High-throughput virtual screening of drug databanks for potential inhibitors of SARS-CoV-2 spike glycoprotein

Treatment of flexibility of protein backbone in simulations of protein-ligand interactions using steered molecular dynamics

To ensure that an external force can break the interaction between a protein and a ligand, the steered molecular dynamics simulation requires a harmonic restrained potential applied to the protein backbone. A usual practice is that all or a certain number of protein's heavy atoms or Cα atoms are fixed, being restrained by a small force. This present study reveals that while fixing both either all heavy atoms and or all Cα atoms is not a good approach, while fixing a too small number of few atoms sometimes cannot prevent the protein from rotating under the influence of the bulk water layer, and the pulled molecule may smack into the wall of the active site. We found that restraining the Cα atoms under certain conditions is more relevant. Thus, we would propose an alternative solution in which only the Cα atoms of the protein at a distance larger than 1.2 nm from the ligand are restrained. A more flexible, but not too flexible, protein will be expected to lead to a more natural release of the ligand.

Functions of MAP3Ks in antiviral immunity

Immune signal transduction is crucial to the body's defense against viral infection. Recognition of pathogen-associated molecular patterns by pattern recognition receptors (PRRs) activates the transcription of interferon regulators and nuclear factor-κB (NF-κB); this promotes the release of interferons and inflammatory factors. Efficient regulation of type I interferon and NF-κB signaling by members of the mitogen-activated protein (MAP) kinase kinase kinase (MAP3K) family plays an important role in antiviral immunity. Elucidating the specific roles of MAP3K activation during viral infection is essential to develop effective antiviral therapies. In this review, we outline the specific regulatory mechanisms of MAP3Ks in antiviral immunity and discuss the feasibility of targeting MAP3Ks for the treatment of virus-induced diseases.

In silico study identifies peptide inhibitors that negate the effect of non-synonymous mutations in major drug targets of SARS-CoV-2 variants

Since its advent in December 2019, SARS-CoV-2 has diverged into multiple variants with differing levels of virulence owing to the accumulation of mutations in its genome. The structural changes induced by non-synonymous mutations in major drug targets of the virus are known to alter the binding of potential antagonistic inhibitors. Here, we analyzed the effects of non-synonymous mutations in major targets of SARS-CoV-2 in response to potential peptide inhibitors. We screened 12 peptides reported to have anti-viral properties against RBD and 5 peptides against Mpro of SARS-CoV-2 variants using molecular docking and simulation approaches. The mutational landscape of RBD among SARS-CoV-2 variants had 21 non-synonymous mutations across 18 distinct sites. Among these, 14 mutations were present in the RBM region directly interacting with the hACE2 receptor. However, Only 3 non-synonymous mutations were observed in Mpro. We found that LCB1 - a de novo-synthesized peptide has the highest binding affinity to RBD despite non-synonymous mutations in variants and engages key residues of RBD-hACE2 interaction such as K417, E484, N487, and N501. Similarly, an antimicrobial peptide; 2JOS, was identified against Mpro with high binding affinity as it interacts with key residues in dimerization sites such as E166 and F140 crucial for viral replication. MD simulations affirm the stability of RBD-LCB1 and Mpro-2JOS complexes with an average RMSD of 1.902 and 2.476 respectively. We ascertain that LCB1 and 2JOS peptides are promising inhibitors to combat emerging variants of SARS-CoV-2 and thus warrant further investigations using in-vitro and in-vivo analysis.Communicated by Ramaswamy H. Sarma.

Molecular Insights into the Binding Behavior of Imidazolium Ionic Liquids to the Receptor Binding Domain of the SARS-CoV-2 Spike Protein

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein is considered as a key target for the design and development of COVID-19 drugs and inhibitors. Due to their unique structure and properties, ionic liquids (ILs) have many special interactions with proteins, showing great potential in biomedicine. Nevertheless, few research studies have been carried out on ILs and the spike RBD protein. Here, we explore the interaction of ILs and the RBD protein through large-scale molecular dynamics simulations (4 μs in total). It was found that IL cations with long alkyl chain lengths (nchain) could spontaneously bind to the cavity region of the RBD protein. The longer the alkyl chain is, the stabler the cations bind to the protein. The binding free energy (ΔG) had the same trend, peaking at nchain = 12 with -101.19 kJ/mol. The cationic chain lengths and their fit to the pocket are decisive factors that influence the binding strength of cations and proteins. The cationic imidazole ring has a high contact frequency with phenylalanine and tryptophan, and the hydrophobic residues phenylalanine, valine, leucine, and isoleucine are the most interacting residues with side chains of cations. Meanwhile, through analysis of the interaction energy, the hydrophobic and π-π interactions are the main contributors to the high affinity between cations and the RBD protein. In addition, the long-chain ILs would also act on the protein through clustering. These studies not only provide insights into the molecular interaction between ILs and the RBD of SARS-CoV-2 but also contribute to the rational design of IL-based drugs, drug carriers, and selective inhibitors as a therapeutic for SARS-CoV-2.

Serine-arginine protein kinases and their targets in viral infection and their inhibition

Accumulating evidence has consolidated the interaction between viral infection and host alternative splicing. Serine-arginine (SR) proteins are a class of highly conserved splicing factors critical for the spliceosome maturation, alternative splicing and RNA metabolism. Serine-arginine protein kinases (SRPKs) are important kinases that specifically phosphorylate SR proteins to regulate their distribution and activities in the central pre-mRNA splicing and other cellular processes. In addition to the predominant SR proteins, other cytoplasmic proteins containing a serine-arginine repeat domain, including viral proteins, have been identified as substrates of SRPKs. Viral infection triggers a myriad of cellular events in the host and it is therefore not surprising that viruses explore SRPKs-mediated phosphorylation as an important regulatory node in virus-host interactions. In this review, we briefly summarize the regulation and biological function of SRPKs, highlighting their involvement in the infection process of several viruses, such as viral replication, transcription and capsid assembly. In addition, we review the structure-function relationships of currently available inhibitors of SRPKs and discuss their putative use as antivirals against well-characterized viruses or newly emerging viruses. We also highlight the viral proteins and cellular substrates targeted by SRPKs as potential antiviral therapeutic candidates.

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.

Structure based Drug Designing Approaches in SARS-CoV-2 Spike Inhibitor Design

The COVID-19 outbreak and the pandemic situation have hastened the research community to design a novel drug and vaccine against its causative organism, the SARS-CoV-2. The spike glycoprotein present on the surface of this pathogenic organism plays an immense role in viral entry and antigenicity. Hence, it is considered an important drug target in COVID-19 drug design. Several three-dimensional crystal structures of this SARS-CoV-2 spike protein have been identified and deposited in the Protein DataBank during the pandemic period. This accelerated the research in computer- aided drug designing, especially in the field of structure-based drug designing. This review summarizes various structure-based drug design approaches applied to this SARS-CoV-2 spike protein and its findings. Specifically, it is focused on different structure-based approaches such as molecular docking, high-throughput virtual screening, molecular dynamics simulation, drug repurposing, and target-based pharmacophore modelling and screening. These structural approaches have been applied to different ligands and datasets such as FDA-approved drugs, small molecular chemical compounds, chemical libraries, chemical databases, structural analogs, and natural compounds, which resulted in the prediction of spike inhibitors, spike-ACE-2 interface inhibitors, and allosteric inhibitors.

High-Throughput Screening for the Potential Inhibitors of SARS-CoV-2 with Essential Dynamic Behavior

Global health security has been challenged by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Due to the lengthy process of generating vaccinations, it is vital to reposition currently available drugs in order to relieve anti-epidemic tensions and accelerate the development of therapies for Coronavirus Disease 2019 (COVID-19), the public threat caused by SARS-CoV-2. High throughput screening techniques have established their roles in the evaluation of already available medications and the search for novel potential agents with desirable chemical space and more cost-effectiveness. Here, we present the architectural aspects of highthroughput screening for SARS-CoV-2 inhibitors, especially three generations of virtual screening methodologies with structural dynamics: ligand-based screening, receptor-based screening, and machine learning (ML)-based scoring functions (SFs). By outlining the benefits and drawbacks, we hope that researchers will be motivated to adopt these methods in the development of novel anti- SARS-CoV-2 agents.

Design and performance characteristics of the Elecsys anti-SARS-CoV-2 S assay

Background

Automated, high throughput assays are required to quantify the immune response after infection with or vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study on the Roche Elecsys^® Anti-SARS-CoV-2 S (ACOV2S) assay provides insights on the assay design and performance.

Methods

The ACOV2S assay quantifies antibodies to the receptor-binding domain of the SARS-CoV-2 spike protein. The assigned units and the underlying standardization were compared to the international reference standard in BAU/mL. Assay specificity was assessed in samples (n=5981) collected prior to the COVID-19 pandemic and in samples from patients with non-COVID-19 respiratory infections (n=697) or other infectious diseases (n=771). Sensitivity was measured in 1313 samples from patients with mild COVID-19 and 297 samples from patients hospitalized with COVID-19. Comparison of results was performed to a comparator semi-quantitative anti-S1 assay of indirect detection format as well as a commercially available and an in-house version of a surrogate neutralization assay (ACE2-RBD).

Results

The originally assigned units for the ACOV2S assay were shown to be congruent to the units of the First International WHO Standard for anti-SARS-CoV-2 immunoglobulins. Overall specificity was 99.98% with no geographical differences noted and no loss of specificity in samples containing potentially cross-reacting antibodies. High sensitivity was observed, with 98.8% of samples reported to be reactive >14 days after infection and sustained detection of antibodies over time. For all samples, ACOV2S titers and neutralization capacities developed with comparable dynamics. Robust standardization and assay setup enable excellent reproducibility of results, independent of lot or analyzer used.

Conclusion

The results from this study confirmed that ACOV2S is a highly sensitive and specific assay and correlates well with surrogate neutralization assays. The units established for ACOV2S are also interchangeable with the units of the First International WHO Standard for anti-SARS-CoV-2 immunoglobulins. Worldwide availability of the assay and analyzers render ACOV2S a highly practical tool for population-wide assessment and monitoring of the humoral response to SARS-CoV-2 infection or vaccination.

Pharmacophore study, molecular docking and molecular dynamic simulation of virgin coconut oil derivatives as anti-inflammatory agent against COX-2

Background

Virgin coconut oil is mostly made up of saturated fatty acids in which approximately 72% are medium chain triglycerides. Medium chain triglycerides can be digested into medium chain fatty acids and medium chain monoglycerides which are bioactive components. Therefore, it is very important to study the in-silico ability of some Virgin coconut oil derivatives, namely, medium chain fatty acids and medium chain monoglycerides to inhibit Cyclooxygenase 2 (COX-2) protein for prevention of excessive inflammatory response.

Results

Pharmacophore study displayed monolaurin with two hydrogen bond donor, three hydrogen bond acceptor and five hydrophobic interactions, while lauric acid presented two hydrogen bond acceptor, five hydrophobic interactions and a negative ion interaction. Molecular docking underlined the ability of monolaurin in the inhibition of COX-2 protein which causes inflammatory action with a decent result of energy binding affinity of - 7.58 kcal/mol and 15 interactions out of which 3 are strong hydrogen bond with TYR385 (3.00 Å), PHE529 (2.77 Å), and GLY533 (3.10 Å) residues of the protein. Monolaurin was employed as hydrogen bond acceptor to the side of residue TYR385 of COX-2 protein with an occupancy of 67.03% and was observed to be long-living during the entire 1000 frames of the molecular dynamic simulation. The analysis of RMSD score of the Monolaurin-COX-2 complex backbone was calculated to be low (1.137 ± 0.153 Å) and was in a stable range of 0.480 to 1.520 Å. Redocking of this complex still maintained a strong hydrogen bond (2.87 Å) with the main residue TYR385. AMDET results where promising for medium chain fatty acids and medium chain monoglycerides with good physicochemical drug scores.

Conclusions

This can be concluded from the results obtained that the monolaurin has strong interactions with COX-2 protein to disrupt its function due to significant hydrogen bonds and hydrophobic interactions with amino acid residues present in the target protein's active site. These results displayed a very significant anti-inflammatory potential of monolaurin and a new promising drug candidates as anti-inflammatory agent.

Graphical Abstract

Structurally Modified Bioactive Peptide Inhibits SARS-CoV-2 Lentiviral Particles Expression

Coronavirus disease 2019 (COVID-19), the current global pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Various pharmaceuticals are being developed to counter the spread of the virus. The strategy of repurposing known drugs and bioactive molecules is a rational approach. A previously described molecule, Ile-Arg-Trp (IRW), is a bioactive tripeptide that exhibits an ability to boost angiotensin converting enzyme-2 (ACE2) expression in animals and cells. Given the importance of SARS-CoV-2 S receptor binding domain (RBD)-ACE2 interaction in SARS-CoV-2 pathophysiology, we synthesized various IRW analogs intending to mitigate the RBD-ACE-2 interaction. Herein, we describe two analogs of IRW, A9 (Acetyl-Ile-Arg-Trp-Amide) and A14 (Formyl-Ile-Arg-Trp-Amide) which lowered the SARS-CoV-2 S RBD-ACE2 (at 50 µM) in vitro. The free energy of binding suggested that A9 and A14 interacted with the SARS-CoV-2 S RBD more favorably than ACE2. The calculated MMGBSA ΔG of spike binding for A9 was −57.22 kcal/mol, while that of A14 was −52.44 kcal/mol. A14 also inhibited furin enzymatic activity at various tested concentrations (25, 50, and 100 µM). We confirmed the effect of the two potent analogs using SARS-CoV-2 spike protein overexpressing cells. Both peptides lowered the protein expression of SARS-CoV-2 spike protein at the tested concentration (50 µM). Similarly, both peptides, A9 and A14 (50 µM), also inhibited pseudotyped lentiviral particles with SARS-CoV-2 Spike in ACE2 overexpressing cells. Further, the molecular dynamics (MD) calculations showed the interaction of A9 and A14 with multiple residues in spike S1 RBD. In conclusion, novel peptide analogs of ACE2 boosting IRW were prepared and confirmed through in vitro, cellular, and computational evaluations to be potential seed candidates for SARS-CoV-2 host cell binding inhibition.

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.

The nsp15 Nuclease as a Good Target to Combat SARS-CoV-2: Mechanism of Action and Its Inactivation with FDA-Approved Drugs

The pandemic caused by SARS-CoV-2 is not over yet, despite all the efforts from the scientific community. Vaccination is a crucial weapon to fight this virus; however, we still urge the development of antivirals to reduce the severity and progression of the COVID-19 disease. For that, a deep understanding of the mechanisms involved in viral replication is necessary. nsp15 is an endoribonuclease critical for the degradation of viral polyuridine sequences that activate host immune sensors. This enzyme is known as one of the major interferon antagonists from SARS-CoV-2. In this work, a biochemical characterization of SARS-CoV-2 nsp15 was performed. We saw that nsp15 is active as a hexamer, and zinc can block its activity. The role of conserved residues from SARS-CoV-2 nsp15 was investigated, and N164 was found to be important for protein hexamerization and to contribute to the specificity to degrade uridines. Several chemical groups that impact the activity of this ribonuclease were also identified. Additionally, FDA-approved drugs with the capacity to inhibit the in vitro activity of nsp15 are reported in this work. This study is of utmost importance by adding highly valuable information that can be used for the development and rational design of therapeutic strategies.

Methylxanthines as Potential Inhibitor of SARS-CoV-2: an In Silico Approach

The aim of the present study was to test the binding affinity of methylxanthines (caffeine/theine, methylxanthine, theobromine, theophylline and xanthine) to three potential target proteins namely Spike protein (6LZG), main protease (6LU7) and nucleocapsid protein N-terminal RNA binding domain (6M3M) of SARS-CoV-2. Proteins and ligand were generated using AutoDock 1.5.6 software. Binding affinity of methylxanthines with SARS-CoV-2 target proteins was determined using Autodock Vina. MD simulation of the best interacting complexes was performed using GROMACS 2018.3 (in duplicate) and Desmond program version 2.0 (academic version) (in triplicate) to study the stabile interaction of protein-ligand complexes. Among the selected methylxanthines, theophylline showed the best binding affinity with all the three targets of SARS-CoV-2 (6LZG - 5.7 kcal mol^-1, 6LU7 - 6.5 kcal mol^-1, 6M3M - 5.8 kcal mol^-1). MD simulation results of 100 ns (in triplicate) showed that theophylline is stable in the binding pockets of all the selected SARS-CoV-2 proteins. Moreover, methylxanthines are safer and less toxic as shown by high LD₅₀ value with Protox II software as compared to drug chloroquine. This research supports the use of methylxanthines as a SARS-CoV-2 inhibitor. It also lays the groundwork for future studies and could aid in the development of a treatment for SARS-CoV-2 and related viral infections.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40495-021-00276-3.

SARS-CoV-2 variants impact RBD conformational dynamics and ACE2 accessibility

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has killed over 6 million people and is having a devastating social and economic impact around the world. The rise of new variants of concern (VOCs) represents a difficult challenge due to the loss of vaccine and natural immunity, as well as increased transmissibility. All VOCs contain mutations in the spike glycoprotein, which mediates fusion between the viral and host cell membranes. The spike glycoprotein binds to angiotensin-converting enzyme 2 (ACE2) via its receptor binding domain (RBD) initiating the infection process. Attempting to understand the effect of RBD mutations in VOCs, a lot of attention has been given to the RBD-ACE2 interaction. However, this type of analysis ignores more indirect effects, such as the conformational dynamics of the RBD itself. Observing that some mutations occur in residues that are not in direct contact with ACE2, we hypothesized that they could affect the RBD conformational dynamics. To test this, we performed long atomistic (AA) molecular dynamics (MD) simulations to investigate the structural dynamics of wt RBD, and that of four VOCs (Alpha, Beta, Delta, and Omicron). Our results show that the wt RBD presents two distinct conformations: an "open" conformation where it is free to bind ACE2; and a "closed" conformation, where the RBM ridge blocks the binding surface. The Alpha and Beta variants shift the open/closed equilibrium towards the open conformation by roughly 20%, likely increasing ACE2 binding affinity. Simulations of the Delta and Omicron variants showed extreme results, with the closed conformation being rarely observed. The Delta variant also differed substantially from the other variants, alternating between the open conformation and an alternative "reversed" one, with a significantly changed orientation of the RBM ridge. This alternate conformation could provide a fitness advantage due to increased availability for ACE2 binding, and by aiding antibody escape through epitope occlusion. These results support the hypothesis that VOCs, and particularly the Omicron and Delta variants, impact RBD conformational dynamics in a direction that promotes efficient binding to ACE2 and, in the case of Delta, may assist antibody escape.

Proteomics advances towards developing SARS-CoV-2 therapeutics using in silico drug repurposing approaches

Standing amidst the COVID-19 pandemic, we have faced major medical and economic crisis in recent times which remains to be an unresolved issue till date. Although the scientific community has made significant progress towards diagnosis and understanding the disease; however, effective therapeutics are still lacking. Several omics-based studies, especially proteomics and interactomics, have contributed significantly in terms of identifying biomarker panels that can potentially be used for the disease prognosis. This has also paved the way to identify the targets for drug repurposing as a therapeutic alternative. US Food and Drug Administration (FDA) has set in motion more than 500 drug development programs on an emergency basis, most of them are focusing on repurposed drugs. Remdesivir is one such success of a robust and quick drug repurposing approach. The advancements in omics-based technologies has allowed to explore altered host proteins, which were earlier restricted to only SARS-CoV-2 protein signatures. In this article, we have reviewed major contributions of proteomics and interactomics techniques towards identifying therapeutic targets for COVID-19. Furthermore, in-silico molecular docking approaches to streamline potential drug candidates are also discussed.

Network analytics for drug repurposing in COVID-19

To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein–protein interaction (PPI) networks integrating the top-ranked host factors, the drug target proteins and directed PPI data. We analyzed the networks to identify drug targets and combinations thereof that offer efficient control over the host factors. We validated our findings against clinical studies data and bioinformatics studies. Our method offers a new insight into the molecular details of the disease and into potentially new therapy targets for it. Our approach for drug repurposing is significant beyond COVID-19 and may be applied also to other diseases.

Interaction of serum proteins with SARS-CoV-2 RBD

The outbreak of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a worldwide public health crisis. When the SARS-CoV-2 enters the biological fluids in the human body, different types of biomolecules (in particular proteins) may adsorb on its surface and alter its infection ability. Although great efforts have recently been devoted to the interaction of specific antibodies with the SARS-CoV-2, it still remains largely unknown how the other serum proteins affect the infection of the SARS-CoV-2. In this work, we systematically investigate the interaction of serum proteins with the SARS-CoV-2 RBD by molecular docking and all-atom molecular dynamics simulations. It is found that non-specific immunoglobulins (Ig) indeed cannot effectively bind to the SARS-CoV-2 RBD while human serum albumin (HSA) may have some potential in blocking its infection (to ACE2). More importantly, we find that the RBD can cause significant structural changes in Apolipoprotein E (ApoE), by which SARS-CoV-2 may hijack the metabolic pathway of ApoE to facilitate its cell entry. The present study enhances the understanding of the role of protein corona in the bio-behaviors of SARS-CoV-2, which may aid the more precise and personalized treatment for COVID-19 infection in the clinic.

Computational identification of repurposed drugs against viruses causing epidemics and pandemics via drug-target network analysis

Viral epidemics and pandemics are considered public health emergencies. However, traditional and novel antiviral discovery approaches are unable to mitigate them in a timely manner. Notably, drug repurposing emerged as an alternative strategy to provide antiviral solutions in a timely and cost-effective manner. In the literature, many FDA-approved drugs have been repurposed to inhibit viruses, while a few among them have also entered clinical trials. Using experimental data, we identified repurposed drugs against 14 viruses responsible for causing epidemics and pandemics such as SARS-CoV-2, SARS, Middle East respiratory syndrome, influenza H1N1, Ebola, Zika, Nipah, chikungunya, and others. We developed a novel computational “drug-target-drug” approach that uses the drug-targets extracted for specific drugs, which are experimentally validated in vitro or in vivo for antiviral activity. Furthermore, these extracted drug-targets were used to fetch the novel FDA-approved drugs for each virus and prioritize them by calculating their confidence scores. Pathway analysis showed that the majority of the extracted targets are involved in cancer and signaling pathways. For SARS-CoV-2, our method identified 21 potential repurposed drugs, of which 7 (e.g., baricitinib, ramipril, chlorpromazine, enalaprilat, etc.) have already entered clinical trials. The prioritized drug candidates were further validated using a molecular docking approach. Therefore, we anticipate success during the experimental validation of our predicted FDA-approved repurposed drugs against 14 viruses. This study will assist the scientific community in hastening research aimed at the development of antiviral therapeutics.

Detection of Binding Sites on SARS-CoV-2 Spike Protein Receptor-Binding Domain by Molecular Dynamics Simulations in Mixed Solvents

The novel SARS-CoV-2 uses ACE2 (Angiotensin-Converting Enzyme 2) receptor as an entry point. Insights on S protein receptor-binding domain (RBD) interaction with ACE2 receptor and drug repurposing has accelerated drug discovery for the novel SARS-CoV-2 infection. Finding small molecule binding sites in S protein and ACE2 interface is crucial in search of effective drugs to prevent viral entry. In this study, we employed molecular dynamics simulations in mixed solvents together with virtual screening to identify small molecules that could be potential inhibitors of S protein -ACE2 interaction. Observation of organic probe molecule localization during the simulations revealed multiple sites at the S protein surface related to small molecule, antibody, and ACE2 binding. In addition, a novel conformation of the S protein was discovered that could be stabilized by small molecules to inhibit attachment to ACE2. The most promising binding site on RBD-ACE2 interface was targeted with virtual screening and top-ranked compounds (DB08248, DB02651, DB03714, and DB14826) are suggested for experimental testing. The protocol described here offers an extremely fast method for characterizing key proteins of a novel pathogen and for the identification of compounds that could inhibit or accelerate spreading of the disease.

Critical Interactions Between the SARS-CoV-2 Spike Glycoprotein and the Human ACE2 Receptor

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects human cells by binding its spike (S) glycoproteins to angiotensin-converting enzyme 2 (ACE2) receptors and causes the coronavirus disease 2019 (COVID-19). Therapeutic approaches to prevent SARS-CoV-2 infection are mostly focused on blocking S-ACE2 binding, but critical residues that stabilize this interaction are not well understood. By performing all-atom molecular dynamics (MD) simulations, we identified an extended network of salt bridges, hydrophobic and electrostatic interactions, and hydrogen bonds between the receptor-binding domain (RBD) of the S protein and ACE2. Mutagenesis of these residues on the RBD was not sufficient to destabilize binding but reduced the average work to unbind the S protein from ACE2. In particular, the hydrophobic end of RBD serves as the main anchor site and is the last to unbind from ACE2 under force. We propose that blocking the hydrophobic surface of RBD via neutralizing antibodies could prove to be an effective strategy to inhibit S-ACE2 interactions.

Screening of world approved drugs against highly dynamical spike glycoprotein of SARS-CoV-2 using CaverDock and machine learning

The new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes pathological pulmonary symptoms. Most efforts to develop vaccines and drugs against this virus target the spike glycoprotein, particularly its S1 subunit, which is recognised by angiotensin-converting enzyme 2. Here we use the in-house developed tool CaverDock to perform virtual screening against spike glycoprotein using a cryogenic electron microscopy structure (PDB-ID: 6VXX) and the representative structures of five most populated clusters from a previously published molecular dynamics simulation. The dataset of ligands was obtained from the ZINC database and consists of drugs approved for clinical use worldwide. Trajectories for the passage of individual drugs through the tunnel of the spike glycoprotein homotrimer, their binding energies within the tunnel, and the duration of their contacts with the trimer's three subunits were computed for the full dataset. Multivariate statistical methods were then used to establish structure-activity relationships and select top candidate for movement inhibition. This new protocol for the rapid screening of globally approved drugs (4359 ligands) in a multi-state protein structure (6 states) showed high robustness in the rate of finished calculations. The protocol is universal and can be applied to any target protein with an experimental tertiary structure containing protein tunnels or channels. The protocol will be implemented in the next version of CaverWeb (https://loschmidt.chemi.muni.cz/caverweb/) to make it accessible to the wider scientific community.

Prediction of repurposed drugs for Coronaviruses using artificial intelligence and machine learning

The world is facing the COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Likewise, other viruses of the Coronaviridae family were responsible for causing epidemics earlier. To tackle these viruses, there is a lack of approved antiviral drugs. Therefore, we have developed robust computational methods to predict the repurposed drugs using machine learning techniques namely Support Vector Machine, Random Forest, k-Nearest Neighbour, Artificial Neural Network, and Deep Learning. We used the experimentally validated drugs/chemicals with anticorona activity (IC50/EC50) from 'DrugRepV' repository. The unique entries of SARS-CoV-2 (142), SARS (221), MERS (123), and overall Coronaviruses (414) were subdivided into the training/testing and independent validation datasets, followed by the extraction of chemical/structural descriptors and fingerprints (17968). The highly relevant features were filtered using the recursive feature selection algorithm. The selected chemical descriptors were used to develop prediction models with Pearson's correlation coefficients ranging from 0.60 to 0.90 on training/testing. The robustness of the predictive models was further ensured using external independent validation datasets, decoy datasets, applicability domain, and chemical analyses. The developed models were used to predict promising repurposed drug candidates against coronaviruses after scanning the DrugBank. Top predicted molecules for SARS-CoV-2 were further validated by molecular docking against the spike protein complex with ACE receptor. We found potential repurposed drugs namely Verteporfin, Alatrofloxacin, Metergoline, Rescinnamine, Leuprolide, and Telotristat ethyl with high binding affinity. These 'anticorona' computational models would assist in antiviral drug discovery against SARS-CoV-2 and other Coronaviruses.

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.

Identification of multipotent drugs for COVID-19 therapeutics with the evaluation of their SARS-CoV2 inhibitory activity

The SARS-CoV2 is a highly contagious pathogen that causes COVID-19 disease. It has affected millions of people globally with an average lethality of ~3%. There is an urgent need of drugs for the treatment of COVID-19. In the current studies, we have used bioinformatics techniques to screen the FDA approved drugs against nine SARS-CoV2 proteins to identify drugs for repurposing. Additionally, we analyzed if the identified molecules can also affect the human proteins whose expression in lung changed during SARS-CoV2 infection. Targeting such genes may also be a beneficial strategy to curb disease manifestation. We have identified 74 molecules that can bind to various SARS-CoV2 and human host proteins. We experimentally validated our in-silico predictions using vero E6 cells infected with SARS-CoV2 virus. Interestingly, many of our predicted molecules viz. capreomycin, celecoxib, mefloquine, montelukast, and nebivolol showed good activity (IC50) against SARS-CoV2. We hope that these studies may help in the development of new therapeutic options for the treatment of COVID-19.