Hyperoside for COVID-19

The COVID-19 pandemic has had a significant and lasting impact on the world. Four years on, despite the existence of effective vaccines, the continuous emergence of new SARS-CoV-2 variants remains a challenge for long-term immunity. Additionally, there remain few purpose-built antivirals to protect individuals at risk of severe disease in the event of future coronavirus outbreaks. A promising mechanism of action for novel coronavirus antivirals is the inhibition of viral entry. To facilitate entry, the coronavirus spike glycoprotein interacts with angiotensin converting enzyme 2 (ACE2) on respiratory epithelial cells. Blocking this interaction and consequently viral replication may be an effective strategy for treating infection, however further research is needed to better characterize candidate molecules with antiviral activity before progressing to animal studies and clinical trials. In general, antiviral drugs are developed from purely synthetic compounds or synthetic derivatives of natural products such as plant secondary metabolites. While the former is often favored due to the higher specificity afforded by rational drug design, natural products offer several unique advantages that make them worthy of further study including diverse bioactivity and the ability to work synergistically with other drugs. Accordingly, there has recently been a renewed interest in natural product-derived antivirals in the wake of the COVID-19 pandemic. This review provides a summary of recent research into coronavirus entry inhibitors, with a focus on natural compounds derived from plants, honey, and marine sponges.

The existing literature supports the anti-inflammatory, antioxidant, and antiviral capacities of the polyphenol extracts derived from Geranium sanguineum L. These extracts exhibit potential in hindering viral replication by inhibiting enzymes like DNA polymerase and reverse transcriptase. The antiviral properties of G. sanguineum L. seem to complement its immunomodulatory effects, contributing to infection resolution. While preclinical studies on G. sanguineum L. suggest its potential effectiveness against COVID-19, there is still a lack of clinical evidence. Therefore, the polyphenols extracted from this herb warrant further investigation as a potential alternative for preventing and treating COVID-19 infections.

Over 750 million cases of COVID-19, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), have been reported since the onset of the global outbreak. The need for effective treatments has spurred intensive research for therapeutic agents based on pharmaceutical repositioning or natural products. In light of prior studies asserting the bioactivity of natural compounds of the autochthonous Peruvian flora, the present study focuses on the identification SARS-CoV-2 Mpro main protease dimer inhibitors. To this end, a target-based virtual screening was performed over a representative set of Peruvian flora-derived natural compounds. The best poses obtained from the ensemble molecular docking process were selected. These structures were subjected to extensive molecular dynamics steps for the computation of binding free energies along the trajectory and evaluation of the stability of the complexes. The compounds exhibiting the best free energy behaviors were selected for in vitro testing, confirming the inhibitory activity of Hyperoside against Mpro, with a Ki value lower than 20 µM, presumably through allosteric modulation.

The COVID-19 pandemic caused by SARS-CoV-2 remains a global public health threat and has prompted the development of antiviral therapies. Artificial intelligence may be one of the strategies to facilitate drug development for emerging and re-emerging diseases. The main protease (Mpro) of SARS-CoV-2 is an attractive drug target due to its essential role in the virus life cycle and high conservation among SARS-CoVs. In this study, we used a data augmentation method to boost transfer learning model performance in screening for potential inhibitors of SARS-CoV-2 Mpro. This method appeared to outperform graph convolution neural network, random forest and Chemprop on an external test set. The fine-tuned model was used to screen for a natural compound library and a de novo generated compound library. By combination with other in silico analysis methods, a total of 27 compounds were selected for experimental validation of anti-Mpro activities. Among all the selected hits, two compounds (gyssypol acetic acid and hyperoside) displayed inhibitory effects against Mpro with IC50 values of 67.6 μM and 235.8 μM, respectively. The results obtained in this study may suggest an effective strategy of discovering potential therapeutic leads for SARS-CoV-2 and other coronaviruses.