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. 

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

COVID-19 is threatening human health worldwide but no effective treatment currently exists for this disease. Current therapeutic strategies focus on the inhibition of viral replication or using anti-inflammatory/immunomodulatory compounds to improve host immunity, but not both. Traditional Chinese medicine (TCM) compounds could be promising candidates due to their safety and minimal toxicity. In this study, we have developed a novel in silico bioinformatics workflow that integrates multiple databases to predict the use of honeysuckle (Lonicera japonica) and Huangqi (Astragalus membranaceus) as potential anti-SARS-CoV-2 agents. Using extracts from honeysuckle and Huangqi, these two herbs upregulated a group of microRNAs including let-7a, miR-148b, and miR-146a, which are critical to reduce the pathogenesis of SARS-CoV-2. Moreover, these herbs suppressed pro-inflammatory cytokines including IL-6 or TNF-α, which were both identified in the cytokine storm of acute respiratory distress syndrome, a major cause of COVID-19 death. Furthermore, both herbs partially inhibited the fusion of SARS-CoV-2 spike protein-transfected BHK-21 cells with the human lung cancer cell line Calu-3 that was expressing ACE2 receptors. These herbs inhibited SARS-CoV-2 Mpro activity, thereby alleviating viral entry as well as replication. In conclusion, our findings demonstrate that honeysuckle and Huangqi have the potential to be used as an inhibitor of SARS-CoV-2 virus entry that warrants further in vivo analysis and functional assessment of miRNAs to confirm their clinical importance. This fast-screening platform can also be applied to other drug discovery studies for other infectious diseases.

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Honeysuckle (Lonicera japonica) and Huangqi (Astragalus membranaceus) Suppress SARS-CoV-2 Entry and COVID-19 Related Cytokine Storm in Vitro

The world is confronting a dire situation due to the recent pandemic of the novel coronavirus disease (SARS-CoV-2) with the mortality rate passed over 470,000. Attaining efficient drugs evolve in parallel to the understanding of the SARS-CoV-2 pathogenesis. The current drugs in the pipeline and some plausible drugs are overviewed in this paper. Although different types of anti-viral targets are applicable for SARS-CoV-2 drug screenings, the more promising targets can be considered as 3C-like main protease (3Cl protease) and RNA polymerase. The remdesivir could be considered the closest bifunctional drug to the provisional clinical administration for SARS-CoV-2. The known molecular targets of the SARS-CoV-2 include fourteen targets, while four molecules of angiotensin-converting enzyme 2 (ACE2), cathepsin L, 3Cl protease and RNA-dependent RNA polymerase (RdRp) are suggested as more promising potential targets. Accordingly, dual-acting drugs as an encouraging solution in drug discovery are suggested. Emphasizing the potential route of SARS-CoV-2 infection and virus entry-related factors like integrins, cathepsin and ACE2 seems valuable. The potential molecular targets of each phase of the SARS-CoV-2 life cycle are discussed and highlighted in this paper. Much progress in understanding the SARS-CoV-2 and molecular details of its life cycle followed by the identification of new therapeutic targets are needed to lead us to an efficient approach in anti-SARS-CoV-2 drug discovery.

Hypothetical targets and plausible drugs of coronavirus infection caused by SARS-CoV-2.

Cyclodextrins (CDs) have a hollow structure with a hydrophobic interior and hydrophilic exterior. Forming inclusion complexes with CDs will maximize the bioavailability of natural compounds and enable active components to be processed into functional foods, medicines, additives, and so forth. However, experimental methods cannot explain CD-guest binding at the atomic level. Different models have been recently developed to simulate the interaction between CDs and guests to study the binding conformation and analyze noncovalent forces. This review paper summarizes modeling methods of CD-natural compound complexes. The methods include quantitative structure-activity relationships, molecular docking, molecular dynamics simulations, and quantum-chemical calculations. The applications of these methods to enhance the solubility and bioactivities of guest molecules, assist material transportation, and promote compound extraction are also discussed. The purpose of this review is to explore interaction mechanisms of CDs and guests and to help expand new applications of CDs.

Computational Methods for the Interaction between Cyclodextrins and Natural Compounds: Technology, Benefits, Limitations, and Trends.

Targeting autophagy with natural products to prevent SARS-CoV-2 infection

The novel Coronavirus disease 2019 (COVID-19) is potentially fatal and caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Due to the unavailability of any proven treatment or vaccination, the outbreak of COVID-19 is wreaking havoc worldwide. Hence, there is an urgent need for therapeutics targeting SARS-CoV-2. Since, botanicals are an important resource for several efficacious antiviral agents, natural compounds gaining significant attention for COVID-19 treatment. In the present study, methyltranferase (MTase) of the SARS-CoV-2 is targeted using computational approach. The compounds were identified using molecular docking, virtual screening and molecular dynamics simulation studies. The binding mechanism of each compound was analyzed considering the stability and energetic parameter using in silico methods. We have found four natural antiviral compounds Amentoflavone, Baicalin, Daidzin and Luteoloside as strong inhibitors of methyltranferase of SARS-CoV-2. ADMET prediction and target analysis of the selected compounds showed favorable results. MD simulation was performed for four top-scored molecules to analyze the stability, binding mechanism and energy requirements. MD simulation studies indicated energetically favorable complex formation between MTase and the selected antiviral compounds. Furthermore, the structural effects on these substitutions were analyzed using the principles of each trajectories, which validated the interaction studies. Our analysis suggests that there is a very high probability that these compounds may have a good potential to inhibit Methyltransferase (MTase) of SARS-CoV-2 and to be used in the treatment of COVID-19. Further studies on these natural compounds may offer a quick therapeutic choice to treat COVID-19. Communicated by Ramaswamy H. Sarma.

In silico identification and validation of natural antiviral compounds as potential inhibitors of SARS-CoV-2 methyltransferase.

Hepatitis E virus (HEV) has emerged as a global health concern during the last decade. In spite of a high mortality rate in pregnant women with fulminant hepatitis, no antiviral drugs or licensed vaccine is available in India. HEV-protease is a pivotal enzyme responsible for ORF1 polyprotein processing leading to cleavage of the non-structural enzymes involved in virus replication. HEV-protease region encoding 432-592 amino acids of Genotype-1 was amplified, expressed in Sf21 cells and purified in its native form. The recombinant enzyme was biochemically characterized using SDS-PAGE, Western blotting and Immunofluorescence. The enzyme activity and the inhibition studies were conducted using Zymography, FTC-casein based protease assay and ORF1 polyprotein digestion. To conduct ORF1 digestion assay, the polyprotein, natural substrate of HEV-protease, was expressed in E. coli and purified. Cleavage of 186 kDa ORF1 polyprotein by the recombinant HEV-protease lead to appearance of non-structural proteins viz. Methyltransferase, Protease, Helicase and RNA dependent RNA polymerase which were confirmed through immunoblotting using antibodies generated against specific epitopes of the enzymes. FTC-casein substrate was used for kinetic studies to determine Km and Vmax of the enzyme and also the effect of different metal ions and other protease inhibitors. A 95% inhibition was observed with E-64 which was validated through in silico analysis. The correlation coefficient between inhibition and docking score of Inhibitors was found to have a significant value of r 2 = 0.75. The predicted 3D model showed two domain architecture structures similar to Papain like cysteine protease though they differed in arrangements of alpha helices and beta sheets. Hence, we propose that HEV-protease has characteristics of "Papain-like cysteine protease," as determined through structural homology, active site residues and class-specific inhibition. However, conclusive nature of the enzyme remains to be established.

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Hepatitis E Virus Cysteine Protease Has Papain Like Properties Validated by in silico Modeling and Cell-Free Inhibition Assays.

Chikungunya Virus (CHIKV) is having a major impact on humans with potentially life-threatening and debilitating arthritis. The lack of a specific antiviral drug against the CHIKV disease has created an alarming situation to identify or develop potent chemical molecules for its remedial measures. Antiviral therapies for viral diseases are generally expensive and have adverse side effects. Plant-based antiviral natural compounds are the most suitable and best alternative of current antiviral drugs because of less toxicity. In the present study, non-structural protein 3 macrodomain (nsP3MD) of the CHIKV that is essential for virus replication has been selected for anti CHIKV drug target. The compounds were identified using molecular docking, virtual screening and further evaluated by molecular dynamics (MD) simulation studies. The binding mechanism of each compound was analyzed considering the stability and energetic parameter. We have found six plant-based natural antiviral compounds Baicalin, Rutaecarpine, Amentoflavone, Apigetrin, Luteoloside, and Baloxavir as strong inhibitors of nsP3MD of CHIKV. ADMET prediction and target analysis of the selected compounds showed drug likeliness of these compounds. MD simulation studies indicated energetically favorable complex formation between nsP3MD and the selected antiviral compounds. Furthermore, the structural effects on these substitutions were analyzed using the principles of each trajectory, which validated the interaction studies. Our analysis suggests a very high probability of these compounds to inhibit nsP3MD of CHIKV and could be evaluated for Chikungunya fever drug development. Communicated by Ramaswamy H. Sarma.

In silico identification of natural antiviral compounds as a potential inhibitor of chikungunya virus non-structural protein 3 macrodomain.

Cold shock domain (CSD) proteins with nucleic acid binding properties are well conserved from bacteria to higher organisms. In bacteria, the cold shock proteins (CSPs) are single domain RNA chapero...

Meenakshi Chaudhary

Papers

In silico identification and validation of natural antiviral compounds as potential inhibitors of SARS-CoV-2 methyltransferase.

Hepatitis E Virus Cysteine Protease Has Papain Like Properties Validated by in silico Modeling and Cell-Free Inhibition Assays.

In silico identification of natural antiviral compounds as a potential inhibitor of chikungunya virus non-structural protein 3 macrodomain.

In silico identification and evaluation of Bacillus subtilis cold shock protein B (cspB)-like plant RNA chaperones