Structural modeling and analysis of the SARS-CoV-2 cell entry inhibitor camostat bound to the trypsin-like protease TMPRSS2

Molecular insights into the inhibition mechanism of harringtonine against essential proteins associated with SARS-CoV-2 entry

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has recently posed a serious threat to global public health. Harringtonine (HT), as a small-molecule antagonist, has antiviral activity against a variety of viruses. There is evidence that HT can inhibit the SARS-CoV-2 entry into host cells by blocking the Spike protein and transmembrane protease serine 2 (TMPRSS2). However, the molecular mechanism underlying the inhibition effect of HT is largely elusive. Here, docking and all-atom molecular dynamic simulations were used to investigate the mechanism of HT against the receptor binding domain (RBD) of Spike, TMPRSS2, as well as the complex of RBD and angiotensin-converting enzyme 2 complex (RBD-ACE2). The results reveal that HT binds to all proteins primarily through hydrogen bond and hydrophobic interactions. Binding with HT influences the structural stability and dynamic motility processes of each protein. The interactions of HT with residues N33, H34 and K353 of ACE2, and residue K417 and Y453 of RBD contribute to disrupting the binding affinity between RBD and ACE2, which may hinder the virus entry into host cells. Our research provides molecular insights into the inhibition mechanism of HT against SARS-CoV-2 associated proteins, which will help for the novel antiviral drugs development.

A multicenter, double-blind, randomized, parallel-group, placebo-controlled study to evaluate the efficacy and safety of camostat mesilate in patients with COVID-19 (CANDLE study)

BACKGROUND

In vitro drug screening studies have indicated that camostat mesilate (FOY-305) may prevent SARS-CoV-2 infection into human airway epithelial cells. This study was conducted to investigate whether camostat mesilate is an effective treatment for SARS-CoV-2 infection (COVID-19).

METHODS

This was a multicenter, double-blind, randomized, parallel-group, placebo-controlled study. Patients were enrolled if they were admitted to a hospital within 5 days of onset of COVID-19 symptoms or within 5 days of a positive test for asymptomatic patients. Severe cases (e.g., those requiring oxygenation/ventilation) were excluded. Patients were enrolled, randomized, and allocated to each group using an interactive web response system. Randomization was performed using a minimization method with the factors medical institution, age, and underlying diseases (chronic respiratory disease, chronic kidney disease, diabetes mellitus, hypertension, cardiovascular diseases, and obesity). The patients, investigators/subinvestigators, study coordinators, and other study personnel were blinded throughout the study. Patients were administered camostat mesilate (600 mg qid; four to eight times higher than the clinical doses in Japan) or placebo for up to 14 days. The primary efficacy endpoint was the time to the first two consecutive negative tests for SARS-CoV-2.

RESULTS

One-hundred fifty-five patients were randomized to receive camostat mesilate (n = 78) or placebo (n = 77). The median time to the first test was 11.0 days (95% confidence interval [CI]: 9.0-12.0) in the camostat mesilate group and 11.0 days (95% CI: 10.0-13.0) in the placebo group. Conversion to negative viral status by day 14 was observed in 45 of 74 patients (60.8%) in the camostat mesilate group and 47 of 74 patients (63.5%) in the placebo group. The primary (Bayesian) and secondary (frequentist) analyses found no significant differences in the primary endpoint between the two groups. No additional safety concerns beyond those already known for camostat mesilate were identified.

CONCLUSIONS

Camostat mesilate did not substantially reduce the time to viral clearance, based on upper airway viral loads, compared with placebo for treating patients with mild to moderate SARS-CoV-2 infection with or without symptoms.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04657497. Japan Registry for Clinical Trials, jRCT2031200198.

Exploring the Potential Role of Theaflavin-3,3′-Digallate in Inhibiting Various Stages of SARS-CoV-2 Life Cycle: An In-Silico Approach

Introduction

Theaflavins belong to the class of polyphenols that are predominantly found in black tea. The major derivatives of theaflavins found in black tea are theaflavin (TF1), theaflavin-3-gallate (TF2A), theaflavin-3′-gallate (TF2B), and theaflavin-3,3′-digallate (TF3). Theaflavin-3,3′-digallate (TF3) is a natural compound present in black tea and known to possess antiviral activity. This study had attempted to explore the potential role of TF3 in inhibiting various stages of the SARS-CoV-2 life cycle.

Methods

Molecular docking studies of TF3 along with positive controls was performed on eight different targets of SARS-CoV-2 followed by binding free energy (MM-GBSA) calculations. The docked complexes with favourable docking and binding free energy results were subjected to molecular dynamics (MD) simulation studies to assess the stability of the dock complex. Finally, TF3 and all the positive controls were taken for ADMET analysis.

Results

The docking and binding free energy results of TF3 was compared against the positive controls. TF3 showed the highest binding energy against all the targets and formed more stable interactions for a longer duration on MD simulations with CLpro, RdRp, helicase and spike protein. Also, the promising in-silico ADMET profile further warrants the exploration of this compound through in-vitro and in-vivo methods.

Conclusion

Through this study, we tried to evaluate the role of theaflavin-3,3’-digallate on multiple targets of SARS-CoV-2, and the positive in-silico results which were obtained on various pharmacodynamic and pharmacokinetic parameters, give a ray of hope as a potential therapeutic drug to this rapidly spreading disease. The search for a curative therapy for SARS-CoV-2 is still ongoing. The favourable preliminary results of TF3 through in-silico analysis offers a ray of hope in ending this devasting pandemic.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42250-022-00376-7.

Study of protease-mediated processes initiating viral infection and cell-cell viral spreading of SARS-CoV-2

Viral-cell entry and cell-cell viral spreading processes of SARS-CoV-2 are subjected to fast evolutionary optimization because of its worldwide spreading, requiring the need for new drug developments. However, this task is still challenging, because a detailed understanding of the underlying molecular processes, mediated by the key cellular proteases TMPRSS2 and furin, is still lacking. Here, we show by large-scale atomistic calculations that binding of the ACE2 cell receptor at one of the heteromers of the SARS-CoV-2 spike leads to a release of its furin cleavage site (S1/S2), enabling an enhanced furin binding, and that this latter process promotes the binding of TMPRSS2 through the release of the TMPRSS2 cleavage site (S2') out of the ACE2-binding heteromer. Moreover, we find that, after proteolytic cleavage, improved furin binding causes that parts of the S2 subunit dissociate from the complex, suggesting that furin promotes the fusion of the S2 subunit with the cell membrane before transfer of the viral RNA. Here we show by computational means that binding of the ACE2-cell receptor at one of the heteromers of the SARS-CoV-2 spike leads to an enhanced binding of the protease furin, promoting the binding of the protease TMPRSS2. Moreover, we show that, after proteolytic cleavage, improved furin binding causes that parts of the heteromer dissociate from the spike.

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.

Hybrid drug-screening strategy identifies potential SARS-CoV-2 cell-entry inhibitors targeting human transmembrane serine protease

The spread of coronavirus infectious disease (COVID-19) is associated with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has risked public health more than any other infectious disease. Researchers around the globe use multiple approaches to identify an effective approved drug (drug repurposing) that treats viral infections. Most of the drug repurposing approaches target spike protein or main protease. Here we use transmembrane serine protease 2 (TMPRSS2) as a target that can prevent the virus entry into the cell by interacting with the surface receptors. By hypothesizing that the TMPRSS2 binders may help prevent the virus entry into the cell, we performed a systematic drug screening over the current approved drug database. Furthermore, we screened the Enamine REAL fragments dataset against the TMPRSS2 and presented nine potential drug-like compounds that give us clues about which kinds of groups the pocket prefers to bind, aiding future structure-based drug design for COVID-19. Also, we employ molecular dynamics simulations, binding free energy calculations, and well-tempered metadynamics to validate the obtained candidate drug and fragment list. Our results suggested three potential FDA-approved drugs against human TMPRSS2 as a target. These findings may pave the way for more drugs to be exposed to TMPRSS2, and testing the efficacy of these drugs with biochemical experiments will help improve COVID-19 treatment.

Mechanistic insights of key host proteins and potential repurposed inhibitors regulating SARS-CoV-2 pathway

The emergence of pandemic situations originated from severe acute respiratory syndrome (SARS)‐CoV‐2 and its new variants created worldwide medical emergencies. Due to the non‐availability of efficient drugs and vaccines at these emergency hours, repurposing existing drugs can effectively treat patients critically infected by SARS‐CoV‐2. Finding a suitable repurposing drug with inhibitory efficacy to a host‐protein is challenging. A detailed mechanistic understanding of the kinetics, (dis)association pathways, key protein residues facilitating the entry–exit of the drugs with targets are fundamental in selecting these repurposed drugs. Keeping this target as the goal of the paper, the potential repurposing drugs, Nafamostat, Camostat, Silmitasertib, Valproic acid, and Zotatifin with host‐proteins HDAC2, CSK22, eIF4E2 are studied to elucidate energetics, kinetics, and dissociation pathways. From an ensemble of independent simulations, we observed the presence of single or multiple dissociation pathways with varying host‐proteins‐drug systems and quantitatively estimated the probability of unbinding through these specific pathways. We also explored the crucial gateway residues facilitating these dissociation mechanisms. Interestingly, the residues we obtained for HDAC2 and CSK22 are also involved in the catalytic activity. Our results demonstrate how these potential drugs interact with the host machinery and the specific target residues, showing involvement in the mechanism. Most of these drugs are in the preclinical phase, and some are already being used to treat severe COVID‐19 patients. Hence, the mechanistic insight presented in this study is envisaged to support further findings of clinical studies and eventually develop efficient inhibitors to treat SARS‐CoV‐2.

Identification of 13 Guanidinobenzoyl- or Aminidinobenzoyl-Containing Drugs to Potentially Inhibit TMPRSS2 for COVID-19 Treatment

Positively charged groups that mimic arginine or lysine in a natural substrate of trypsin are necessary for drugs to inhibit the trypsin-like serine protease TMPRSS2 that is involved in the viral entry and spread of coronaviruses, including SARS-CoV-2. Based on this assumption, we identified a set of 13 approved or clinically investigational drugs with positively charged guanidinobenzoyl and/or aminidinobenzoyl groups, including the experimentally verified TMPRSS2 inhibitors Camostat and Nafamostat. Molecular docking using the C-I-TASSER-predicted TMPRSS2 catalytic domain model suggested that the guanidinobenzoyl or aminidinobenzoyl group in all the drugs could form putative salt bridge interactions with the side-chain carboxyl group of Asp435 located in the S1 pocket of TMPRSS2. Molecular dynamics simulations further revealed the high stability of the putative salt bridge interactions over long-time (100 ns) simulations. The molecular mechanics/generalized Born surface area-binding free energy assessment and per-residue energy decomposition analysis also supported the strong binding interactions between TMPRSS2 and the proposed drugs. These results suggest that the proposed compounds, in addition to Camostat and Nafamostat, could be effective TMPRSS2 inhibitors for COVID-19 treatment by occupying the S1 pocket with the hallmark positively charged groups.