The interaction of the bioflavonoids with five SARS-CoV-2 proteins targets: An in silico study

Alpha-cyperone mitigates renal ischemic injury via modulation of HDAC-2 expression in diabetes: Insights from molecular dynamics simulations and experimental evaluation

Chronic diabetes mellitus is reported to be associated with acute kidney injury. The enzyme histone deacetylase-2 (HDAC-2) was found to be upregulated in diabetes-related kidney damage. Alpha-cyperone (α-CYP) is one of the active ingredients of Cyperus rotundus that possesses antioxidant and anti-inflammatory effects. We evaluated the effect of α-CYP on improving oxidative stress and tissue inflammation following renal ischemia/reperfusion (I/R) injury in diabetic rats. The effect of α-CYP on HDAC-2 expression in renal homogenates and in the NRK-52 E cell line was evaluated following renal I/R injury and high glucose conditions, respectively. Molecular docking was used to investigate the binding of α-CYP with the HDAC-2 active site. Both renal function and oxidative stress were shown to be impaired in diabetic rats due to renal I/R injury. Significant improvements in kidney/body weight ratio, creatinine clearance, serum creatinine, blood urea nitrogen (BUN), and uric acid were observed in diabetic rats treated with α-CYP (50 mg/kg) two weeks prior to renal I/R injury. α-CYP treatment also improved histological alterations in renal tissue and lowered levels of malondialdehyde, myeloperoxidase, and hydroxyproline. Treatment with α-CYP suppressed the increased HDAC-2 expression in the renal tissue of diabetic rats and in the NRK-52 E cell line. The molecular docking reveals that α-CYP binds to HDAC-2 with good affinity, ascertained by molecular dynamics simulations and binding free energy analysis. Overall, our data suggest that α-CYP can effectively prevent renal injury in diabetic rats by regulating oxidative stress, tissue inflammation, fibrosis and inhibiting HDAC-2 activity.

An efficient eco-friendly, simple, and green synthesis of some new spiro-N-(4-sulfamoyl-phenyl)-1,3,4-thiadiazole-2-carboxamide derivatives as potential inhibitors of SARS-CoV-2 proteases: drug-likeness, pharmacophore, molecular docking, and DFT exploration

INTRODUCTION

The coronavirus disease 2019 (COVID-19) pandemic has caused a global health crisis. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious virus that can cause severe respiratory illness. There is no specific treatment for COVID-19, and the development of new drugs is urgently needed.

PROBLEM STATEMENT

The SARS-CoV-2 main protease (Mpro) enzyme is a critical viral enzyme that plays a vital role in viral replication. The inhibition of Mpro enzyme can be an effective strategy for developing new COVID-19 drugs.

METHODOLOGY

An efficient operationally simple and convenient green synthesis method had been done towards a series of novel spiro-N-(4-sulfamoylphenyl)-2-carboxamide derivatives, in ethanol at room temperature in green conditions, up to 90% yield. The molecular structures of the synthesized compounds were verified using spectroscopic methods.The title compounds were subjected to in silico analysis, including Lipinski's rule and ADMET prediction, in addition to pharmacophore modeling and molecular docking against the active site of SARS-CoV-2 target main protease (Mpro) enzyme (6LU7). Furthermore, both of the top-ranked compounds (5 and 6) and the standard Nirmatrelvir were subjected to DFT analysis.

FINDINGS

The synthesized compounds exhibited good binding affinity to SARS-CoV-2 Mpro enzyme, with binding energy scores ranging from - 7.33 kcal/mol (compound 6) and - 7.22kcal/mol (compound 5) to - 6.54 kcal/mol (compounds 8 and 9). The top-ranked compounds (5 and 6) had lower HOMO-LUMO energy difference (ΔE) than the standard drug Nirmatrelvir. This highlights the potential and relevance of charge transfer at the molecular level.

RECOMMENDATION

These findings suggest that the synthesized spiro-N-(4-sulfamoylphenyl)-2-carboxamide derivatives could be potential candidates for COVID-19 drug development. To confirm these drugs' antiviral efficacy in vivo, more research is required. With very little possibility of failure, this proven method could aid in the search for the SARS-CoV-2 pandemic's desperately needed medications.

Plant flavonoid inhibition of SARS-CoV-2 main protease and viral replication

Plant-based flavonoids have been evaluated as inhibitors of β-coronavirus replication and as therapies for COVID-19 on the basis of their safety profile and widespread availability. The SARS-CoV-2 main protease (Mpro) has been implicated as a target for flavonoids in silico. Yet no comprehensive in vitro testing of flavonoid activity against SARS-CoV-2 Mpro has heretofore been performed. We screened 1,019 diverse flavonoids for their ability to inhibit SARS-CoV-2 Mpro. Multiple structure-activity relationships were identified among active compounds such as enrichment of galloylated flavonoids and biflavones, including multiple biflavone analogs of apigenin. In a cell-based SARS-CoV-2 replication assay, the most potent inhibitors were apigenin and the galloylated pinocembrin analog, pinocembrin 7-O-(3''-galloyl-4'',6''-(S)-hexahydroxydiphenoyl)-beta-D-glucose (PGHG). Molecular dynamic simulations predicted that PGHG occludes the S1 binding site via a galloyl group and induces a conformational change in Mpro. These studies will advance the development of plant-based flavonoids-including widely available natural products-to target β-coronaviruses.

Targeting SARS-CoV-2 endoribonuclease: a structure-based virtual screening supported by in vitro analysis

Researchers are focused on discovering compounds that can interfere with the COVID-19 life cycle. One of the important non-structural proteins is endoribonuclease since it is responsible for processing viral RNA to evade detection of the host defense system. This work investigates a hierarchical structure-based virtual screening approach targeting NSP15. Different filtering approaches to predict the interactions of the compounds have been included in this study. Using a deep learning technique, we screened 823,821 compounds from five different databases (ZINC15, NCI, Drug Bank, Maybridge, and NCI Diversity set III). Subsequently, two docking protocols (extra precision and induced fit) were used to assess the binding affinity of the compounds, followed by molecular dynamic simulation supported by the MM-GBSA free binding energy. Interestingly, one compound (ZINC000104379474) from the ZINC15 database has been found to have a good binding affinity of − 7.68 kcal/Mol. The VERO-E6 cell line was used to investigate its therapeutic effect in vitro. Half-maximal cytotoxic concentration and Inhibitory concentration 50 were determined to be 0.9 mg/ml and 0.01 mg/ml, respectively; therefore, the selectivity index is 90. In conclusion, ZINC000104379474 was shown to be a good hit for targeting the virus that needs further investigations in vivo to be a drug candidate.

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.