Investigating the active compounds and mechanism of HuaShi XuanFei formula for prevention and treatment of COVID-19 based on network pharmacology and molecular docking analysis

Discovery of potential quality markers of Fritillariae thunbergii bulbus in pneumonia by combining UPLC-QTOF-MS, network pharmacology, and molecular docking

Fritillariae thunbergii bulbus (FTB) is a popular Chinese herbal medicine with various applications in respiratory diseases. The quality evaluation of FTB has been insufficient to date, as the active ingredients and mechanisms of action of FTB remain unclear. This study proposes a novel strategy for exploring the quality markers (Q-markers) of FTB based on UPLC-QTOF-MS analysis, network pharmacology, molecular docking, and molecular dynamics (MD) simulation. A total of 26 compounds in FTB were identified by UPLC-QTOF-MS. Ten of these compounds were screened as Q-markers based on network pharmacology for their anti-pneumonia effects, including imperialine, peimisine, peiminine, ebeiedinone, zhebeirine, puqiedine, 9-hydroxy-10,12-octadecadienoic acid, (9Z,12Z,15Z)-13-hydroxy-9,12,15-octadecatrienoic acid, 9,12,15-octadecatrienoic acid, and (2E,4Z,7Z,10Z,13Z,16Z,19Z)-2,4,7,10,13,16,19-docosaheptaenoic acid methyl ester (DAME). These Q-markers were predicted to act on multiple targets and pathways associated with pneumonia. Molecular docking results revealed that most of the Q-markers showed high affinity with at least one of the main targets of pneumonia, and the top ten complexes were confirmed with MD simulation. Network pharmacology indicated that FTB may act on the TNF signaling pathway, HIF-1 signaling pathway, JAK-STAT signaling pathway, etc. The results demonstrated that imperialine (P8), peimisine (P9), peiminine (P11), ebeiedine (P15), zhebeirine (P16), and puqiedine (P18) may be potential Q-markers of FTB, and AKT1, IL-6, VEGFA, TP53, EGFR, STAT3, PPARG, MMP9, and CASP3 may be promising therapeutic targets for pneumonia treatment that are worthy of further research.

In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review

The coronavirus disease 2019 (COVID-19) is a severe worldwide pandemic. Due to the emergence of various SARS-CoV-2 variants and the presence of only one Food and Drug Administration (FDA) approved anti-COVID-19 drug (remdesivir), the disease remains a mindboggling global public health problem. Developing anti-COVID-19 drug candidates that are effective against SARS-CoV-2 and its various variants is a pressing need that should be satisfied. This systematic review assesses the existing literature that used in silico models during the discovery procedure of anti-COVID-19 drugs. Cochrane Library, Science Direct, Google Scholar, and PubMed were used to conduct a literature search to find the relevant articles utilizing the search terms "In silico model," "COVID-19," "Anti-COVID-19 drug," "Drug discovery," "Computational drug designing," and "Computer-aided drug design." Studies published in English between 2019 and December 2022 were included in the systematic review. From the 1120 articles retrieved from the databases and reference lists, only 33 were included in the review after the removal of duplicates, screening, and eligibility assessment. Most of the articles are studies that use SARS-CoV-2 proteins as drug targets. Both ligand-based and structure-based methods were utilized to obtain lead anti-COVID-19 drug candidates. Sixteen articles also assessed absorption, distribution, metabolism, excretion, toxicity (ADMET), and drug-likeness properties. Confirmation of the inhibitory ability of the candidate leads by in vivo or in vitro assays was reported in only five articles. Virtual screening, molecular docking (MD), and molecular dynamics simulation (MDS) emerged as the most commonly utilized in silico models for anti-COVID-19 drug discovery.

Elucidation of the potential antioxidant compound and mechanism of mung bean using network pharmacology and in vitro anti-oxidative activity

Mung bean is rich in bioactive components, but the main compound and pharmacological mechanism in reducing oxidative and free radical damage are unclear. Network pharmacology and 2,2′-azino-bis-3-ethylbenzthiazoline-6-sulfonic acid (ABTS) radical scavenging activities were employed to uncover the antioxidant mechanism of potentially active compounds, considering the interactions between mung bean targets and oxidative and free radical damage. These key targets were analyzed by protein–protein interactions (PPIs), and key genes were used to find the biological pathway and therapeutic mechanism by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The results showed that five antioxidant components and 18 mung bean targets were screened. β-carotene and vitexin both played a crucial role in mung bean against oxidative and free radical damage, and the ABTS radical scavenging activities of β-carotene and vitexin were 94.84 and 87.79%, which were equivalent to those of vitamin C. Key targets may be AR, HSP90AA1, MYC, and CASP3 for mung bean to exert antioxidant activity. GO and KEGG indicated that mung bean may mainly act on thyroid hormone signaling pathway, estrogen signaling pathway, p53 signaling pathway, etc. In vitro antioxidant activity tests showed that the bioactive ingredients of mung beans had great antioxidant activity. Network pharmacology analysis also revealed the underlying molecular mechanisms of oxidative and free radical damage. This study provides new insights and evidence to explore the bioactive compounds and biological functions of food cereals and legumes, as well as a reference for the functional evaluation of food ingredients and the development of functional foods.

Exploration of molecular targets and mechanisms of Chinese medicinal formula Acacia Catechu -Scutellariae Radix in the treatment of COVID-19 by a systems pharmacology strategy

Coronavirus disease 2019 (COVID‐19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). In China, the Acacia catechu (AC)‐Scutellariae Radix (SR) formula has been widely used for pulmonary infection in clinical practice for several centuries. However, the potential role and mechanisms of this formula against COVID‐19 remains unclear. The present study was designed to dissect the active ingredients, molecular targets, and the therapeutic mechanisms of AC‐SR formula in the treatment of COVID‐19 based on a systems pharmacology strategy integrated by ADME screening, target prediction, network analysis, GO and KEGG enrichment analysis, molecular docking, and molecular dynamic (MD) simulations. Finally, Quercetin, Fisetin(1‐), kaempferol, Wogonin, Beta‐sitosterol, Baicalein, Skullcapflavone II, Stigmasterol were primarily screened to be the potentially effective active ingredients against COVID‐19. The hub‐proteins were TP53, JUN, ESR1, MAPK1, Akt1, HSP90AA1, TNF, IL‐6, SRC, and RELA. The potential mechanisms of AC‐SR formula in the treatment of COVID‐19 were the TNF signaling pathway, PI3K‐Akt signaling pathway and IL‐17 signaling pathway, etc. Furthermore, virtual docking revealed that baicalein, (+)‐catechin and fisetin(1‐) exhibited high affinity to SARS‐CoV‐2 3CLpro, which has validated by the FRET‐based enzymatic inhibitory assays with the IC₅₀ of 11.3, 23.8, and 44.1 μM, respectively. And also, a concentration‐dependent inhibition of baicalein, quercetin and (+)‐catechin against SARS‐CoV‐2 ACE2 was observed with the IC₅₀ of 138.2, 141.3, and 348.4 μM, respectively. These findings suggested AC‐SR formula exerted therapeutic effects involving “multi‐compounds and multi‐targets.” It might be working through directly inhibiting the virus, improving immune function, and reducing the inflammatory in response to anti‐COVID‐19. Ultimately, this study would provide new perspective for discovering potential drugs and mechanisms against COVID‐19.

Integrating network pharmacology and molecular docking to explore the potential mechanism of Xinguan No. 3 in the treatment of COVID-19

Xinguan No. 3 has been recommended for the treatment of coronavirus disease 2019 (COVID-19); however, its potential mechanisms are unclear. This study aims to explore the mechanisms of Xinguan No. 3 against COVID-19 through network pharmacology and molecular docking. We first searched the ingredients of Xinguan No. 3 in three databases (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Traditional Chinese Medicines Integrated Database, and The Encyclopedia of Traditional Chinese Medicine). The active components and their potential targets were predicted through the SwissTargetPrediction website. The targets of COVID-19 can be found on the GeneCards website. Protein interaction analysis, screening of key targets, functional enrichment of key target genes, and signaling pathway analysis were performed through Search Tool for the Retrieval of Interacting Genes databases, Metascape databases, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases. Finally, the affinity of the key active components with the core targets was verified by molecular docking. The results showed that five core targets had been screened, including MAPK1, NF-κB1, RELA, AKT1, and MAPK14. Gene ontology enrichment analysis revealed that the key targets were associated with inflammatory responses and responses to external stimuli. KEGG enrichment analysis indicated that the main pathways were influenza A, hepatitis B, Toll-like receptor signaling pathway, NOD-like receptor signaling pathway, and TNF signaling pathway. Therefore, Xinguan No. 3 might play a role in treating COVID-19 through anti-inflammatory, immune responses, and regulatory responses to external stimuli.

Influence of Harvest Time on the Chemical Profile of Pereskia aculeate Mill. Using Paper Spray Mass Spectrometry

This study evaluated the physicochemical characteristics and the production of bioactive compounds of Pereskia aculeata Mill. at different harvest times. Here, we performed a qualitative evaluation of the chemical profile by paper spray mass spectrometry (PSMS), the phenolic acid and flavonoid profile by high-performance liquid chromatography (HPLC), antioxidant activity, total carotenoids, total phenolic compounds, total flavonoids, total anthocyanins, color characteristics, total soluble solids (TSS), total solids (TS), pH, and total titratable acidity (TTA). The chemical profile was not affected, with the exception of 4,5-dimethyl-2,6-octadiene and azelaic acid, which was only identified in the leaves harvested during the winter. The content of four phenolic acids and three flavonoids were analyzed; out of these, no significant amounts of ellagic acid and quercetin were detected. There was no difference in production of bioactive compounds between seasons, reflecting the antioxidant activity, which also did not differ. Brightness, chroma, and leaf pH were the only physicochemical characteristics that did not vary between seasons.

Efficacy and mechanisms of traditional Chinese medicine for COVID-19: a systematic review

Since the outbreak of coronavirus disease 2019 (COVID-19), traditional Chinese medicine (TCM) has made an important contribution to the prevention and control of the epidemic. This review aimed to evaluate the efficacy and explore the mechanisms of TCM for COVID-19. We systematically searched 7 databases from their inception up to July 21, 2021, to distinguish randomized controlled trials (RCTs), cohort studies (CSs), and case–control studies (CCSs) of TCM for COVID-19. Two reviewers independently completed the screening of literature, extraction of data, and quality assessment of included studies. Meta-analysis was performed using Review Manager 5.4 software. Eventually, 29 RCTs involving 3060 patients and 28 retrospective studies (RSs) involving 12,460 patients were included. The meta-analysis demonstrated that TCM could decrease the proportion of patients progressing to severe cases by 55% and the mortality rate of severe or critical patients by 49%. Moreover, TCM could relieve clinical symptoms, curtail the length of hospital stay, improve laboratory indicators, and so on. In addition, we consulted the literature and obtained 149 components of Chinese medicinal herbs that could stably bind to antiviral targets or anti-inflammatory or immune-regulating targets by the prediction of molecular docking. It suggested that the mechanisms involved anti-virus, anti-inflammation, and regulation of immunity. Our study made a systematic review on the efficacy of TCM for COVID-19 and discussed the possible mechanisms, which provided clinical reference and theoretical basis for further research on the mechanism of TCM for COVID-19.

Immunometabolism at the service of traditional Chinese medicine

To enhance therapeutic efficacy and reduce adverse effects, ancient practitioners of traditional Chinese medicine (TCM) prescribe combinations of plant species/animal species and minerals designated "TCM formulae" developed based on TCM theory and clinical experience. TCM formulae have been shown to exert curative effects on complex diseases via immune regulation but the underlying mechanisms remain unknown at present. Considerable progress in the field of immunometabolism, referring to alterations in the intracellular metabolism of immune cells that regulate their function, has been made over the past decade. The core context of immunometabolism is regulation of the allocation of metabolic resources supporting host defense and survival, which provides a critical additional dimension and emerging insights into how the immune system and metabolism influence each other during disease progression. This review summarizes research findings on the significant association between the immune function and metabolic remodeling in health and disease as well as the therapeutic modulatory effects of TCM formulae on immunometabolism. Progressive elucidation of the immunometabolic mechanisms involved during the course of TCM treatment continues to aid in the identification of novel potential targets against pathogenicity. In this report, we have provided a comprehensive overview of the benefits of TCM based on regulation of immunometabolism that are potentially applicable for the treatment of modern diseases.

Discovery and identification of potential anti-melanogenic active constituents of Bletilla striata by zebrafish model and molecular docking

BACKGROUND

Bletilla striata is the main medicine of many skin whitening classic formulas in traditional Chinese medicine (TCM) and is widely used in cosmetic industry recently. However, its active ingredients are still unclear and its fibrous roots are not used effectively. The aim of the present study is to discover and identify its potential anti-melanogenic active constituents by zebrafish model and molecular docking.

METHODS

The antioxidant activities were evaluated by 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, 2,2'-azino-bis-(3-ethylbenthiazoline-6-sulphonic acid) (ABTS) radical scavenging activity and ferric reducing antioxidant power (FRAP) assay. The anti-melanogenic activity was assessed by tyrosinase inhibitory activity in vitro and melanin inhibitory in zebrafish. The chemical profiles were performed by ultra-high-performance liquid chromatography combined with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS). Meanwhile, the potential anti-melanogenic active constituents were temporary identified by molecular docking.

RESULTS

The 95% ethanol extract of B. striata fibrous roots (EFB) possessed the strongest DPPH, ABTS, FRAP and tyrosinase inhibitory activities, with IC50 5.94 mg/L, 11.69 mg/L, 6.92 mmol FeSO4/g, and 58.92 mg/L, respectively. In addition, EFB and 95% ethanol extract of B. striata tuber (ETB) significantly reduced the melanin synthesis of zebrafish embryos in a dose-dependent manner. 39 chemical compositions, including 24 stilbenoids were tentatively identified from EFB and ETB. Molecular docking indicated that there were 83 (including 60 stilbenoids) and 85 (including 70 stilbenoids) compounds exhibited stronger binding affinities toward tyrosinase and adenylate cyclase.

CONCLUSION

The present findings supported the rationale for the use of EFB and ETB as natural skin-whitening agents in pharmaceutical and cosmetic industries.

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

Background

The recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.

Methods

RNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.

Results

Based on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19's main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis.

Conclusion

This study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.