Discovery of TCMs and derivatives against the main protease of SARS-CoV-2 via high throughput screening, ADMET analysis, and inhibition assay in vitro

Chinese Medicine for Treatment of COVID-19: A Review of Potential Pharmacological Components and Mechanisms

Coronavirus disease 2019 (COVID-19) is an acute infectious respiratory disease that has been prevalent since December 2019. Chinese medicine (CM) has demonstrated its unique advantages in the fight against COVID-19 in the areas of disease prevention, improvement of clinical symptoms, and control of disease progression. This review summarized the relevant material components of CM in the treatment of COVID-19 by searching the relevant literature and reports on CM in the treatment of COVID-19 and combining with the physiological and pathological characteristics of the novel coronavirus. On the basis of sorting out experimental methods in vivo and in vitro, the mechanism of herb action was further clarified in terms of inhibiting virus invasion and replication and improving related complications. The aim of the article is to explore the strengths and characteristics of CM in the treatment of COVID-19, and to provide a basis for the research and scientific, standardized treatment of COVID-19 with CM.

Methyl rosmarinate is an allosteric inhibitor of SARS-CoV-2 3 CL protease as a potential candidate against SARS-cov-2 infection

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been ongoing for more than three years and urgently needs to be addressed. Traditional Chinese medicine (TCM) prescriptions have played an important role in the clinical treatment of patients with COVID-19 in China. However, it is difficult to uncover the potential molecular mechanisms of the active ingredients in these TCM prescriptions. In this paper, we developed a new approach by integrating the experimental assay, virtual screening, and the experimental verification, exploring the rapid discovery of active ingredients from TCM prescriptions. To achieve this goal, 4 TCM prescriptions in clinical use for different indications were selected to find the antiviral active ingredients in TCMs. The 3-chymotrypsin-like protease (3CLpro), an important target for fighting COVID-19, was utilized to determine the inhibitory activity of the TCM prescriptions and single herb. It was found that 10 single herbs had better inhibitory activity than other herbs by using a fluorescence resonance energy transfer (FRET) - based enzymatic assay of SARS-CoV-2 3CLpro. The ingredients contained in 10 herbs were thus virtually screened and the predicted active ingredients were experimentally validated. Thus, such a research strategy firstly removed many single herbs with no inhibitory activity against SARS-CoV-2 3CLpro at the very beginning by FRET-based assay, making our subsequent virtual screening more effective. Finally, 4 active components were found to have stronger inhibitory effects on SARS-CoV-2 3CLpro, and their inhibitory mechanism was subsequently investigated. Among of them, methyl rosmarinate as an allosteric inhibitor of SARS-CoV-2 3CLpro was confirmed and its ability to inhibit viral replication was demonstrated by the SARS-CoV-2 replicon system. To validate the binding mode via docking, the mutation experiment, circular dichroism (CD), enzymatic inhibition and surface plasmon resonance (SPR) assay were performed, demonstrating that methyl rosmarinate bound to the allosteric site of SARS-CoV-2 3CLpro. In conclusion, this paper provides the new ideas for the rapid discovery of active ingredients in TCM prescriptions based on a specific target, and methyl rosmarinate has the potential to be developed as an antiviral therapeutic candidate against SARS-CoV-2 infection.

Research progress on classical traditional Chinese medicine formula Baihe Zhimu (Lilium lancifolium bulb and Anemarrhena asphodeloides rhizome) decoction in the treatment of depression

Depression is considered to be an "emotional disease" in ancient books of traditional Chinese medicine. Its clinical features are similar to those of "Lily disease" in the ancient Chinese medicine book Synopsis of the Golden Chamber written by Zhang Zhongjing in the Han Dynasty. Baihe Zhimu (Lilium lancifolium bulb and Anemarrhena asphodeloides rhizome) decoction (LBRAD) is the first prescription of "Lily Disease" in this book. It is also a special remedy for "Lily disease" after sweating. The classic recipe LBRAD consists of two herbs, fresh lily bulbs and dried Rhizoma Anemarrhena slice. It has the effect of supplementing nutrition and clearing heat, nourishing Yin and moistening. After more than two thousand years of clinical practice, it has been currently widely used in clinical treatment of depression. In this paper, the relationship between LBRAD and depression was systematically reviewed from both clinical and experimental studies, as well as the preparation, the clinical application, the pharmacological mechanism and the effective material basis for the treating depression of LBRAD. The core targets and biological processes of the depression treatment were explored through network pharmacological analysis, so as to speculate its potential mechanism. Finally, the association between LBRAD and post-COVID-19 depression was discussed. We concluded with a summary and future prospects. This review may provide a theoretical basis for the expansion of the clinical application of LBRAD and the development of new drugs for the treatment of depression, as well as new ideas for the secondary development of classical prescriptions.

Identification of a Putative SARS-CoV-2 Main Protease Inhibitor through In Silico Screening of Self-Designed Molecular Library

There have been outbreaks of SARS-CoV-2 around the world for over three years, and its variants continue to evolve. This has become a major global health threat. The main protease (M^pro, also called 3CL^pro) plays a key role in viral replication and proliferation, making it an attractive drug target. Here, we have identified a novel potential inhibitor of M^pro, by applying the virtual screening of hundreds of nilotinib-structure-like compounds that we designed and synthesized. The screened compounds were assessed using SP docking, XP docking, MM-GBSA analysis, IFD docking, MD simulation, ADME/T prediction, and then an enzymatic assay in vitro. We finally identified the compound V291 as a potential SARS-CoV-2 M^pro inhibitor, with a high docking affinity and enzyme inhibitory activity. Moreover, the docking results indicate that His41 is a favorable amino acid for pi-pi interactions, while Glu166 can participate in salt-bridge formation with the protonated primary or secondary amines in the screened molecules. Thus, the compounds reported here are capable of engaging the key amino acids His41 and Glu166 in ligand-receptor interactions. A pharmacophore analysis further validates this assertion.

High-Throughput Screening for the Potential Inhibitors of SARS-CoV-2 with Essential Dynamic Behavior

Global health security has been challenged by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Due to the lengthy process of generating vaccinations, it is vital to reposition currently available drugs in order to relieve anti-epidemic tensions and accelerate the development of therapies for Coronavirus Disease 2019 (COVID-19), the public threat caused by SARS-CoV-2. High throughput screening techniques have established their roles in the evaluation of already available medications and the search for novel potential agents with desirable chemical space and more cost-effectiveness. Here, we present the architectural aspects of highthroughput screening for SARS-CoV-2 inhibitors, especially three generations of virtual screening methodologies with structural dynamics: ligand-based screening, receptor-based screening, and machine learning (ML)-based scoring functions (SFs). By outlining the benefits and drawbacks, we hope that researchers will be motivated to adopt these methods in the development of novel anti- SARS-CoV-2 agents.

In Silico Identification of Anti-SARS-CoV-2 Medicinal Plants Using Cheminformatics and Machine Learning

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of COVID-19, is spreading rapidly and has caused hundreds of millions of infections and millions of deaths worldwide. Due to the lack of specific vaccines and effective treatments for COVID-19, there is an urgent need to identify effective drugs. Traditional Chinese medicine (TCM) is a valuable resource for identifying novel anti-SARS-CoV-2 drugs based on the important contribution of TCM and its potential benefits in COVID-19 treatment. Herein, we aimed to discover novel anti-SARS-CoV-2 compounds and medicinal plants from TCM by establishing a prediction method of anti-SARS-CoV-2 activity using machine learning methods. We first constructed a benchmark dataset from anti-SARS-CoV-2 bioactivity data collected from the ChEMBL database. Then, we established random forest (RF) and support vector machine (SVM) models that both achieved satisfactory predictive performance with AUC values of 0.90. By using this method, a total of 1011 active anti-SARS-CoV-2 compounds were predicted from the TCMSP database. Among these compounds, six compounds with highly potent activity were confirmed in the anti-SARS-CoV-2 experiments. The molecular fingerprint similarity analysis revealed that only 24 of the 1011 compounds have high similarity to the FDA-approved antiviral drugs, indicating that most of the compounds were structurally novel. Based on the predicted anti-SARS-CoV-2 compounds, we identified 74 anti-SARS-CoV-2 medicinal plants through enrichment analysis. The 74 plants are widely distributed in 68 genera and 43 families, 14 of which belong to antipyretic detoxicate plants. In summary, this study provided several medicinal plants with potential anti-SARS-CoV-2 activity, which offer an attractive starting point and a broader scope to mine for potentially novel anti-SARS-CoV-2 drugs.

Traditional Chinese Medicine in Treatment of COVID-19 and Viral Disease: Efficacies and Clinical Evidence

Coronavirus disease 2019 (COVID-19) remains an uncontained, worldwide pandemic. While battling the disease in China, the Chinese government has actively promoted the use of traditional Chinese medicine, and many studies have been conducted to determine the efficacy of traditional Chinese medicine for treating COVID-19. The present review discusses the effectiveness and safety of traditional Chinese medicine in curing COVID-19 and provides clinical evidence from all confirmed cases in China. Applications of traditional Chinese medicine and specific recipes for treating other viral infections, such as those caused by severe acute respiratory syndrome coronavirus and influenza A viruses (including H1N1), are also discussed. Studies have reported that traditional Chinese medicine treatment plays a significant role in improving clinical symptoms. Therefore, further investigation may be of high translational value in revealing novel targeted therapies for COVID-19.

Small GTPase-a Key Role in Host Cell for Coronavirus Infection and a Potential Target for Coronavirus Vaccine Adjuvant Discovery

Small GTPases are signaling molecules in regulating key cellular processes (e.g., cell differentiation, proliferation, and motility) as well as subcellular events (e.g., vesicle trafficking), making them key participants, especially in a great array of coronavirus infection processes. In this review, we discuss the role of small GTPases in the coronavirus life cycle, especially pre-entry, endocytosis, intracellular traffic, replication, and egress from the host cell. Furthermore, we also suggest the molecules that have potent adjuvant activity by targeting small GTPases. These studies provide deep insights and references to understand the pathogenesis of coronavirus as well as to propose the potential of small GTPases as targets for adjuvant development.