Chromone-embedded peptidomimetics and furopyrimidines as highly potent SARS-CoV-2 infection inhibitors: docking and MD simulation study

BACKGROUND

COVID-19 is a respiratory illness caused by SARS-CoV-2. Pharmaceutical companies aim to control virus spread through effective drugs. This study investigates chromone compound derivatives' ability to inhibit viral entry and prevent replication.

METHOD

This study investigated the inhibitory effect of chromone-embedded peptidomimetics and furopyrimidines on 7BZ5 from Severe Acute Respiratory Syndrome CoV-2, Homo sapiens, and 6LU7 from Bat SARS-like CoV using molecular docking. The crystal structure of these proteins was obtained from the Protein Data Bank, and the inhibition site was determined using ligand binding interaction options. The 3D structure was protonated and energetically minimised using MOE software. Chromone derivatives were designed in three dimensions, and their energy was minimised using MOE 2019. The molecular drug-likeness was calculated using SwissADME, Lipinski and Benigni-Bossa's rule, and toxicity was calculated using Toxtree v3.1.0 software. Compounds with pharmacological properties were selected for molecular docking, and interactions were assessed using MOE 2019. MD simulations of Mpro-ch-p complexes were performed to evaluate root mean square fluctuations (RMSF) and measure protein stability.

RESULT

The pharmacokinetic tests revealed that chromone derivatives of the peptidomimetic family have acceptable pharmacokinetic activity in the human body. Some compounds, such as Ch-p1, Ch-p2, Ch-p6, Ch-p7, Ch-p12, and Ch-p13, have pronounced medicinal properties. Molecular docking revealed high affinity for binding to SARS-CoV-2 protease. Ch-p7 had the highest binding energy, likely due to its inhibitory property. A 10 ns molecular dynamics study confirmed the stability of the protein-ligand complex, resulting in minimal fluctuations in the system's backbone. The MM-GBSA analysis revealed free energies of binding of - 19.54 kcal/mol.

CONCLUSIONS

The study investigated the inhibition of viral replication using chromone derivatives, finding high inhibitory effects in the peptidomimetic family compared to other studies.

Investigating the impact of CO2 emissions on the COVID-19 pandemic by generalized linear mixed model approach with inverse Gaussian and gamma distributions

Carbon dioxide (CO2) rate within the atmosphere has been rising for decades due to human activities especially due to usage of fuel types such as coal, cement, flaring, gas, oil, etc. Especially in 2020, COVID-19 pandemic caused major economic, production, and energy crises all around the world. As a result of this situation, there was a sharp decrease in the global CO2 emissions depending on the fuel types used during this pandemic. The aim of this study was to explore the effects of “CO2 emissions due to the fuel types” on “percentage of deaths in total cases” attributed to the COVID-19 pandemic using generalized linear model and generalized linear mixed model (GLMM) approaches with inverse Gaussian and gamma distributions, and also to obtain global statistical inferences about 169 World Health Organization member countries that will disclose the impact of the CO2 emissions due to the fuel types during this pandemic. The response variable is taken as “percentage of deaths in total cases attributed to the COVID-19 pandemic” calculated as “(total deaths/total confirmed cases attributed to the COVID-19 pandemic until December 31, 2020)*100.” The explanatory variables are taken as “production-based emissions of CO2 from different fuel types,” measured in tonnes per person, which are “coal, cement, flaring, gas, and oil.” As a result of this study, according to the goodness-of-fit test statistics, “GLMM approach with gamma distribution” called “gamma mixed regression model” is determined as the most appropriate statistical model for investigating the impact of CO2 emissions on the COVID-19 pandemic. As the main findings of this study, 1 t CO2 emissions belonging to the fuel types “cement, coal, flaring, gas, and oil” per person cause increase in deaths in total cases attributed to the COVID-19 pandemic by 2.8919, 2.6151, 2.5116, 2.5774, and 2.5640%, respectively.

Metallo-antiviral aspirants: Answer to the upcoming virusoutbreak

In light of the current SARS-CoV-2 outbreak, about one million research papers (articles, reviews, communications, etc.) were published in the last one and a half years. It was also noticed that in the past few years; infectious diseases, mainly those of viral origin, burdened the public health systems worldwide. The current wave of the Covid-19 pandemic has unmasked critical demand for compounds that can be swiftly mobilized for the treatment of re-emerging or emerging viral infections. With the potential chemical and structural characteristics of organic motifs, the coordination compounds might be a promising and flexible option for drug development. Their therapeutic consequence may be tuned by varying metal nature and its oxidation number, ligands characteristics, and stereochemistry of the species formed. The emerging successes of cisplatin in cancer chemotherapy inspire researchers to make new efforts for studying metallodrugs as antivirals. Metal-based compounds have immense therapeutic potential in terms of structural diversity and possible mechanisms of action; therefore, they might offer an excellent opportunity to achieve new antivirals. This review is an attempt to summarize the current status of antiviral therapies against SARS-CoV-2 from the available literature sources, discuss the specific challenges and solutions in the development of metal-based antivirals, and also talk about the possibility to accelerate discovery efforts in this direction.

Screening of Phyllanthus niruri Leaves Phytoconstituents for Antiviral and Antibacterial Activity by Molecular Docking Studies

The genus Phyllanthus belongs to one of the largest plant families, the Phyllantaceae (L.). Phyllanthus niruri is an annual perennial herb that grows in tropical Asia, America, China, and the islands of the Indian Ocean. Numerous alkaloids, steroids, flavonoids, lignans, coumarins, polyphenols, and lipids are present in Phyllanthus. The effects of plants have been studied for a variety of purposes, including their antioxidant (Giribabu et al., Evid Based Complement Alternat Med, 2014), anti-inflammatory (Porto et al., Revista Brasileira de Pharmacognosy, 2013), antinociceptive (Sathisha et al., Indian Drugs, 2009), analgesic (Mostofa et al., BMC Complement Altern Med, 2017), antiulcer (Mali et al., Biomed Aging Pathol, 2011), antiarthritic (Obidike and Salawu, Planta Medica, 2010), antiplasmodial (Shilpa et al., Environ Dis, 2018), immunomodulatory (Manikkoth et al., Anticonvulsant activity of Phyllanthus amarus in experimental animal models), anticonvulsant (Wasnik et al., Int J Pharm Sci Rev Res, 2014), antidepressant (Venkateswaran et al., Effects of an extract from Phyllanthus niruri on hepatitis B and woodchuck hepatitis viruses: In vitro and in vivo studies (antiviral agent/Marmota monax/DNA polymerase/hepatitis B surface antigen/woodchuck hepatitis surface antigen). In Hepatitis B and The Prevention of Primary Cancer of The Liver: Selected Publications of Baruch S Blumberg, pp 535-539), antiviral (Venkateswaran et al., Effects of an extract from Phyllanthus niruri on hepatitis B and woodchuck hepatitis viruses: In vitro and in vivo studies (antiviral agent/Marmota monax/DNA polymerase/hepatitis B surface antigen/woodchuck hepatitis surface antigen). In Hepatitis B and The Prevention of Primary Cancer of The Liver: Selected Publications of Baruch S Blumberg, pp 535-539), antitumor (Sharma et al., Asian Pac J Cancer Prev, 2009), hyperlipidemia (Khanna et al., J Ethnopharmacol, 2002), and antifertility (Ezeonwu, Inquiries J, 2011). For additional docking investigations with distinct proteins, the leaf chemicals are assessed, that is, the crystal structure of serine protease hepsin in complex with inhibitor [PDB ID:5 CE1] for antiviral activity human topoisomerase II beta in complex with DNA and etoposide [PDB ID:3QX3] and crystal structure of E. coli GyraseB 24 kDa in complex with 4-(4-bromo-1H-pyrazol-1-yl)-6-[(ethylcarbamoyl)amino]-N-(pyridin-3-yl) pyridine-3-carboxamide [PDB ID: 6F86] for antibacterial activity and have been selected. To evaluate the in silico results and grading of virtual screening, or molecular docking, ritonavir antiviral activity and ampicillin for antibacterial activity were used as a benchmark.

Screening of Phyllanthus niruri Root Phytoconstituents for Antibacterial, Antifungal, Anticancer, and Antiviral Activities by Molecular Docking Studies

The systematic exploitation of the structural variety of natural products is made possible by docking studies, which have been shown to be a crucial technique. This study's goal was to evaluate various activities for the chemicals in the root portion of Phyllanthus niruri. This plant's constituents are active in a variety of ways. In order to develop drugs, molecules with such a framework have been utilized as the lead. Schrodinger Maestro (v13.0) software was used to conduct a molecular docking analysis of root components with certain proteins linked to the illnesses. In comparison to commercially available conventional medications, molecular docking data also demonstrated greater scores. For additional docking investigations with distinct proteins, the root chemicals are assessed, that is, crystal structure of serine protease hepsin in complex with inhibitor [PDB ID:5 CE1] for antiviral activity, human topoisomerase II beta in complex with DNA and etoposide [PDB ID:3QX3], and crystal structure of E. coli GyraseB 24 kDa in complex with 4-(4-bromo-1H-pyrazol-1-yl)-6-[(ethylcarbamoyl)amino]-N-(pyridin-3-yl) pyridine-3-carboxamide [PDB ID: 6F86] for antibacterial activity, Cytochrome P450 14 alpha-sterol demethylase (CYP51) from Mycobacterium tuberculosis in complex with fluconazole [PDB ID:1EA1], and structure of yeast Sec14p with a picolinamide compound [PDB ID:6F0E] for antifungal activity and synthesis and biological evaluation of novel selective androgen receptor modulators (SARMs). Part II: Optimization of 4-(pyrrolidin-1-yl) benzonitrile derivatives [PDB ID: 5T8E] and Human Cytochrome P450 CYP17A1 in complex with Abiraterone [PD B ID:3RUK] for anticancer activity have been selected. Ritonavir's antiviral activity, ampicillin's ability to treat bacterial infections, fluconazole's ability to treat fungi, and dacarbazine's ability to treat cancer were utilized as benchmarks to assess the in silico outcomes and grading of virtual screening or molecular docking.

In-silico docking studies of selected phytochemicals against papain like protease of SARS-Cov-2

The SARS-Cov-2 virus, which is evolving continuously and causing adverse effects throughout the world, needs an effective drug molecule for its treatment. There are several receptors of SARS Cov-2 which are targeted for its inhibition by many lead molecules both in-vitro and in-vivo. Papain like Protease (PLpro) is one of the two SARS-Cov-2 proteases that can be used as a drug target for SARS Cov-2. It is a coronavirus enzyme that plays a role in the cleavage and maturation of viral polyproteins, assembly of the replicase-transcriptase complex and disruption of host responses. PLpro has also been linked to the cleavage of proteinaceous post translational modifications on host proteins as a means of evading antiviral immune responses. Structure-based drug discovery can be one of the effective methods to screen for various molecules against the target receptors. In this study, PLpro of SARS CoV-2 was chosen as the target for docking. Forty phytochemicals from various plant sources and four synthetic drugs have been screened for their inhibitory potential against PLpro using AutoDock Vina. Phytochemicals such as Tinosponone, Rhoifolin, Rosmanol, Berberin, Nimbin and two other existing drugs Elbasvir and Declatasvir showed higher inhibitory potential in terms of higher binding affinities. ADME and toxicity analysis were also performed to predict the pharmacokinetics and drug likeliness properties. It was concluded from the study that Tinosponone possesss potential inhibitor property of papain-like proteases (PLpro) of SARS CoV-2. Tinosponone from the plant Tinospora cordifolia had a binding affinity of - 9.3 kcal/mol and obeyed the Lipinski rules, making it an effective lead molecule for treating SARS CoV-2. Molecular Dynamics simulation of Tinosponone with PLpro has proved the stability and validity of the binding with RMSD value in range of 0.2 nm when it was run for 50 ns using GROMACS. Therefore, Tinosponone could be considered as a potential inhibitor of PLpro of SARS CoV-2.

Repurposing of potential antiviral drugs against RNA-dependent RNA polymerase of SARS-CoV-2 by computational approach

The high incidences of COVID-19 cases are believed to be associated with high transmissibility rates, which emphasizes the need for the discovery of evidence-based antiviral therapies for curing the disease. The rationale of repurposing existing classes of antiviral small molecule therapeutics against SARS-CoV-2 infection has been expected to accelerate the tedious and expensive drug development process. While Remdesivir has been recently approved to be the first treatment option for specific groups of COVID-19 patients, combinatory therapy with potential antiviral drugs may be necessary to enhance the efficacy in different populations. Hence, a comprehensive list of investigational antimicrobial drug compounds such as Favipiravir, Fidaxomicin, Galidesivir, GC376, Ribavirin, Rifabutin, and Umifenovir were computationally evaluated in this study. We performed in silico docking and molecular dynamics simulation on the selected small molecules against RNA-dependent RNA polymerase, which is one of the key target proteins of SARS-CoV-2, using AutoDock and GROMACS. Interestingly, our results revealed that the macrocyclic antibiotic, Fidaxomicin, possesses the highest binding affinity with the lowest energy value of -8.97 kcal/mol binding to the same active sites of RdRp. GC376, Rifabutin, Umifenovir and Remdesivir were identified as the next best compounds. Therefore, the above-mentioned compounds could be considered good leads for further preclinical and clinical experimentations as potentially efficient antiviral inhibitors for combination therapies against SARS-CoV-2.

A review on computer-aided chemogenomics and drug repositioning for rational COVID-19 drug discovery

Application of materials capable of energy harvesting to increase the efficiency and environmental adaptability is sometimes reflected in the ability of discovery of some traces in an environment-either experimentally or computationally-to enlarge practical application window. The emergence of computational methods, particularly computer-aided drug discovery (CADD), provides ample opportunities for the rapid discovery and development of unprecedented drugs. The expensive and time-consuming process of traditional drug discovery is no longer feasible, for nowadays the identification of potential drug candidates is much easier for therapeutic targets through elaborate in silico approaches, allowing the prediction of the toxicity of drugs, such as drug repositioning (DR) and chemical genomics (chemogenomics). Coronaviruses (CoVs) are cross-species viruses that are able to spread expeditiously from the into new host species, which in turn cause epidemic diseases. In this sense, this review furnishes an outline of computational strategies and their applications in drug discovery. A special focus is placed on chemogenomics and DR as unique and emerging system-based disciplines on CoV drug and target discovery to model protein networks against a library of compounds. Furthermore, to demonstrate the special advantages of CADD methods in rapidly finding a drug for this deadly virus, numerous examples of the recent achievements grounded on molecular docking, chemogenomics, and DR are reported, analyzed, and interpreted in detail. It is believed that the outcome of this review assists developers of energy harvesting materials and systems for detection of future unexpected kinds of CoVs or other variants.

Probing the Immune System Dynamics of the COVID-19 Disease for Vaccine Designing and Drug Repurposing Using Bioinformatics Tools

The pathogenesis of COVID-19 is complicated by immune dysfunction. The impact of immune-based therapy in COVID-19 patients has been well documented, with some notable studies on the use of anti-cytokine medicines. However, the complexity of disease phenotypes, patient heterogeneity and the varying quality of evidence from immunotherapy studies provide problems in clinical decision-making. This review seeks to aid therapeutic decision-making by giving an overview of the immunological responses against COVID-19 disease that may contribute to the severity of the disease. We have extensively discussed theranostic methods for COVID-19 detection. With advancements in technology, bioinformatics has taken studies to a higher level. The paper also discusses the application of bioinformatics and machine learning tools for the diagnosis, vaccine design and drug repurposing against SARS-CoV-2.

Molecular docking and dynamic simulations of Cefixime, Etoposide and Nebrodenside A against the pathogenic proteins of SARS-CoV-2

The catastrophe of the coronavirus continues from one part of the world to another, and hardly a country is left without its devastations. Millions of people were infected and several hundred thousand died of the COVID-19 pandemic across the world. There is no clear targeted drug therapy available for the treatment of the patients. The discovery of vaccines is not enough to curtail its spread and disastrous implications. An instantly qualifying approach is needed to utilize the current drugs and isolated compounds. The purpose of this work is to determine potent inhibitors against the target proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). For this purpose, molecular docking study of pathogenic spike glycoproteins (S), nucleocapsid phosphoprotein (N), an envelope protein (E), two drugs i.e., cefixime, etoposide, and a previously isolated compound nebrodenside A is performed. Promising results were obtained via complimentary analysis of molecular dynamics (MD) simulations performed for the complexes of three proteins with etoposide drug. Minimum values were recorded for the docking scores and binding energies of the complexes. These results were further supported by the RMSD, RMSF data for the stability of proteins and ligands. Additionally, ligand properties and ligand-protein contacts were also explained with histograms of every simulation trajectory. The computational studies confirmed that cefixime, etoposide, and nebrodenoside A can be used as potent inhibitors of COVID-19. Nevertheless, additional experimental investigations and validation of the selected candidates are mandatory to confirm their applicability for clinical trials.

Molybdenum Carbonyl Complexes with Benzimidazole Derivatives Against SARS-CoV-2 by Molecular Docking and DFT/TDDFT Methods

Benzimidazole derivative molecules attract attention of scientists due to their bioactivities. The dramatic changes in recorded activities according to the type and position of the substituents motivate synthesis and analysis of new molecules. Commercial benzimidazole-based molecules have been used in therapeutic procedures. It is known that the activities of metal complexes with benzimidazole derivative ligands have different activities when compared to the benzimidazole main structure. Nowadays, one of the most important health problems is COVID-19, which caused the pandemic that we are still experiencing. Although vaccine studies are important to overcome acute problems, regarding the possible post-vaccination adverse effects, the need for new drugs against the virus is obvious. Considering the urgency and the limited facilities during the pandemic, preliminary in silico studies of candidate molecules are essential. In this study, {[bis-(N-benzylbenzimidazole)] tetracarbonylmolybdenum}, {[bis-(N-4-chlorobenzylbenzimidazole)] tetracarbonylmolybdenum} and {[bis-(N-4-methoxybenzylbenzimidazole)] tetracarbonylmolybdenum} were synthesized and characterized. The optimization and the structural analysis of these molecules were performed by DFT/TDDFT methods. The molecules were docked into SARS coronavirus main peptidase (PDB ID: 2gtb), COVID-19 main protease in complex with Z219104216 (PDB ID: 5r82), COVID-19 main protease in complex with an inhibitor N3 (PDB ID: 6lu7) and Papain-like protease of SARS-CoV-2 (PDB ID: 6w9c) crystal structures for evaluation of their anti-viral activity.

In Silico Modeling as a Perspective in Developing Potential Vaccine Candidates and Therapeutics for COVID-19

The potential of computational models to identify new therapeutics and repurpose existing drugs has gained significance in recent times. The current ‘COVID-19’ pandemic caused by the new SARS CoV2 virus has affected over 200 million people and caused over 4 million deaths. The enormity and the consequences of this viral infection have fueled the research community to identify drugs or vaccines through a relatively expeditious process. The availability of high-throughput datasets has cultivated new strategies for drug development and can provide the foundation towards effective therapy options. Molecular modeling methods using structure-based or computer-aided virtual screening can potentially be employed as research guides to identify novel antiviral agents. This review focuses on in-silico modeling of the potential therapeutic candidates against SARS CoVs, in addition to strategies for vaccine design. Here, we particularly focus on the recently published SARS CoV main protease (Mpro) active site, the RNA-dependent RNA polymerase (RdRp) of SARS CoV2, and the spike S-protein as potential targets for vaccine development. This review can offer future perspectives for further research and the development of COVID-19 therapies via the design of new drug candidates and multi-epitopic vaccines and through the repurposing of either approved drugs or drugs under clinical trial.