In silico approach to understand the epigenetic mechanism of SARS-CoV-2 and its impact on the environment

In Silico molecular docking and dynamic analysis of natural compounds against major non-structural proteins of SARS-COV-2

COVID-19 has infected millions and significantly affected the global economy and healthcare systems. Despite continuous lockdowns, symptomatic management with currently available medications, and numerous vaccination drives, it is still far more difficult to control. Against COVID-19 infection, the pressure to develop vaccines and drugs has led to using some currently available medications like remdesivir, azithromycin, hydroxychloroquine and ritonavir. Understanding the importance and potential of harmless molecules to tackle SARS-COV-2, we designed the present study to identify potential natural phytocompounds. In the present study, we docked natural compounds and standard drugs against SARS-COV-2 proteins: papain-like protease, main protease and helicase. ADME/T and ProTox-II analyses were used to determine the toxicity of phytocompounds and drugs. The docking analysis revealed that podophyllotoxin gave the highest binding affinity scores of -8.1, -7.1 and -7.4 kcal/mol against PLpro, Mpro and helicase, respectively. Among the control drugs, doxycycline hydrochloride showed the highest binding affinity of -10.5, -8.4 and -8.8 kcal/mol against PLpro, Mpro and helicase. The results of this study revealed that podophyllotoxin and doxycycline hydrochloride could be promising inhibitors against SARS-Cov-2. Molecular dynamic simulations were executed for the best docked (PLpro-podophyllotoxin) complex, and the results displayed stable conformation and convergence. Energy plot results predicted a global minima average energy of -95 kcal/mol and indicated podophyllotoxin's role in stabilizing protein and making it compact and complex. FarPPI server used MM/GBSA approach to determine free binding affinity, and helicase-gallic acid complex showed the highest affinity, respectively. Therefore, it can be concluded that there is still a need for in vitro and in vivo studies to support further and validate these findings and validate these findings.Communicated by Ramaswamy H. Sarma.

In silico Analysis of ACE2 Receptor to Find Potential Herbal Drugs in COVID-19 Associated Neurological Dysfunctions

COVID-19 mainly causes the collapse of the pulmonary system thereby causing a dearth of oxygen in the human body. Patients infected with this viral disease have been reported to experience various signs and symptoms associated with brain dysfunction, from the feeling of vagueness to loss of smell and taste to severe strokes. These neurological problems have been reported by younger COVID-19 infected patients mainly in their thirties and forties. Various researchers from around the globe have discerned numerous other brain dysfunctions, such as headache, dizziness, numbness, major depressive disorder, anosmia, encephalitis, febrile seizures, and Guillain-Barre syndrome. The involvement of the CNS by this viral infection has been predicted to be for a longer period of time, even if the patient recovers from COVID-19. The neuronal cell damage caused by COVID-19 is a potent factor responsible for cognitive, behavioral, and psychological problems among its sufferers. The hypoxic conditions can also trigger the formation of beta-amyloid plaques and tau-tangles and thus the virus can even induce Alzheimer’s in patients in the near future. The virus affects the brain directly, thereby causing encephalitis. This pandemic has also been shown to have a negative psychological toll on people. This research aims to highlight the brain dysfunction associated with the ACE2 receptor that is known to be a crucial player in the COVID-19 pandemic using genetic networking approaches. Furthermore, we have identified herbal drug candidates that bind to the ACE2 receptor in order to identify potential treatments for the neurological manifestations of COVID-19.

Network Pharmacology, Molecular Docking and Molecular Dynamics Simulation Studies of the Molecular Targets and Mechanisms of ChuanKeZhi in the Treatment of COVID-19

Objectives: Coronavirus disease 2019 (COVID-19) has had a global impact and is spreading quickly. ChuanKeZhi injection (CKZI) is widely used in asthma patients. In this paper, we aimed to explore active compounds of CKZ and determine potential mechanisms against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through network pharmacology, molecular docking and dynamic simulation studies. Materials and Methods: We used the Systematic Pharmacology Database and Analysis Platform of Traditional Chinese Medicine (TCMSP) to screen active compounds and potential target proteins of CKZ. COVID-19 target genes were screened via the American National Center for Biotechnology Information (NCBI) gene database and human gene database (GeenCards). The protein interaction network was constructed by the Protein Interaction Network Database (Search Tool for the Retrieval of Interacting Genes/Proteins (STRING)) platform. GO enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by the Metascape database. The main active compounds of CKZ were docked with angiotensin-converting enzyme 2 (ACE2), spike protein S1, and SARS-CoV-2-3CL pro and also docked with hub targets. We performed molecular dynamics (MD) simulation studies for validation. Results: We finally obtained 207 CKZ potential targets and 4681 potential COVID-19 targets. Key targets included mainly AKT1, TNF, IL6, VEGFA, IL1B, TP53, JUN, CASP3, etc. There were 217 Gene Ontology (GO) items in the GO enrichment analysis ( p < 0.05). The main KEGG pathways included the advanced glycation end products (AGE)- receptor for AGE (RAGE) signalling pathway in diabetic complications, rheumatoid arthritis, chemical carcinogenesis-receptor activation, alcoholic liver disease, etc. Molecular docking and dynamics simulation studies both exhibited great binding capacity. Conclusions: Network pharmacology, molecular docking and dynamics simulation studies were used to identify the potential and key targets, pharmacological functions, and therapeutic mechanisms of CKZI in the treatment of COVID-19. CKZI may be an effective and safe drug in COVID-19 treatment. However, further work is needed for validation.

Combined Network Pharmacology, Molecular Docking, and Experimental Verification Approach to Investigate the Potential Mechanisms of Polydatin Against COVID-19

Background: Coronavirus disease 2019 (COVID-19) has posed a serious threat to human health and there is an urgent need for drug development. In this study, we explored the potential mechanisms underlying the efficacy of polydatin against COVID-19. Methods: A combined approach of network pharmacology, molecular docking, and experimental verification were employed in this study. Potential targets of polydatin for treating COVID-19 were obtained from multiple drug and disease databases. Protein–protein interaction and enrichment analyses were performed to predict the potential mechanism of action of polydatin against COVID-19. The binding potential of polydatin and key targets was evaluated through molecular docking. Furthermore, experimental methods including flow cytometry and luciferase assay were used to validate the results of computational analyses. Results: The main diseases identified as polydatin targets included metabolic diseases, lung diseases, inflammation, infectious diseases, and tumors. Polydatin may be used to treat COVID-19 through interventions that alter the immune and inflammatory responses, including IL-17 signaling pathway, T-cell activation, cytokines and inflammatory response, lipopolysaccharide-mediated signaling pathway, as well as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) innate immunity evasion and cell-specific immune response. Polydatin can potentially bind to the target proteins related to COVID-19, such as SARS-CoV-2 Mpro, RdRp, and human angiotensin-converting enzyme 2 (ACE2), while directly exerting its regulatory or therapeutic functions. The experimental results showed that polydatin decreased the infectivity of the SARS-CoV-2 spike pseudovirus in HEK293T-ACE2 cells. Accordingly, polydatin may retard the entry of SARS-CoV-2 into cells by competitively binding to human ACE2. Conclusion: The potential targets and signaling pathways of polydatin against COVID-19 were preliminarily identified. The findings may benefit the development and application of polydatin as a treatment for COVID-19.

Ayurvedic Medicinal Plants Against COVID-19: An In Silico Analysis

Even after one and a half years since the outbreak of COVID-19, its complete and effective control is still far from being achieved despite vaccination drives, symptomatic management with available drugs, and wider lockdowns. This has inspired researchers to screen potential phytochemicals from medicinal plants against SARS-CoV-2, adopting a bio-informatics approach. The current study aimed to assess anti-viral activity of the phytochemicals derived from Ayurvedic medicinal plants against SARS-CoV-2 drug targets [3-chymotrypsin-like protease (3CLpro) and RNA dependent RNA polymerase (RdRp)] using validated in silico methods.3D Structures of 196 phytochemicals from three Ayurvedic plants were retrieved from PubChem and KNApSAcK databases and screened for Absorption Distribution Metabolism Excretion and Toxicity(ADMET) to predict drug-likeness. The phytochemicals were subjected to molecular docking and only three showed promise: Acetovanillonewith a binding affinity of −4.7Kcal/mol with RdRp and −4.1 Kcal/mol with 3CL pro; myrtenol with equivalent values of −4.3 Kcal/mol with RdRP and −3.2 Kcal/mol with 3CLpro; and nimbochalcin with equivalent values of −5.0Kcal/mol with RdRp and −4.9 Kcal/mol with 3CLpro. Molecular dynamics simulation (50ns) analysis was made of 3CLpro and RdRp using Autodock Vina 1.1.2 software and VMD software. After ADMET analysis, 78 phytochemicals were found suitable for molecular docking. Three, namely acetovanillone, myrtenol and nimbochalcin from Picrorhiza kurroa, Azadirachta indica and Cyperus rotundus,respectively,exhibited good binding affinity with 3CLproand RdRp of SARS-CoV-2. Interaction analysis, molecular dynamics simulations and MM-PBSA calculations were executed for two complexes, acetovanillone_RdRp and myrtenol_3CL pro.Acetovanillone_RdRpcomplex did not display any structural change after MD simulation as compared to myrtenol_3CL pro. The overall stability of acetovanillone_6NUR was 154.7 kJ/mol, and for myrtenol_1UJ1 90.5 kJ/mol. In silico analysis revealed that acetovanillone ( Picrorhiza kurroa) and myrtenol ( Cyperus rotundus) possess anti SARS-CoV-2 activity. Further studies are needed to validate their efficacy in biological models.

COVIDium: a COVID-19 resource compendium

The severe acute respiratory syndrome coronavirus 2 that causes coronavirus disease 2019 (COVID-19) disrupted the normal functioning throughout the world since early 2020 and it continues to do so. Nonetheless, the global pandemic was taken up as a challenge by researchers across the globe to discover an effective cure, either in the form of a drug or vaccine. This resulted in an unprecedented surge of experimental and computational data and publications, which often translated their findings in the form of databases (DBs) and tools. Over 160 such DBs and more than 80 software tools were developed, which are uncharacterized, unannotated, deployed at different universal resource locators and are challenging to reach out through a normal web search. Besides, most of the DBs/tools are present on preprints and are either underutilized or unrecognized because of their inability to make it to top Google search hits. Henceforth, there was a need to crawl and characterize these DBs and create a compendium for easy referencing. The current article is one such concerted effort in this direction to create a COVID-19 resource compendium (COVIDium) that would facilitate the researchers to find suitable DBs and tools for their research studies. COVIDium tries to classify the DBs and tools into 11 broad categories for quick navigation. It also provides end-users some generic hit terms to filter the DB entries for quick access to the resources. Additionally, the DB provides Tracker Dashboard, Neuro Resources, references to COVID-19 datasets and protein-protein interactions. This compendium will be periodically updated to accommodate new resources. Database URL: The COVIDium is accessible through http://kraza.in/covidium/.

Analysis of the Active Components and Mechanism of Three Prescriptions in the Treatment of COVID-19 Via Network Pharmacology and Molecular Docking

Purpose: Prescriptions of Han-Shi-Yu-Fei (HSYF), Han-Shi-Zu-Fei (HSZF), and Yi-Du-Bi-Fei (YDBF) were effective in treating COVID-19. Based on network pharmacology and molecular docking, overlapping Traditional Chinese medicines (TCMs), their active components, and core targets were explored in this study. Methods: First, the overlapping TCMs and their active components were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) by evaluating Oral Bioactivity (OB) and Drug Likeness (DL). The overlapping targets of potential components and COVID-19 were collected by SwissTargetPrediction, Gene Cards, and Venn 2.1.0 databases. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were analyzed via DAVID6.8.1 database. Through comprehensive analysis of the “prescriptions-TCMs-components” (P-T-C), “components-targets-pathways” (C-T-P) and “protein–protein interaction” (PPI) networks constructed by Cytoscape 3.7.1 software, the active components and core targets were obtained. Finally, the binding energies of these components with ACE2 and SARS-CoV-2 3CL were analyzed by AutDockTools-1.5.6 and PyMOL software. Results: In all, five overlapping TCMs, 40 potential active components, and 47 candidate targets were obtained and analyzed in these prescriptions. There were 288 GO entries ( P < 0.05), including 211 biological process (BP), 40 cell composition (CC), and 37 molecular function (MF) entries. Most of the 105 KEGG pathways ( P < 0.05) were involved with viral infection and inflammation. Through “PPI” and “C-T-P” networks, the core targets (EGFR, PTGS2, CDK2, GSK3B, PIK3R1, and MAPK3) and active components (Q27134551, acanthoside B, neohesperidin, and irisolidone) with high degrees were obtained. Molecular docking results showed that the above-mentioned four components could inhibit the binding of ACE2 and SARS-COV-2 3CL to protect against COVID-19. Conclusion: In this study, the active components and core targets of three prescriptions in the treatment of COVID-19 were elaborated by network pharmacology and molecular docking, providing a reference for their applications.