Pseudoephedrine and its derivatives antagonize wild and mutated severe acute respiratory syndrome-CoV-2 viruses through blocking virus invasion and antiinflammatory effect

Exploring anti-SARS-CoV-2 natural products: dual-viral target inhibition by delphinidin and the anti-coronaviral efficacy of deapio platycodin D

Qingfei Paidu decoction (QFPDD) has been extensively used in clinical treatments during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. SARS-CoV-2 primarily invades host cells via its spike (S) protein binding to the angiotensin-converting enzyme 2 (ACE2) on the cell membrane, mediating viral-host membrane fusion. Blocking viral entry is a crucial step in preventing infection, with the interaction between the S receptor binding domain (S-RBD) and ACE2 being a key antiviral target. Given that SARS-CoV-2 predominantly affects the respiratory system and approximately 25% of patients suffering from corona virus disease 2019 (COVID-19) with gastrointestinal symptoms, we are committed to identifying more active ingredients in QFPDD that target the respiratory and gastrointestinal tracts of COVID-19 patients. Among medicinal plants, ephedra and liquorice derived from QFPDD, along with two other Chinese herbs, Platycodon grandiflorum and Radix Rhei Et Rhizome (rhubarb), have garnered our interest. These herbs have historically been used in traditional Chinese medicine (TCM) for treating infectious diseases with respiratory and digestive symptoms. Here, we established a library containing all components of the four individual herbs gathered from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and performed structure-based virtual screening to identify potential ACE2/S-RBD inhibitors. Subsequently, we selected 10 ingredients from the top 30 candidates and evaluated their activities using a pseudovirus neutralization assay. Delphinidin and deapio platycodin D (DPD) showed significant antiviral potential with half-maximal inhibitory concentration (IC50) values of 45.35 µM and 1.38 µM, respectively. Furthermore, delphinidin also inhibited the 3-chymotrypsin-like protease (3CLpro), indicating its dual-viral target inhibitory potential. Notably, DPD effectively suppressed HCoV-229E replication in BEL-7402 cells. This study not only provides a strategy for rapid identifying antiviral agents from TCM in anticipation of future pandemics but also offers theoretical and experimental evidence to support for the clinical use of QFPDD.

Salidroside Derivative SHPL-49 Exerts Anti-Neuroinflammatory Effects by Modulating Excessive Autophagy in Microglia

The neuroinflammation triggered by cellular demise plays a pivotal role in ameliorating the injury associated with ischemic stroke, which represents a significant global burden of mortality and disability. The compound SHPL-49, a derivative of rhodioloside, was discovered by our research team and has previously demonstrated neuroprotective effects in rats with ischemic stroke. This study aimed to elucidate the underlying mechanisms of SHPL-49's protective effects. Preliminary investigations revealed that SHPL-49 effectively alleviates PMCAO-induced neuroinflammation. Further studies indicated that SHPL-49 downregulates the expression of the lysosomal protein LAMP-2 and reduces lysosomal activity, impeding the fusion of lysosomes and autophagosomes, thus inhibiting excessive autophagy and increasing the expression levels of the autophagy proteins LC3-II and P62. Furthermore, SHPL-49 effectively reverses the NF-κB nuclear translocation induced by the autophagy inducer rapamycin, significantly lowering the expression levels of the inflammatory factors IL-6, IL-1β, and iNOS. In a co-culture system of BV2 and PC12 cells, SHPL-49 enhanced PC12 cell viability by inhibiting excessive autophagy in BV2 cells and reducing the ratio of apoptotic proteins Bax and BCL-2. The overall findings suggest that SHPL-49 exerts its neuroprotective effects through the inhibition of excessive autophagy and the suppression of the NF-κB signaling pathway in microglia, thereby attenuating neuroinflammation.

Traditional Chinese Medicine for Viral Pneumonia Therapy: Pharmacological Basis and Mechanistic Insights

Different respiratory viruses might cause similar symptoms, ranging from mild upper respiratory tract involvement to severe respiratory distress, which can rapidly progress to septic shock, coagulation disorders, and multiorgan failure, ultimately leading to death. The COVID-19 pandemic has shown that predicting clinical outcomes can be challenging because of the complex interactions between the virus and the host. Traditional Chinese medicine (TCM) has distinct benefits in the treatment of respiratory viral illnesses due to its adherence to the principles of "different treatments for the same disease" and "same treatment for different diseases". This paper examines the effectiveness and underlying mechanisms of key TCM treatments for viral pneumonia in recent years. The aim of this study was to discover and confirm the active substances of TCM with potential therapeutic effects on viral pneumonia and their integrative effects and synergistic mechanisms and to provide a scientific basis for elucidating the effectiveness of TCM treatment and drug discovery. Furthermore, a thorough analysis of previous research is necessary to evaluate the effectiveness of TCM in treating viral pneumonia.

iNGNN-DTI: prediction of drug-target interaction with interpretable nested graph neural network and pretrained molecule models

MOTIVATION

Drug-target interaction (DTI) prediction aims to identify interactions between drugs and protein targets. Deep learning can automatically learn discriminative features from drug and protein target representations for DTI prediction, but challenges remain, making it an open question. Existing approaches encode drugs and targets into features using deep learning models, but they often lack explanations for underlying interactions. Moreover, limited labeled DTIs in the chemical space can hinder model generalization.

RESULTS

We propose an interpretable nested graph neural network for DTI prediction (iNGNN-DTI) using pre-trained molecule and protein models. The analysis is conducted on graph data representing drugs and targets by using a specific type of nested graph neural network, in which the target graphs are created based on 3D structures using Alphafold2. This architecture is highly expressive in capturing substructures of the graph data. We use a cross-attention module to capture interaction information between the substructures of drugs and targets. To improve feature representations, we integrate features learned by models that are pre-trained on large unlabeled small molecule and protein datasets, respectively. We evaluate our model on three benchmark datasets, and it shows a consistent improvement on all baseline models in all datasets. We also run an experiment with previously unseen drugs or targets in the test set, and our model outperforms all of the baselines. Furthermore, the iNGNN-DTI can provide more insights into the interaction by visualizing the weights learned by the cross-attention module.

AVAILABILITY AND IMPLEMENTATION

The source code of the algorithm is available at https://github.com/syan1992/iNGNN-DTI.

Plant-derived compounds as potential leads for new drug development targeting COVID-19

COVID-19, which was first identified in 2019 in Wuhan, China, is a respiratory illness caused by a virus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although some patients infected with COVID-19 can remain asymptomatic, most experience a range of symptoms that can be mild to severe. Common symptoms include fever, cough, shortness of breath, fatigue, loss of taste or smell and muscle aches. In severe cases, complications can arise including pneumonia, acute respiratory distress syndrome, organ failure and even death, particularly in older adults or individuals with underlying health conditions. Treatments for COVID-19 include remdesivir, which has been authorised for emergency use in some countries, and dexamethasone, a corticosteroid used to reduce inflammation in severe cases. Biological drugs including monoclonal antibodies, such as casirivimab and imdevimab, have also been authorised for emergency use in certain situations. While these treatments have improved the outcome for many patients, there is still an urgent need for new treatments. Medicinal plants have long served as a valuable source of new drug leads and may serve as a valuable resource in the development of COVID-19 treatments due to their broad-spectrum antiviral activity. To date, various medicinal plant extracts have been studied for their cellular and molecular interactions, with some demonstrating anti-SARS-CoV-2 activity in vitro. This review explores the evaluation and potential therapeutic applications of these plants against SARS-CoV-2. This review summarises the latest evidence on the activity of different plant extracts and their isolated bioactive compounds against SARS-CoV-2, with a focus on the application of plant-derived compounds in animal models and in human studies.

Xuanfei Baidu decoction in the treatment of coronavirus disease 2019 (COVID-19): Efficacy and potential mechanisms

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread worldwide and become a major global public health concern. Although novel investigational COVID-19 antiviral candidates such as the Pfizer agent PAXLOVID™, molnupiravir, baricitinib, remdesivir, and favipiravir are currently used to treat patients with COVID-19, there is still a critical need for the development of additional treatments, as the recommended therapeutic options are frequently ineffective against SARS-CoV-2. The efficacy and safety of vaccines remain uncertain, particularly with the emergence of several variants. All 10 versions of the National Health Commission's diagnosis and treatment guidelines for COVID-19 recommend using traditional Chinese medicine. Xuanfei Baidu Decoction (XFBD) is one of the "three Chinese medicines and three Chinese prescriptions" recommended for COVID-19. This review summarizes the clinical evidence and potential mechanisms of action of XFBD for COVID-19 treatment. With XFBD, patients with COVID-19 experience improved clinical symptoms, shorter hospital stay, prevention of the progression of their symptoms from mild to moderate and severe symptoms, and reduced mortality in critically ill patients. The mechanisms of action may be associated with its direct antiviral, anti-inflammatory, immunomodulatory, antioxidative, and antimicrobial properties. High-quality clinical and experimental studies are needed to further explore the clinical efficacy and underlying mechanisms of XFBD in COVID-19 treatment.

Ginkgolic acids inhibit SARS-CoV-2 and its variants by blocking the spike protein/ACE2 interplay

Targeting the interaction between the spike protein receptor binding domain (S-RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and angiotensin-converting enzyme 2 (ACE2) is a potential therapeutic strategy for treating coronavirus disease 2019 (COVID-19). However, we still lack small-molecule drug candidates for this target due to the missing knowledge in the hot spots for the protein-protein interaction. Here, we used NanoBiT technology to identify three Ginkgolic acids from an in-house traditional Chinese medicine (TCM) library, and they interfere with the S-RBD/ACE2 interplay. Our pseudovirus assay showed that one of the compounds, Ginkgolic acid C17:1 (GA171), significantly inhibits the entry of original SARS-CoV-2 and its variants into the ACE2-overexpressed HEK293T cells. We investigated and proposed the binding sites of GA171 on S-RBD by combining molecular docking and molecular dynamics simulations. Site-directed mutagenesis and surface plasmon resonance revealed that GA171 specifically binds to the pocket near R403 and Y505, critical residues of S-RBD for S-RBD interacting with ACE2. Thus, we provide structural insights into developing new small-molecule inhibitors and vaccines against the proposed S-RBD binding site.

Rational drug repositioning for coronavirus-associated diseases using directional mapping and side-effect inference

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen of coronavirus disease 2019 (COVID-19), has infected hundreds of millions of people and caused millions of deaths. Looking for valid druggable targets with minimal side effects for the treatment of COVID-19 remains critical. After discovering host genes from multiscale omics data, we developed an end-to-end network method to investigate drug-host gene(s)-coronavirus (CoV) paths and the mechanism of action between the drug and the host factor in a directional network. We also inspected the potential side effect of the candidate drug on several common comorbidities. We established a catalog of host genes associated with three CoVs. Rule-based prioritization yielded 29 Food and Drug Administration (FDA)-approved drugs via accounting for the effects of drugs on CoVs, comorbidities, and drug-target confidence information. Seven drugs are currently undergoing clinical trials as COVID-19 treatment. This catalog of druggable host genes associated with CoVs and the prioritized repurposed drugs will provide a new sight in therapeutics discovery for severe COVID-19 patients.

Combined exploration of the mechanism of Sang Xing Decoction in the treatment of smoke-induced acute bronchitis from protein and metabolic levels

Sang Xing decoction (SXD) is a typical prescription for treating "warm dryness" in traditional Chinese medicine (TCM), which is equivalent to respiratory diseases such as acute bronchitis in modern medicine. However, its mechanism of action remains unclear. In this study, the representative components of SXD were characterized using liquid chromatography-tandem mass spectrometry (LC-MS). The key targets, signaling pathways, and metabolic pathways associated with SXD in the treatment of acute bronchitis were identified via network prediction and metabolomics. A rat model of acute bronchitis was also established using mixed smoke, systematic in vivo experiments such as histopathological analyses, enzyme-linked immunosorbent assay (ELISA), immunofluorescence, immunohistochemistry and western blotting were conducted to evaluate the network prediction results. An in-depth analysis of the targeted quantitative results was performed using the SIMCA software and MetaboAnalyst website. The results revealed that 50 active compounds and 45 key targets were screened and clustered with 20 approved drugs. The NF-κB signaling pathway, oxidative stress, and glutamine metabolism were associated with the therapeutic mechanism of SXD in acute bronchitis. In vivo experiments showed that SXD may maintain the production of inflammatory factors by regulating the PI3K/Akt/NF-κB signaling pathway, improving the metabolism of glutamine and glutamate to reduce oxidative stress, and inhibiting apoptosis. Simultaneously, the possibility of using SXD as an adjuvant drug for COVID-19 treatment was also revealed. This research will lay the foundation for the modern clinical application of SXD and promote the promotion and innovation of TCM.