trajectories for 78 potent ACE2-binding compounds, also generated by D. E. Shaw Research, were projected onto the LDA classification vector in order to determine whether the ligand-bound ACE2 structures were compatible with S1 protein binding. This allows us to predict which compounds are "apo-like" versus "complex-like" and to pinpoint long-range ligand-induced allosteric changes in the ACE2 structure.

Protein-protein interactions at a glance: Protocols for the visualization of biomolecular interactions

Protein-protein interactions (PPIs) play a key role in many biological processes and are intriguing targets for drug discovery campaigns. Advancements in experimental and computational techniques are leading to a growth of data accessibility, and, with it, an increased need for the analysis of PPIs. In this respect, visualization tools are essential instruments to represent and analyze biomolecular interactions. In this chapter, we reviewed some of the available tools, highlighting their features, and describing their functions with practical information on their usage.

Identification of Potential Binding Sites of Sialic Acids on the RBD Domain of SARS-CoV-2 Spike Protein

COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is still an emergent pandemic for humans. The virus infection is achieved by penetrating its spike protein to host cells via binding with ACE2. Moreover, recent studies show that SARS-CoV-2 may have multiple receptors that need to be further revealed. SARS-CoV-2 shares similar sequences of the spike protein with the Middle East Respiratory Syndrome Coronavirus (MERS-CoV), which can invade host cells by binding to either DPP4 or sialic acids. Sialic acids can be linked to the terminal of glycoproteins and gangliosides are used as one of the receptors of many types of viruses. Therefore, it is very interesting to determine whether sialic acid is a potential receptor of SARS-CoV-2. To address this question, we took N-Acetylneuraminic acid (Neu5Ac), a type of predominant sialic acid found in human cells, as the molecular probe to computationally search the surface of the spike protein to locate the potential binding sites of Neu5Ac. SPR analysis and mass spectrum analysis confirmed the interaction between Neu5Ac and spike protein. This study shows that sialic acids can moderately interact with the spike protein of SARS-CoV-2 by binding between the two RBDs of the spike protein, indicating it could be a potential secondary or auxiliary receptor of SARS-CoV-2.

Small molecule therapeutics to destabilize the ACE2-RBD complex: A molecular dynamics study

The ongoing coronavirus disease 19 (COVID-19) pandemic has infected millions of people, claimed hundreds of thousands of lives, and made a worldwide health emergency. Understanding the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mechanism of infection is crucial in the development of potential therapeutics and vaccines. The infection process is triggered by direct binding of the SARS-CoV-2 receptor-binding domain (RBD) to the host-cell receptor angiotensin-converting enzyme 2 (ACE2). Many efforts have been made to design or repurpose therapeutics to deactivate the RBD or ACE2 and prevent the initial binding. In addition to direct inhibition strategies, small chemical compounds might be able to interfere and destabilize the metastable, prefusion complex of ACE2-RBD. This approach can be employed to prevent the further progress of virus infection at its early stages. In this study, molecular docking was employed to analyze the binding of two chemical compounds, SSAA09E2 and Nilotinib, with the druggable pocket of the ACE2-RBD complex. The structural changes as a result of the interference with the ACE2-RBD complex were analyzed by molecular dynamics simulations. Results show that both Nilotinib and SSAA09E2 can induce significant conformational changes in the ACE2-RBD complex, intervene with the hydrogen bonds, and influence the flexibility of proteins. Moreover, essential dynamics analysis suggests that the presence of small molecules can trigger large-scale conformational changes that may destabilize the ACE2-RBD complex.

Drug repurposing against SARS-CoV-2 receptor binding domain using ensemble-based virtual screening and molecular dynamics simulations

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused worldwide pandemic and is responsible for millions of worldwide deaths due to -a respiratory disease known as COVID-19. In the search for a cure of COVID-19, drug repurposing is a fast and cost-effective approach to identify anti-COVID-19 drugs from existing drugs. The receptor binding domain (RBD) of the SARS-CoV-2 spike protein has been a main target for drug designs to block spike protein binding to ACE2 proteins. In this study, we probed the conformational plasticity of the RBD using long molecular dynamics (MD) simulations, from which, representative conformations were identified using clustering analysis. Three simulated conformations and the original crystal structure were used to screen FDA approved drugs (2466 drugs) against the predicted binding site at the ACE2-RBD interface, leading to 18 drugs with top docking scores. Notably, 16 out of the 18 drugs were obtained from the simulated conformations, while the crystal structure suggests poor binding. The binding stability of the 18 drugs were further investigated using MD simulations. Encouragingly, 6 drugs exhibited stable binding with RBD at the ACE2-RBD interface and 3 of them (gonadorelin, fondaparinux and atorvastatin) showed significantly enhanced binding after the MD simulations. Our study shows that flexibility modeling of SARS-CoV-2 RBD using MD simulation is of great help in identifying novel agents which might block the interaction between human ACE2 and the SARS-CoV-2 RBD for inhibiting the virus infection.

Repurposing of FDA-approved drugs against active site and potential allosteric drug-binding sites of COVID-19 main protease

The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still has serious negative effects on health, social life, and economics. Recently, vaccines from various companies have been urgently approved to control SARS-CoV-2 infections. However, any specific antiviral drug has not been confirmed so far for regular treatment. An important target is the main protease (M^pro ), which plays a major role in replication of the virus. In this study, Gaussian and residue network models are employed to reveal two distinct potential allosteric sites on M^pro that can be evaluated as drug targets besides the active site. Then, Food and Drug Administration (FDA)-approved drugs are docked to three distinct sites with flexible docking using AutoDock Vina to identify potential drug candidates. Fourteen best molecule hits for the active site of M^pro are determined. Six of these also exhibit high docking scores for the potential allosteric regions. Full-atom molecular dynamics simulations with MM-GBSA method indicate that compounds docked to active and potential allosteric sites form stable interactions with high binding free energy (∆G_bind ) values. ∆G_bind values reach -52.06 kcal/mol for the active site, -51.08 kcal/mol for the potential allosteric site 1, and - 42.93 kcal/mol for the potential allosteric site 2. Energy decomposition calculations per residue elucidate key binding residues stabilizing the ligands that can further serve to design pharmacophores. This systematic and efficient computational analysis successfully determines ivermectine, diosmin, and selinexor currently subjected to clinical trials, and further proposes bromocriptine, elbasvir as M^pro inhibitor candidates to be evaluated against SARS-CoV-2 infections.

Druggability of cavity pockets within SARS-CoV-2 spike glycoprotein and pharmacophore-based drug discovery

Aim: Virus spike glycoprotein of SARS-CoV-2 is a good target for drug discovery. Objective: To examine the potential for druggability of spike protein for pharmacophore-based drug discovery and to investigate the binding affinity of natural products with SARS-CoV-2 spike protein. Methods: Druggable cavities were searched though CavityPlus. A pharmacophore was built and used for hit identification. Autodock Vina was used to evaluate the hits' affinities. 10 chemical derivatives were also made from the chemical backbone to optimize the lead compound. Results: 10 druggable cavities were found within the glycoprotein spike. Only one cavity with the highest score at the binding site was selected for pharmacophore extraction. Hit identification resulted in the identification of 410 hits. Discussion: This study provides a druggable region within viral glycoprotein and a candidate compound to block viral entry.

Combined use of the hepatitis C drugs and amentoflavone could interfere with binding of the spike glycoprotein of SARS-CoV-2 to ACE2: the results of a molecular simulation study

The worldwide rapid spread of the COVID-19 disease necessitates the search for fast and effective treatments. The repurposing of existing drugs seems to be the best solution in this situation. In this study, the molecular docking method was used to test 248 drugs against the receptor-binding domain (RBD) of spike glycoprotein of SARS-CoV-2, which is responsible for viral entry into the host cell. Among the top-ranked ligands are drugs that are used for hepatitis C virus (HCV) treatments (paritaprevir, ledipasvir, simeprevir) and a natural biflavonoid amentoflavone. The binding sites of the HCV drugs and amentoflavone are different. Therefore, the ternary complexes of the HCV drug, amentoflavone, and RBD can be created. For the 5 top-ranked ligands, the validating molecular dynamics simulations of binary and ternary complexes with RBD were performed. According to the MMPBSA-binding free energies, the HCV drugs ledipasvir and paritaprevir (in a neutral form) are the most efficient binders of the RBD when used in combination with amentoflavone.Communicated by Ramaswamy H. Sarma.

Small Molecules to Destabilize the ACE2-RBD Complex: A Molecular Dynamics Study for Potential COVID-19 Therapeutics

The ongoing COVID-19 pandemic has infected millions of people, claimed hundreds of thousands of lives, and made a worldwide health emergency. Understanding the SARS-CoV-2 mechanism of infection is crucial in the development of potential therapeutics and vaccines. The infection process is triggered by direct binding of the SARS-CoV-2 receptor-binding domain (RBD) to the host cell receptor, Angiotensin-converting enzyme 2 (ACE2). Many efforts have been made to design or repurpose therapeutics to deactivate RBD or ACE2 and prevent the initial binding. In addition to direct inhibition strategies, small chemical compounds might be able to interfere and destabilize the meta-stable, pre-fusion complex of ACE2-RBD. This approach can be employed to prevent the further progress of virus infection at its early stages. In this study, Molecular docking is employed to analyze the binding of two chemical compounds, SSAA09E2 and Nilotinib, with the druggable pocket of the ACE2-RBD complex. The structural changes as a result of the interference with the ACE2-RBD complex are analyzed by molecular dynamics simulations. Results show that both Nilotinib and SSAA09E2 can induce significant conformational changes in the ACE2-RBD complex, intervene with the hydrogen bonds, and influence the flexibility of proteins. Moreover, essential dynamics analysis suggests that the presence of small molecules can trigger large-scale conformational changes that may destabilize the ACE2-RBD complex.

The tyrosine kinase inhibitor nilotinib inhibits SARS-CoV-2 in vitro

Since the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at the end of 2019, no vaccine has been approved to counter this infection and the available treatments are mainly directed against the immune pathology caused by the infection. The coronavirus disease 2019 (COVID-19) is currently causing a worldwide pandemic, pointing the urgent need for effective treatment. In such emergency, drug repurposing presents the best option for a rapid antiviral response. We assess here the in vitro activity of nilotinib, imatinib and dasatinib, three Abl tyrosine kinase inhibitors, against SARS-CoV-2. Although the last two compounds do not show antiviral efficacy, we observe inhibition with nilotinib in Vero-E6 cells and Calu-3 cells with EC50s of 1.44 μM and 3.06 μM, respectively. These values are close to the mean peak concentration of nilotinib observed at steady state in serum, making this compound a potential candidate for treatment of COVID-19 in vivo.