Abstract: In recent years, traditional Chinese medicine has played an important role in the treatment of gastric cancer in China. ZiYinHuaTan (ZYHT) recipe was developed for advanced gastric cancer and had shown its promising value in the clinic. In this study, we explore the effect of ZYHT on gastric cancer in vitro and in vivo. ZYHT can inhibit tumor growth and improve the general condition of mice in subcutaneous transplantation nude mice models of gastric cancer. And ZYHT can also inhibit cell proliferation and blocked the cells in G0/G1 to induce cell apoptosis in HGC27 and MGC803 cells. Then, network pharmacology analysis showed that ZYHT may exert antitumor effect mainly through PI3K/AKT signaling pathway. Furthermore, the expression of PI3K, p-Akt, CyclinD1, and Bcl-2 was detected in vitro and in vivo. The results showed that ZYHT could decrease the expression of PI3K, CyclinD1, and Bcl-2 both in vitro and in vivo. These results suggested that ZYHT could be used as a method for the treatment of developed gastric cancer.

Abstract: Heart failure (HF), a clinical syndrome with a high incidence due to various reasons, is the advanced stage of most cardiovascular diseases. Huangqi is an effective treatment for cardiovascular disease, which has multitarget, multipathway functions. Therefore, we used network pharmacology to explore the molecular mechanism of Huangqi in treating HF. In this study, 21 compounds of Huangqi, which involved 407 targets, were obtained and reconfirmed using TCMSP and PubChem databases. Moreover, we used Cytoscape 3.7.1 to construct compound-target network and screened the top 10 compounds. 378 targets related to HF were obtained from CTD and GeneCards databases and HF-target network was constructed by Cytoscape 3.7.1. The 46 overlapping targets of HF and Huangqi were gotten by Draw Venn Diagram. STRING database was used to set up a protein-protein interaction network, and MCODE module and the top 5 targets with the highest degree for overlapping targets were obtained. GO analysis performed by Metascape indicated that the overlapping targets were mainly enriched in blood vessel development, reactive oxygen species metabolic process, response to wounding, blood circulation, and so on. KEGG analysis analyzed by ClueGO revealed that overlapping targets were mainly enriched in AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, HIF-1 signaling pathway, c-type lectin receptor signaling pathway, relaxin signaling pathway, and so on. Finally, molecular docking showed that top 10 compounds of Huangqi also had good binding activities to important targets compared with digoxin, which was carried out in CB-Dock molecular docking server. In conclusion, Huangqi has potential effect on regulating overlapping targets and GE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, HIF-1 signaling pathway, and so on to be a latent multitarget, multipathway treatment for HF.

Abstract: Introduction: The extreme health and economic problems in the world due to the SARS-CoV-2 infection have led to an urgent need to identify potential drug targets for treating coronavirus disease 2019 (COVID-19). The present state-of-the-art tool-based screening was targeted to identify drug targets among clinically approved drugs by uncovering SARS-CoV-2 helicase inhibitors through molecular docking analysis. Material and methods: Helicase is a vital viral replication enzyme, which unwinds nucleic acids and separates the double-stranded nucleic acids into single-stranded nucleic acids. Hence, the SARS-CoV-2 helicase protein 3D structure was predicted, validated, and used to screen the druggable targets among clinically approved drugs such as protease inhibitor, nucleoside reverse transcriptase inhibitor, and non-nucleoside reverse transcriptase inhibitors, used to treat HIV infection using molecular docking analysis. Results: Interaction with SARS-CoV-2 helicase, approved drugs, vapreotide (affinity: -12.88; S score: -9.84 kcal/mol), and atazanavir (affinity: -11.28; S score: -9.32 kcal/mol), approved drugs for treating AIDS-related diarrhoea and HIV infection, respectively, are observed with significantly low binding affinity and MOE score or binding free energy. The functional binding pockets of the clinically approved drugs on SARS-CoV-2 helicase protein molecule suggest that vapreotide and atazanavir may interrupt the activities of the SARS-CoV-2 helicase. Conclusions: The study suggests that vapreotide may be a choice of drug for wet lab studies to inhibit the infection of SARS-CoV-2.

Abstract: Stroke is the second leading cause of death after heart disease globally and cerebral ischemic stroke accounts for approximately 70% of all incident stroke cases. We selected four main compounds from a patent Chinese medicine, Qingkailing (QKL) injection, including baicalin from Scutellaria baicalensis Georgi (Huang Qin), geniposide from Gardenia jasminoides J. Ellis (Zhizi), and cholic acid and hyodeoxycholic acid from Bovis Calculus (Niuhuang) with a ratio of 4.4:0.4:3:2.6 m/m, to develop a more efficacious and safer modern Chinese medicine injection against ischemic stroke, refined QKL (RQKL). In this study, we investigated multiple targets, levels, and pathways of RQKL by using an integrative pharm\acology combining experimental validation approach. In silica study showed that RQKL may regulate PI3K-Akt, estrogen, neurotrophin, HIF-1, MAPK, Hippo, FoxO, TGF-beta, NOD-like receptor, apoptosis, NF-kappa B, Wnt, chemokine, TNF, Toll-like receptor signaling pathways against ischemic stroke. The experimental results showed that RQKL improved neurological function and prevented infract volume and blood-brain-barrier damage. RQKL inhibited microgliosis and astrogliosis, and protected neurons from ischemic/reperfusion injury. RQKL also inhibited cell apoptosis and affecting the ratio of the anti-apoptosis protein B-cell lymphoma-2 (Bcl2) and pro-apoptosis protein Bcl2-associated X protein (Bax). Western blot analysis showed that RQKL activated AKT/PI3K signaling pathway and antibody array showed RQKL inhibited inflammatory response and decreased proinflammatory factor Tnf, Il6, and Il1b, and chemokines Ccl2, Cxcl2, and Cxcl3, and increased anti-inflammatory cytokine Il10. In conclusion, RQKL protected tissue against ischemic stroke through multiple-target, multiple signals, and modulating multiple cell-types in brain. This study not only promoted our understanding of the role of RQKL against ischemic stroke, but also provided a pattern for the study of Chinese medicine combining pharmaceutical Informatics and system biology methods.

Abstract: Drug-drug interactions (DDI) can cause severe adverse drug reactions and pose a major challenge to medication therapy. Recently, informatics-based approaches are emerging for DDI studies. In this paper, we aim to identify key pharmacological components in DDI based on large-scale data from DrugBank, a comprehensive DDI database. With pharmacological components as features, logistic regression is used to perform DDI classification with a focus on searching for most predictive features, a process of identifying key pharmacological components. Using univariate feature selection with chi-squared statistic as the ranking criteria, our study reveals that top 10% features can achieve comparable classification performance compared to that using all features. The top 10% features are identified to be key pharmacological components. Furthermore, their importance is quantified by feature coefficients in the classifier, which measures the DDI potential and provides a novel perspective to evaluate pharmacological components.

Abstract: Materials and Methods: (1) Based on system-pharmacology platform, the potential active compounds of DB are screened out according to ADME. (2) The ischemic stroke-related targets are predicted by utilizing these active compounds as probes, mapping the targets to the CTD database to establish a molecular-target-disease network. (3) To analyze the mechanism of DB treatment for the prognosis of ischemic stroke, we used the Metascape and DAVID databases to construct "ischemic stroke pathways". (4) PC12 cells were used to explore the protective effect of loureirin B on oxygen-glucose deprivation/reperfusion (OGD/R) injury, and BV-2 cells were used to determine the anti-inflammation effect of 4',7-dihydroxyflavone. Results: Finally, we obtained 38 active compounds and 58 stroke-related targets. Network and pathway analysis indicate that DB is effective in the treatment of ischemic stroke by enhancing cell survival and inhibiting inflammatory and antiplatelet activation. In in vitro experiments, the main component loureirin B promoted the expression of HO-1 and Bcl-2 via positive regulation of PI3K/AKT/CREB and Nrf2 signaling pathways in PC12 cells against OGD/R damage. And the anti-in fl ammatory activity of 4',7-dihydroxyflavone was related to the inhibition of COX-2, TNF-alpha, and IL-6 in LPS-induced BV-2 cells. Conclusions: In our study, the results illustrated that DB in improving ischemic stroke prognosis may involve enhancing cell survival and antioxidant, anti-inflammation, and antiplatelet activities.

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection depends on viral polyprotein processing, catalysed by the main proteinase (Mpro). The solution of the SARS-CoV-2 Mpro structure allowed the investigation of potential inhibitors. This work aims to provide first evidences of the applicability of commercially approved drugs to treat coronavirus disease-19 (COVID-19). We screened 4,334 compounds to found potential inhibitors of SARS-CoV-2 replication using an in silico approach. Our results evidenced the potential use of coagulation modifiers in COVID-19 treatment due to the structural similarity of SARS-CoV-2 Mpro and human coagulation factors thrombin and Factor Xa. Further in vitro and in vivo analysis are needed to corroborate these results.

Abstract: Background: HeChan tablet (HCT) is a traditional Chinese medicine preparation extensively prescribed to treat lung cancer in China. However, the pharmacological mechanisms of HCT on lung cancer remain to be elucidated. Methods: A comprehensive network pharmacology-based strategy was conducted to explore underlying mechanisms of HCT on lung cancer. Putative targets and compounds of HCT were retrieved from TCMSP and BATMAN-TCM databases; related genes of lung cancer were retrieved from OMIM and DisGeNET databases; known therapeutic target genes of lung cancer were retrieved from TTD and DrugBank databases; PPI networks among target genes were constructed to filter hub genes by STRING. Furthermore, the pathway and GO enrichment analysis of hub genes was performed by clusterProfiler, and the clinical significance of hub genes was identified by The Cancer Genome Atlas. Result: A total of 206 compounds and 2,433 target genes of HCT were obtained. 5,317 related genes of lung cancer and 77 known therapeutic target genes of lung cancer were identified. 507 unique target genes were identified among HCT-related genes of lung cancer and 34 unique target genes were identified among HCT-known therapeutic target genes of lung cancer. By PPI networks, 11 target genes AKT1, TP53, MAPK8, JUN, EGFR, TNF, INS, IL-6, MYC, VEGFA, and MAPK1 were identified as major hub genes. IL-6, JUN, EGFR, and MYC were shown to associate with the survival of lung cancer patients. Five compounds of HCT quercetin, luteolin, kaempferol, beta-sitosterol, and baicalein were recognized as key compounds of HCT on lung cancer. The gene enrichment analysis implied that HCT probably benefitted patients with lung cancer by modulating the MAPK and PI3K-Akt pathways. Conclusion: This study predicted pharmacological and molecular mechanisms of HCT against lung cancer and could pave the way for further experimental research and clinical application of HCT.

Abstract: Chronic obstructive pulmonary disease (COPD) is a global high-incidence chronic airway inflammation disease. Its deterioration will lead to more serious lung lesions and even lung cancer. Therefore, it is urgent to determine the pathogenesis of COPD and find potential therapeutic targets. The purpose of this study is to reveal the molecular mechanism of COPD disease development through in-depth analysis of transcription factors and ncRNA-driven pathogenic modules of COPD. We obtained the expression profile of COPD-related microRNAs from the NCBI-GEO database and analyzed the differences among groups to identify the microRNAs significantly associated with COPD. Then, their target genes are predicted and mapped to a protein-protein interaction (PPI) network. Finally, key transcription factors and the ncRNA of the regulatory module were identified based on the hypergeometric test. The results showed that CUL1 was the most interactive gene in the highly interactive module, so it was recognized as a dysfunctional molecule of COPD. Enrichment analysis also showed that it was much involved in the biological process of organelle fission, the highest number of regulatory modules. In addition, ncRNAs, mainly composed of miR-590-3p, miR-495-3p, miR-186-5p, and transcription factors such as MYC, BRCA1, and CDX2, significantly regulate COPD dysfunction blocks. In summary, we revealed that the COPD-related target gene CUL1 plays a key role in the potential dysfunction of the disease. It promotes the proliferation of fibroblast cells in COPD patients by mediating functional signals of organelle fission and thus participates in the progress of the disease. Our research helps biologists to further understand the etiology and development trend of COPD.

Abstract: Objective: To elucidate the pharmacological mechanisms of Qubi Formula (QBF), a traditional Chinese medicine (TCM) formula which has been demonstrated as an effective therapy for psoriasis in China. Methods: The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, BATMAN-TCM database, and literature search were used to excavate the pharmacologically active ingredients of QBF and to predict the potential targets. Psoriasis-related targets were obtained from Therapeutic Target Database (TTD), DrugBank database (DBD), MalaCards database, and DisGeNET database. Then, we established the network concerning the interactions of potential targets of QBF with well-known psoriasis-related targets by using protein-protein interaction (PPI) data in String database. Afterwards, topological parameters (including DNMC, Degree, Closeness, and Betweenness) were calculated to excavate the core targets of Qubi Formula in treating psoriasis (main targets in the PPI network). Cytoscape was used to construct the ingredients-targets core network for Qubi Formula in treating psoriasis, and ClueGO was used to perform GO-BP and KEGG pathway enrichment analysis on these core targets. Results: The ingredient-target-disease core network of QBF in treating psoriasis was screened to contain 175 active ingredients, which corresponded to 27 core targets. Additionally, enrichment analysis suggested that targets of QBF in treating psoriasis were mainly clustered into multiple biological processes (associated with nuclear translocation of proteins, cellular response to multiple stimuli (immunoinflammatory factors, oxidative stress, and nutrient substance), lymphocyte activation, regulation of cyclase activity, cell-cell adhesion, and cell death) and related pathways (VEGF, JAK-STAT, TLRs, NF-kappaB, and lymphocyte differentiation-related pathways), indicating the underlying mechanisms of QBF on psoriasis. Conclusion: In this work, we have successfully illuminated that Qubi Formula could relieve a wide variety of pathological factors (such as inflammatory infiltration and abnormal angiogenesis) of psoriasis in a "multicompound, multitarget, and multipathway" manner by using network pharmacology. Moreover, our present outcomes might shed light on the further clinical application of QBF on psoriasis treatment.