Scutellarin for COVID-19

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) caused an outbreak in 2002-2003, spreading to 29 countries with a mortality rate of about 10%. Strict quarantine and infection control methods quickly stopped the spread of the disease. Later research showed that SARS-CoV came from animals (zoonosis) and stressed the possibility of a similar spread from host to human, which was clearly shown by the COVID-19 outbreak. The COVID-19 pandemic, instigated by SARS-CoV-2, has affected 776 million confirmed cases and more than seven million deaths globally as of Sept 15, 2024. The existence of animal reservoirs of coronaviruses continues to pose a risk of re-emergence with improved fitness and virulence. Given the high death rate (up to 70 percent) and the high rate of severe sickness (up to 68.7 percent in long-COVID patients), it is even more critical to identify new therapies as soon as possible. This study combines research on antivirals that target SARS coronaviruses that have been conducted over the course of more than twenty years. It is a beneficial resource that might be useful in directing future studies.

The human transmembrane protease, serine 2 (TMPRSS2), essential for SARS-CoV-2 entry, is a key antiviral target. Here, we computationally profiled the TMPRSS2-binding affinities of 15 antiviral compounds. Molecular dynamics (MD) simulations for the docked complexes revealed that three compounds exited the substrate-binding cavity (SBC), suggesting noncompetitive inhibition. Of the remaining compounds, five charged ones exhibited reduced binding stability due to competing electrostatic interactions and increased solvent exposure, while seven neutral compounds showed stronger binding affinity driven by van der Waals (vdW) interactions compensating for unfavorable electrostatic effects (including electrostatic interactions and desolvation penalties). Positive and negative hotspot residues were identified as uncharged and charged, respectively, both lining the SBC. Despite forming diverse interactions with compounds, the burial of positive hotspots led to strong vdW interactions that overcompensated for unfavorable electrostatic effects, whereas negative hotspots incurred high desolvation penalties, negating any favorable contributions. Charged residues at the SBC’s outer rim can reduce binding affinity significantly when forming hydrogen bonds or salt bridges. These findings underscore the importance of enhancing vdW interactions with uncharged residues and minimizing the unfavorable electrostatic effects of charged residues, providing valuable insights for designing effective TMPRSS2 inhibitors.

COVID-19 pandemic caused by the novel SARS-CoV-2 has impacted human livelihood globally. Strenuous efforts have been employed for its control and prevention; however, with recent reports on mutated strains with much higher infectivity, transmissibility, and ability to evade immunity developed from previous SARS-CoV-2 infections, prevention alternatives must be prepared beforehand in case. We have perused over 128 recent works (found on Google Scholar, PubMed, and ScienceDirect as of February 2023) on medicinal plants and their compounds for anti-SARS-CoV-2 activity and eventually reviewed 102 of them. The clinical application and the curative effect were reported high in China and in India. Accordingly, this review highlights the unprecedented opportunities offered by medicinal plants and their compounds, candidates as the therapeutic agent, against COVID-19 by acting as viral protein inhibitors and immunomodulator in (32 clinical trials and hundreds of in silico experiments) conjecture with modern science. Moreover, the associated foreseeable challenges for their viral outbreak management were discussed in comparison to synthetic drugs.

AbstractThe search for an effective drug is still urgent for COVID-19 as no drug with proven clinical efficacy is available. Finding the new purpose of an approved or investigational drug, known as drug repurposing, has become increasingly popular in recent years. We propose here a new drug repurposing approach for COVID-19, based on knowledge graph (KG) embeddings. Our approach learns “ensemble embeddings” of entities and relations in a COVID-19 centric KG, in order to get a better latent representation of the graph elements. Ensemble KG-embeddings are subsequently used in a deep neural network trained for discovering potential drugs for COVID-19. Compared to related works, we retrieve more in-trial drugs among our top-ranked predictions, thus giving greater confidence in our prediction for out-of-trial drugs. For the first time to our knowledge, molecular docking is then used to evaluate the predictions obtained from drug repurposing using KG embedding. We show that Fosinopril is a potential ligand for the SARS-CoV-2 nsp13 target. We also provide explanations of our predictions thanks to rules extracted from the KG and instanciated by KG-derived explanatory paths. Molecular evaluation and explanatory paths bring reliability to our results and constitute new complementary and reusable methods for assessing KG-based drug repurposing.