Comparative proteomics reveals new insights into the endosperm responses to drought, salinity and submergence in germinating wheat seeds

Beyond the role of a nutrient reservoir during germination, the endosperm of wheat seeds also responds to different abiotic stresses via modification of the protein profiles. The endosperm is the main component of wheat seeds. During seed germination, it provides nutrients to support the embryo development, and its constituents vary under environmental stresses such as drought, salinity and submergence that are associated with disordered water supply. However, the molecular mechanism of these stress responses remains unclear. In this study, a comparative label-free proteomic analysis was performed on endosperm from the germinating wheat seeds subjected to PEG, NaCl and submergence treatments. In total, 2273 high confidence proteins were detected, and 234, 207 and 209 of them were identified as differentially expressed proteins (DEPs) under the three stresses, respectively. Functional classification revealed that the DEPs were mainly involved in protein, amino acid and organic acid metabolic process in all stress treatments. While some other metabolic processes were highlighted in one or two of the stresses specifically, such as oxidative phosphorylation in PEG and submergence, and β-alanine metabolism in PEG and NaCl treatments. The identification of a series of stress-related proteins and their biased expression in different stresses indicates the active stress-responding role of endosperm beyond a simple nutrient reservoir during germination, while the overall stress responses of the endosperm were found to be moderate and lag behind the embryo. Besides, some fundamental processes and DEPs shared by the three stresses could be selected priorly for future molecular breeding researches. Our results provide new insights into the mechanism of endosperm responses to abiotic stresses during seed germination.

Using Network Pharmacology to Explore the Mechanism of Peach Kernel-Safflower in the Treatment of Diabetic Nephropathy

OBJECTIVE

The mechanism of peach kernel-safflower in treating diabetic nephropathy (DN) was investigated using network pharmacology.

METHODS

Network pharmacology methodology was applied to screen the effective compounds of peach kernel-safflower in the SymMap and TCMSP databases. Potential targets were then screened in the ETCM, SEA, and SymMap databases to construct a compound-target network. This was followed by screening of DN targets in OMIM, Gene, and GeneCards databases. The common targets of drugs and diseases were selected for analysis in the STRING database, and the results were imported into Cytoscape 3.8.0 to construct a protein-protein interaction network. Next, GO and KEGG enrichment analyses were performed. Finally, Schrödinger molecular docking verified the reliability of the results.

RESULTS

A total of 23 effective compounds and 794 potential targets resulted from our screening process. Quercetin and luteolin were identified as the main effective ingredients in peach kernel-safflower. Furthermore, five key targets (VEGFA, IL6, TNF, AKT1, and TP53), AGE-RAGE, fluid shear stress and atherosclerosis, IL-17, and HIF-1 signaling pathways may be involved in the treatment of DN using peach kernel-safflower.

CONCLUSIONS

This study embodies the complex network relationship of multicomponents, multitargets, and multipathways of peach kernel-safflower to treat DN and provides a basis for further research on its mechanism.

Network pharmacology for the identification of phytochemicals in traditional Chinese medicine for COVID-19 that may regulate interleukin-6

OBJECTIVE

´Three formulas and three medicines,' namely, Jinhua Qinggan Granule, Lianhua Qingwen Capsule, Xuebijing Injection, Qingfei Paidu Decoction, HuaShi BaiDu Formula, and XuanFei BaiDu Granule, were proven to be effective for coronavirus disease 2019 (COVID-19) treatment. The present study aimed to identify the active chemical constituents of this traditional Chinese medicine (TCM) and investigate their mechanisms through interleukin-6 (IL-6) integrating network pharmacological approaches.

METHODS

We collected the compounds from all herbal ingredients of the previously mentioned TCM, but those that could down-regulate IL-6 were screened through the network pharmacology approach. Then, we modeled molecular docking to evaluate the binding affinity between compounds and IL-6. Furthermore, we analyzed the biological processes and pathways of compounds. Finally, we screened out the core genes of compounds through the construction of the protein-protein interaction network and the excavation of gene clusters of compounds.

RESULTS

The network pharmacology research showed that TCM could decrease IL-6 using several compounds, such as quercetin, ursolic acid, luteolin, and rutin. Molecular docking results showed that the molecular binding affinity with IL-6 of all compounds except γ-aminobutyric acid was < -5.0 kJ/mol, indicating the potential of numerous active compounds in TCM to directly interact with IL-6, leading to an anti-inflammation effect. Finally, Cytoscape 3.7.2 was used to topologize the biological processes and pathways of compounds, revealing potential mechanisms for COVID-19 treatment.

CONCLUSION

These results indicated the positive effect of TCM on the prevention and rehabilitation of COVID-19 in at-risk people. Quercetin, ursolic acid, luteolin, and rutin could inhibit COVID-19 by down-regulating IL-6.

Functional lncRNA-miRNA-mRNA Networks in Response to Baicalein Treatment in Hepatocellular Carcinoma

INTRODUCTION

Baicalein has been shown to have antitumor activities in several cancer types. However, its acting mechanisms remain to be further investigated. This work is aimed at exploring the functional long noncoding RNA (lncRNA)/microRNA (miRNA)/messenger RNA (mRNA) triplets in response to baicalein in hepatocellular carcinoma (HCC) cell to understand the mechanisms of baicalein in HCC.

METHODS

Differentially expressed lncRNAs (DELs) and miRNAs (DEMs) in HCC cell treated with baicalein were first screened using GSE95504 and GSE85511, respectively. miRNA targets for DELs were predicted and intersected with DEMs, after which the miRNA expression was validated using ENCORI and its prognostic value was assessed using Kaplan-Meier plotter. Potential miRNA targets were predicted by 3 prediction tools, after which expression level was validated at UALCAN and Human Protein Atlas. Kaplan-Meier plotter was used to evaluate the effects of these genes on overall survival and recurrence-free survival of HCC patients. Enrichment analyses for these genes were performed at DAVID.

RESULTS

Here, we identified 14 overlapping DELs and 26 overlapping DEMs in the baicalein treatment group than those in the DMSO treatment group. Subsequently, by analyzing expression and clinical significance of miRNAs, hsa-miR-4443 was found as a highly potential miRNA target. Then, targets of hsa-miR-4443 were predicted and analyzed, and we found AKT1 was the most potential target for hsa-miR-4443. Hence, the lncRNAs-hsa-miR-4443-AKT1 axis that can respond to baicalein was established.

CONCLUSION

Collectively, we elucidated a role of lncRNAs-hsa-miR-4443-AKT1 pathway in response to baicalein treatment in HCC, which could help us understand the roles of baicalein in inhibiting cancer progression and may provide novel insights into the mechanisms behind HCC progression.

Mechanisms of Fritillariae Thunbergii Flos in lung cancer treatment from a systems pharmacology perspective

ETHNOPHARMACOLOGICAL RELEVANCE

Fritillariae Thunbergii Flos (FTF) included in the Chinese Pharmacopoeia (1977 Edition) is a Chinese medicinal herb traditionally used to treat bronchitis. In recent years, it has been applied in the treatment of lung cancer. However, the molecular mechanism remains largely unknown.

METHODS

The screening of bioactive compounds, acquisition of drug targets, network construction, and experimental validation in vivo were combined to explored the mechanism of FTF in the treatment of lung carcinoma with regards to systems pharmacology.

RESULTS

The network Lung Cancer Pathway consisted of 114 nodes (44 compounds and 70 potential targets) and 361 edges, as well as modules that included inflammatory response, angiogenesis, negative regulation of the apoptotic process, and positive regulation of cell proliferation and migration. It was examined by conducting experiments that involved the administration of ethanol-based extracts of FTF in Lewis lung carcinoma mice. The extracts exerted excellent anti-lung cancer effects in vivo by significantly inhibiting tumor proliferation, thereby extending the survival period of tumor-bearing mice. Moreover, FTF induced the downregulation of PIK3CG, Bcl-2, eNOS, VEGF, p-STAT3, and STAT3 genes in tumor-bearing mice.

CONCLUSIONS

The findings of the present study verify the therapeutic effects and mechanism of FTF on lung cancer and provide a theoretical basis to support the comprehensive utilization of FTF resources.

Network pharmacology analysis and experimental validation to explore the mechanism of sea buckthorn flavonoids on hyperlipidemia

ETHNOPHARMACOLOGICAL RELEVANCE

Sea buckthorn is popularly used as a herbal medicine and food additive in the world. Sea buckthorn flavonoids (SF) is reported to have an ameliorative effect on obesity and hyperlipidemia (HLP).

AIM

To identify the major bioactive compounds and the lipid-lowering mechanism of SF.

METHODS

We used network pharmacology analysis and in vitro experiments to identify the major bioactive compounds and the lipid-lowering mechanism of SF.

RESULTS

A total of 12 bioactive compounds, 60 targets related to SF and HLP were identified, and a component-target-disease network was constructed. The KEGG analysis revealed that SF regulated cholesterol metabolism, fat digestion and absorption, and PPAR signaling pathways in HLP. The experimental validation indicated that sea buckthorn flavonoids extract (SFE) and 4 bioactive compounds reduced lipid droplet accumulation, up-regulated the mRNA expression of PPAR-γ, PPAR-α, ABCA1 and CPT1A, etc, down-regulated SREBP-2 and its target gene LDLR, which are closely related to cholesterol conversion into bile acids, de novo synthesis and fatty acids oxidation. The major bioactive flavonoid isorhamnetin (ISOR) also increased the protein expression of PPAR-γ, LXRα and CYP7A1.

CONCLUSION

SF might promote cholesterol transformation into bile acids and cholesterol efflux, inhibit cholesterol de novo synthesis and accelerate fatty acids oxidation for ameliorating HLP.

An integrated network pharmacology and RNA-Seq approach for exploring the preventive effect of Lonicerae japonicae flos on LPS-induced acute lung injury

ETHNOPHARMACOLOGICAL RELEVANCE

Lonicerae japonicae flos (LJF, the dried flower bud or newly bloomed flower of Lonicera japonica Thunb.), a typical herbal medicine, targets the lung, heart and stomach meridian with the function of clearing heat and detoxication. It ameliorated inflammatory responses and protected against acute lung inflammation in animal models. Acute lung injury (ALI) is a kind of inflammatory disease in which alveolar cells are damaged. However, a network pharmacology study to thoroughly investigate the mechanisms preventing ALI has not been performed.

AIM OF THE STUDY

In this study, we examined the main active ingredients in LJF and the protective effects of LJF on LPS-induced ALI in rats.

MATERIALS AND METHODS

First, the main active ingredients of LJF were screened in the TCMSP database, and the ALI-associated targets were collected from the GeneCards database. Then, we used compound-target and target-pathway networks to uncover the preventive mechanisms of LJF. Furthermore, we assessed the preventive effects of LJF in an LPS-induced rat model with the RNA-Seq technique to validate the possible molecular mechanisms of the effects of LJF in the treatment of ALI.

RESULTS

The network pharmacology results identified 28 main active compounds in LJF, and eight chemical components highly related to the potential targets, which were potential active compounds in LJF. In all, 94 potential targets were recognized, including IL6, TNF, PTGS2, APP, F2, and GRM5. The pathways revealed that the possible targets of LJF involved in the regulation of the IL-17 signalling pathway. Then, in vivo experiments indicated that LJF decreased the levels of proinflammatory cytokines (TNF-, IL-1, and IL-6) in serum and bronchoalveolar lavage fluid, decreased the levels of oxidative stress factors (MDA and MPO) and increased the activities of SOD and GSH-Px in lung tissue. The RNA-Seq results revealed that 7811, 775 and 3654 differentially expressed genes (DEGs) in Ctrl (control group), ALI-LJF (Lonicerae japonicae flos group) and ALI-DXSM (dexamethasone group), respectively. KEGG pathway analysis showed that the DEGs associated with immune response and inflammation signalling pathways and the IL-17 signalling pathway were significantly enriched in LJF. Compared with those in ALI, the expression of CXCL2, CXCL1, CXCL6, NFKBIA, IFNG, IL6, IL17A, IL17F, IL17C, MMP9 and TNFAIP3, which are involved in the IL-17 signalling pathway, were significantly decreased in the LJF group according to the qRT-PCR analyses.

CONCLUSIONS

In view of the network pharmacology and RNA-Seq results, the study identified the main active ingredient and potential targets of LJF involved in protecting against ALI, which suggests directions for further research on LJF.

TMT-based proteomics analysis reveals the efficacy of jiangzhuo formula in improving the lipid profiles of dyslipidemia rats

ETHNOPHARMACOLOGICAL RELEVANCE

Jiangzhuo Formula (JZF) is a traditional Chinese herbal prescription that is clinically applied to treat dyslipidemia. However, the mechanism underlying its efficacy remains unexplored.

AIM OF THE STUDY

This study aims to elucidate the underlying mechanisms, explore potential pathways, and identify the key proteins of JZF for the treatment of dyslipidemia.

METHODS

In this work, Q-Orbitrap high-resolution liquid chromatography mass spectrometry was used to identify the natural ingredients in JZF, rats with dyslipidemia were established via a high-fat diet for four weeks, then the dyslipidemia rats were treated with high-dose JZF (9 g/d) and low-dose JZF (4.5 g/d) for four weeks. After treatment, serum lipid detection and Oil-red-O staining were conducted to assess the efficacy of JZF in ameliorating dyslipidemia. Tandem mass tag (TMT) -based quantitative proteomics technology was then used to evaluate the roles and importance of proteins from the extracted hepatic tissue. The differentially expressed proteins were assessed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, Gene Ontology (GO), and protein-protein interaction (PPI) networks. Western blot and PCR analysis were used to validate the potential targets regulated by JZF.

RESULTS

JZF could significantly improve the blood lipid profiles of serum and fat deposits of the liver. A total of 123 differentially expressed proteins were detected after JZF intervention, comprising 65 up-regulated proteins and 58 down-regulated proteins. The KEGG pathway analysis revealed that cholesterol metabolism, the PPAR signaling pathway, and bile secretion were the principal pathways involved in the disordered lipid metabolism, while GO analysis suggested that proteins that are located in the cell, regulate cellular processes, and show binding activity contribute to reductions in lipids. The combination of proteomics, Western blot, and PCR suggested that Apolipoprotein B (APOB), Apolipoprotein E (APOE), cholesterol 7 alpha-hydroxylase A1 (CYP7A1), and Hydroxymethylglutaryl-CoA synthase 1 (HMGCS1) might play critical roles in JZF's lipid-lowering network.

CONCLUSION

JZF can effectively improve lipid profiles via multiple pathways involved in cholesterol metabolism, the PPAR signaling pathway, and bile secretion. Generally, the proteomics techniques used in this research show that JZF could be a promising drug for the treatment of dyslipidemia.

Xiaoyaosan decoction alleviated rat liver fibrosis via the TGFβ/Smad and Akt/FoxO3 signaling pathways based on network pharmacology analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Liver fibrosis is an outcome of many chronic liver diseases and often results in cirrhosis, liver failure, and even hepatocarcinoma. Xiaoyaosan decoction (XYS) as a classical Traditional Chinese Medicine (TCM) formula is used to liver fibrosis in clinical practice while its mechanism is unclear.

AIM OF THE STUDY

The aim of this study was to investigate the anti-fibrosis effect of XYS and to explore the molecular mechanisms by combining network pharmacology and transcriptomic technologies.

MATERIALS AND METHODS

The carbon tetrachloride (CCl4)-induced liver fibrosis rat were treated with three doses of XYS. The liver fibrosis and function were evaluated by histopathological examination and serum biochemical detection. The fibrosis related protein a-SMA and collagen I were assessed by Western blot. Different expressed genes (DEGs) between XYS-treated group and model group were analyzed. The herb-component-target network was constructed combined the network pharmacology. The predict targets and pathways were validated by in vitro and in vivo experiments.

RESULTS

With XYS treatment, the liver function was significantly improved, and fibrotic changes were alleviated. The a-SMA and collagen I expression levels in the liver were also decreased in XYS-treated rats compared with CCl4 model rats. 108 active components and 42 targets from 8 herbs constituted herb-compound-target network by transcriptomics and network pharmacology analysis. The KEGG pathway and GO enrichment analyses showed that the FoxO, TGFβ, AMPK, MAPK, PPAR, and hepatitis B and C pathways were involved in the anti-fibrosis effects of XYS. In the liver tissues, p-FoxO3a and p-Akt expression levels were significantly increased in the CCl4 model group but decreased in the XYS-treated group. The TGFβ1/Smad pathway and Akt/FoxO3 pathway were verified in LX2 cells by inhibiting phosphorylation of Smad3 and Akt activity, respectively.

CONCLUSIONS

Our findings suggested that XYS markedly alleviated CCl4-induced liver fibrosis in histopathological and serum liver function analyses, and this effect may occur via the TGFβ1/Smad and Akt/FoxO signaling pathways.

Identification of Key Candidate Genes and Chemical Perturbagens in Diabetic Kidney Disease Using Integrated Bioinformatics Analysis

Globally, nearly 40 percent of all diabetic patients develop serious diabetic kidney disease (DKD). The identification of the potential early-stage biomarkers and elucidation of their underlying molecular mechanisms in DKD are required. In this study, we performed integrated bioinformatics analysis on the expression profiles GSE111154, GSE30528 and GSE30529 associated with early diabetic nephropathy (EDN), glomerular DKD (GDKD) and tubular DKD (TDKD), respectively. A total of 1,241, 318 and 280 differentially expressed genes (DEGs) were identified for GSE30258, GSE30529, and GSE111154 respectively. Subsequently, 280 upregulated and 27 downregulated DEGs shared between the three GSE datasets were identified. Further analysis of the gene expression levels conducted on the hub genes revealed SPARC (Secreted Protein Acidic And Cysteine Rich), POSTN (periostin), LUM (Lumican), KNG1 (Kininogen 1), FN1 (Fibronectin 1), VCAN (Versican) and PTPRO (Protein Tyrosine Phosphatase Receptor Type O) having potential roles in DKD progression. FN1, LUM and VCAN were identified as upregulated genes for GDKD whereas the downregulation of PTPRO was associated with all three diseases. Both POSTN and SPARC were identified as the overexpressed putative biomarkers whereas KNG1 was found as downregulated in TDKD. Additionally, we also identified two drugs, namely pidorubicine, a topoisomerase inhibitor (LINCS ID- BRD-K04548931) and Polo-like kinase inhibitor (LINCS ID- BRD-K41652870) having the validated role in reversing the differential gene expression patterns observed in the three GSE datasets used. Collectively, this study aids in the understanding of the molecular drivers, critical genes and pathways that underlie DKD initiation and progression.

Luteolin Potentially Treating Prostate Cancer and COVID-19 Analyzed by the Bioinformatics Approach: Clinical Findings and Drug Targets

Coronavirus disease 2019 (COVID-19) is a serious epidemic, characterized by potential mutation and can bring about poor vaccine efficiency. It is evidenced that patients with malignancies, including prostate cancer (PC), may be highly vulnerable to the SARS-CoV-2 infection. Currently, there are no existing drugs that can cure PC and COVID-19. Luteolin can potentially be employed for COVID-19 treatment and serve as a potent anticancer agent. Our present study was conducted to discover the possible drug target and curative mechanism of luteolin to serve as treatment for PC and COVID-19. The differential gene expression of PC cases was determined via RNA sequencing. The application of network pharmacology and molecular docking aimed to exhibit the drug targets and pharmacological mechanisms of luteolin. In this study, we found the top 20 up- and downregulated gene expressions in PC patients. Enrichment data demonstrated anti-inflammatory effects, where improvement of metabolism and enhancement of immunity were the main functions and mechanism of luteolin in treating PC and COVID-19, characterized by associated signaling pathways. Additional core drug targets, including MPO and FOS genes, were computationally identified accordingly. In conclusion, luteolin may be a promising treatment for PC and COVID-19 based on bioinformatics findings, prior to future clinical validation and application.

Biological Regulatory Network (BRN) Analysis and Molecular Docking Simulations to Probe the Modulation of IP3R Mediated Ca2+ Signaling in Cancer

Inositol trisphosphate receptor (IP3R) mediated Ca+2 signaling is essential in determining the cell fate by regulating numerous cellular processes, including cell division and cell death. Despite extensive studies about the characterization of IP3R in cancer, the underlying molecular mechanism initiating the cell proliferation and apoptosis remained enigmatic. Moreover, in cancer, the modulation of IP3R in downstream signaling pathways, which control oncogenesis and cancer progression, is not well characterized. Here, we constructed a biological regulatory network (BRN), and describe the remodeling of IP3R mediated Ca2+ signaling as a central key that controls the cellular processes in cancer. Moreover, we summarize how the inhibition of IP3R affects the deregulated cell proliferation and cell death in cancer cells and results in the initiation of pro-survival responses in resistance of cell death in normal cells. Further, we also investigated the role of stereo-specificity of IP3 molecule and its analogs in binding with the IP3 receptor. Molecular docking simulations showed that the hydroxyl group at R6 position along with the phosphate group at R5 position in 'R' conformation is more favorable for IP3 interactions. Additionally, Arg-266 and Arg-510 showed π-π and hydrogen bond interactions and Ser-278 forms hydrogen bond interactions with the IP3 binding site. Thus, they are identified as crucial for the binding of antagonists.

MNBDR: A Module Network Based Method for Drug Repositioning

Drug repurposing/repositioning, which aims to find novel indications for existing drugs, contributes to reducing the time and cost for drug development. For the recent decade, gene expression profiles of drug stimulating samples have been successfully used in drug repurposing. However, most of the existing methods neglect the gene modules and the interactions among the modules, although the cross-talks among pathways are common in drug response. It is essential to develop a method that utilizes the cross-talks information to predict the reliable candidate associations. In this study, we developed MNBDR (Module Network Based Drug Repositioning), a novel method that based on module network to screen drugs. It integrated protein-protein interactions and gene expression profile of human, to predict drug candidates for diseases. Specifically, the MNBDR mined dense modules through protein-protein interaction (PPI) network and constructed a module network to reveal cross-talks among modules. Then, together with the module network, based on existing gene expression data set of drug stimulation samples and disease samples, we used random walk algorithms to capture essential modules in disease development and proposed a new indicator to screen potential drugs for a given disease. Results showed MNBDR could provide better performance than popular methods. Moreover, functional analysis of the essential modules in the network indicated our method could reveal biological mechanism in drug response.

TMT-based quantitative proteomic analysis of antitumor mechanism of Sporisorium reilianum polysaccharide WM-NP-60 against HCT116 cells

Sporisorium reilianum is an active edible and medicinal phytopathogenic fungus. Our study indicated that the S. reilianum polysaccharide WM-NP-60 could inhibit the growth of HCT116 cells in a dose-dependent manner. In addition, WM-NP-60 could trigger the cell cycle of HCT116 arrest at the G₁ phase and induce its apoptosis. In order to explore the anti-tumor mechanism of WM-NP-60, TMT-based quantitative proteomic analysis was used. Results indicated that 369 differentially expressed proteins including 240 up-regulated and 129 down-regulated proteins in WM-NP-60 treated HCT116 cells compared with normal HCT116 cells. Furthermore, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that 192 pathways were enriched containing 15 metabolic pathways with significant difference (P < 0.05). The levels of mRNA and protein up-regulated TGFβR1, P107, DP1 and down-regulated THBS1 related to TGF-β signaling pathway were verified with qRT-PCR and Western Blot (WB). These findings will provide theoretical basis for the important role of fungal polysaccharides in the field of tumor treatment.

Large-Scale Characterization of Drug Responses of Clinically Relevant Proteins in Cancer Cell Lines

Perturbation biology is a powerful approach to modeling quantitative cellular behaviors and understanding detailed disease mechanisms. However, large-scale protein response resources of cancer cell lines to perturbations are not available, resulting in a critical knowledge gap. Here we generated and compiled perturbed expression profiles of ∼210 clinically relevant proteins in >12,000 cancer cell line samples in response to ∼170 drug compounds using reverse-phase protein arrays. We show that integrating perturbed protein response signals provides mechanistic insights into drug resistance, increases the predictive power for drug sensitivity, and helps identify effective drug combinations. We build a systematic map of "protein-drug" connectivity and develop a user-friendly data portal for community use. Our study provides a rich resource to investigate the behaviors of cancer cells and the dependencies of treatment responses, thereby enabling a broad range of biomedical applications.

A SYK/SHC1 pathway regulates the amount of CFTR in the plasma membrane

Mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene cause the recessive genetic disease cystic fibrosis, where the chloride transport across the apical membrane of epithelial cells mediated by the CFTR protein is impaired. CFTR protein trafficking to the plasma membrane (PM) is the result of a complex interplay between the secretory and membrane recycling pathways that control the number of channels present at the membrane. In addition, the ion transport activity of CFTR at the PM is modulated through post-translational protein modifications. Previously we described that spleen tyrosine kinase (SYK) phosphorylates a specific tyrosine residue in the nucleotide-binding domain 1 domain and this modification can regulate the PM abundance of CFTR. Here we identified the underlying biochemical mechanism using peptide pull-down assays followed by mass spectrometry. We identified in bronchial epithelial cells that the adaptor protein SHC1 recognizes tyrosine-phosphorylated CFTR through its phosphotyrosine-binding domain and that the formation of a complex between SHC1 and CFTR is induced at the PM in the presence of activated SYK. The depletion of endogenous SHC1 expression was sufficient to promote an increase in CFTR at the PM of these cells. The results identify a SYK/SHC1 pathway that regulates the PM levels of CFTR channels, contributing to a better understanding of how CFTR-mediated chloride secretion is regulated.

The synergistic antitumour effect of multi-components from Pulsatilla chinensis saponins in NCI-H460 lung cancer cell line through induction of apoptosis

Context: Pulsatilla chinensis (Bunge) Regel (Ranunculaceae) possess antitumour effects; however, its antitumour potential has not been extensively investigated.Objective: To investigate the synergetic effect of multi-components from P. chinensis induced cell apoptosis and explore the mechanism.Materials and methods: The cytotoxicity was measured against NCI-H460, SMMC-7721, HCT-116 and U251 cell lines treated with eight monomers from P. chinensis. The synergetic effect of a combination of Pulsatilla saponin D (PSD), Raddeanoside R13 (R13), and Pulsatilla saponin A (PSA) was assessed using CalcuSyn3.0. Annexin V-FITC/PI and DAPI staining analyzed apoptosis of NCI-H460 cells treated with PSD, R13 and PSA alone or in combination. Proteins differential expression was analyzed using proteomic, DAVID Bioinformatics Resources, R software environment and KEGG database, and verified by western blotting.Results: PSD, R13, and PSA displayed greater antitumor activity with IC₅₀ values of 5.6, 5.1 and 10.5 µM against NCI-H460 cells compared with other monomers. The combination of PSD, R13, and PSA had a synergistic effect at CI = 0.27 and induced 17.53% cells apoptotic detected by flow cytometric. Bioinformatic analysis showed an overview of the differentially expressed proteins and some signalling pathways. Moreover, some candidate proteins (LDHA, PI3K, NOL3 and cleaved-caspase-3) were validated by western blotting.Discussion and Conclusion: These results show PSD, R13, and PSA are good candidates as natural products for use in the treatment of lung cancer. Potential signalling pathways and protein targets need to be further validated. The application of the drug combination approach also provides a therapeutic strategy for cancer.

Uncovering the pharmacological mechanism of the effects of the Banxia-Xiakucao Chinese Herb Pair on sleep disorder by a systems pharmacology approach

Sleep disorder (SD) has a high incidence and seriously affects quality of life, mental health and even the manifestation of physical diseases. The combination of Pinellia ternata (Chinese name: banxia) and Prunella vulgaris (Chinese name: xiakucao), known as the Banxia-Xiakucao Chinese herb pair (BXHP), is a proven Chinese herbal medicine that has been used to treat SD for thousands of years due to its significant clinical effects. However, its active pharmacological components and sedative-hypnotic mechanisms have not been fully elucidated. Thus, the present study used a systematic pharmacological approach to develop pharmacokinetic screens and target predictions via construction of a protein-protein interaction network and annotation database for SD-related and putative BXHP-related targets. Visualization, screening and integrated discovery enrichment analyses were conducted. The BXHP chemical database contains 166 compounds between the two herbal ingredients, and of these, 22 potential active molecules were screened by pharmacokinetic evaluation. The targets of 114 of the active molecules were predicted, and 34 were selected for further analysis. Finally, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses suggested that BXHP can reduce inflammatory responses. and mediate immune-related and central nervous system neurotransmitters via regulation of multiple targets and pathways. The use of a systematic pharmacology-based approach in the present study further elucidated the mechanisms of action underlying BXHP for the treatment of SD from a holistic perspective and sheds light on the systemic mechanisms of action of Chinese herbal medicines in general.

Quantifying the Selectivity of Protein-Protein and Small Molecule Interactions with Fluorinated Tandem Bromodomain Reader Proteins

Multidomain bromodomain-containing proteins regulate gene expression via chromatin binding, interactions with the transcriptional machinery, and by recruiting enzymatic activity. Selective inhibition of members of the bromodomain and extra-terminal (BET) family is important to understand their role in disease and gene regulation, although due to the similar binding sites of BET bromodomains, selective inhibitor discovery has been challenging. To support the bromodomain inhibitor discovery process, here we report the first application of protein-observed fluorine (PrOF) NMR to the tandem bromodomains of BRD4 and BRDT to quantify the selectivity of their interactions with acetylated histones as well as small molecules. We further determine the selectivity profile of a new class of ligands, 1,4-acylthiazepanes, and find them to have ≥3-10-fold selectivity for the C-terminal bromodomain of both BRD4 and BRDT. Given the speed and lower protein concentration required over traditional protein-observed NMR methods, we envision that these fluorinated tandem proteins may find use in fragment screening and evaluating nucleosome and transcription factor interactions.

Quantitative Structure-Mutation-Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction

BACKGROUND

Protein kinases are a large family of druggable proteins that are genomically and proteomically altered in many human cancers. Kinase-targeted drugs are emerging as promising avenues for personalized medicine because of the differential response shown by altered kinases to drug treatment in patients and cell-based assays. However, an incomplete understanding of the relationships connecting genome, proteome and drug sensitivity profiles present a major bottleneck in targeting kinases for personalized medicine.

RESULTS

In this study, we propose a multi-component Quantitative Structure-Mutation-Activity Relationship Tests (QSMART) model and neural networks framework for providing explainable models of protein kinase inhibition and drug response ([Formula: see text]) profiles in cell lines. Using non-small cell lung cancer as a case study, we show that interaction terms that capture associations between drugs, pathways, and mutant kinases quantitatively contribute to the response of two EGFR inhibitors (afatinib and lapatinib). In particular, protein-protein interactions associated with the JNK apoptotic pathway, associations between lung development and axon extension, and interaction terms connecting drug substructures and the volume/charge of mutant residues at specific structural locations contribute significantly to the observed [Formula: see text] values in cell-based assays.

CONCLUSIONS

By integrating multi-omics data in the QSMART model, we not only predict drug responses in cancer cell lines with high accuracy but also identify features and explainable interaction terms contributing to the accuracy. Although we have tested our multi-component explainable framework on protein kinase inhibitors, it can be extended across the proteome to investigate the complex relationships connecting genotypes and drug sensitivity profiles.

Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients

Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. However, current machine-learning-based predictions of drug response often fail to identify robust translational biomarkers from preclinical models. Here, we present a machine-learning framework to identify robust drug biomarkers by taking advantage of network-based analyses using pharmacogenomic data derived from three-dimensional organoid culture models. The biomarkers identified by our approach accurately predict the drug responses of 114 colorectal cancer patients treated with 5-fluorouracil and 77 bladder cancer patients treated with cisplatin. We further confirm our biomarkers using external transcriptomic datasets of drug-sensitive and -resistant isogenic cancer cell lines. Finally, concordance analysis between the transcriptomic biomarkers and independent somatic mutation-based biomarkers further validate our method. This work presents a method to predict cancer patient drug responses using pharmacogenomic data derived from organoid models by combining the application of gene modules and network-based approaches.

A novel HIV-1 inhibitor that blocks viral replication and rescues APOBEC3s by interrupting vif/CBFβ interaction

HIV remains a health challenge worldwide, partly because of the continued development of resistance to drugs. Therefore, it is urgent to find new HIV inhibitors and targets. Apolipoprotein B mRNA-editing catalytic polypeptide-like 3 family members (APOBEC3) are important host restriction factors that inhibit HIV-1 replication by their cytidine deaminase activity. HIV-1 viral infectivity factor (Vif) promotes proteasomal degradation of APOBEC3 proteins by recruiting the E3 ubiquitin ligase complex, in which core-binding factor β (CBFβ) is a necessary molecular chaperone. Interrupting the interaction between Vif and CBFβ can release APOBEC3 proteins to inhibit HIV-1 replication and may be useful for developing new drug targets for HIV-1. In this study, we identified a potent small molecule inhibitor CBFβ/Vif-3 (CV-3) of HIV-1 replication by employing structure-based virtual screening using the crystal structure of Vif and CBFβ (PDB: 4N9F) and validated CV-3's antiviral activity. We found that CV-3 specifically inhibited HIV-1 replication (IC50 = 8.16 µm; 50% cytotoxic concentration >100 µm) in nonpermissive lymphocytes. Furthermore, CV-3 treatment rescued APOBEC3 family members (human APOBEC3G (hA3G), hA3C, and hA3F) in the presence of Vif and enabled hA3G packaging into HIV-1 virions, which resulted in Gly-to-Ala hypermutations in viral genomes. Finally, we used FRET to demonstrate that CV-3 inhibited the interaction between Vif and CBFβ by simultaneously forming hydrogen bonds with residues Gln-67, Ile-102, and Arg-131 of CBFβ. These findings demonstrate that CV-3 can effectively inhibit HIV-1 by blocking the interaction between Vif and CBFβ and that this interaction can serve as a new target for developing HIV-1 inhibitors.

Interactome analysis of gene expression profiles identifies CDC6 as a potential therapeutic target modified by miR-215-5p in hepatocellular carcinoma

Background: Illustrating the pathogenesis of hepatocellular carcinoma (HCC) pathogenesis as well as identifying specific biomarkers are of great significance. Methods: The original CEL files were obtain from Gene Expression Omnibus, then affymetrix package was used to preprocess the CEL files, the function of DEGs were investigated by multiple bioinformatics approach. Finally, typical HCC cell lines and tissue samples were using to validate the role of CDC6 in vitro. Bioinformatics software was used to predict potential microRNA of CDC6. Luciferase assay was used to verify the interactions between CDC6 and microRNA. Results: A total of 445 DEGs were identified in HCC tissues based on two GEO datasets. GSEA results showed that the significant enriched gene sets were only associated with cell cycle signaling pathway. In the co-expression analysis, there were 370 hub genes from the blue modules were screened. We integrated DEGs, hub genes, TCGA cohort and GSEA analyses to further obtain 10 upregulated genes for validation. These genes were overexpressed in HCC tissues and negatively associated with overall and disease-free survival in HCC patients and related to immune cell infiltration in HCC microenvironments. Finally, Cell Division Cycle 6 (CDC6) was highlighted as one of the most probable genes among the 10 candidates participating in cancer process. The expression of CDC6 either in public datasets and HCC tissues sample were commonly high than the non-cancerous counterpart. Furthermore, we recognized that miR-215-5p, could directly bind to the 3'UTR of CDC6. In addition, CDC6 promoted proliferation via regulation of G1 phase checkpoint and was negative regulated by miR-215-5p to involve in the proliferation of HCC. Conclusion: Our study suggested that CDC6 served as a potential therapeutic target for HCC.

Identification of the significant pathways of Banxia Houpu decoction in the treatment of depression based on network pharmacology

Banxia Houpu decoction (BXHPD) has been used to treat depression in clinical practice for centuries. However, the pharmacological mechanisms of BXHPD still remain unclear. Network Pharmacology (NP) approach was used to explore the potential molecular mechanisms of BXHPD in treating depression. Potential active compounds of BXHPD were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform Database. STRING database was used to build a interaction network between the active compounds and target genes associated with depression. The topological features of nodes were visualized and calculated. Significant pathways and biological functions were identified using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. A total of 44 active compounds were obtained from BXHPD, and 121 potential target genes were considered to be therapeutically relevant. Pathway analysis indicated that MAPK signaling pathway, ErbB signaling pathway, HIF-1 signaling pathway and PI3K-Akt pathway were significant pathways in depression. They were mainly involved in promoting nerve growth and nutrition and alleviating neuroinflammatory conditions. The result provided some potential ways for modern medicine in the treatment of depression.

Network Controllability-Based Prioritization of Candidates for SARS-CoV-2 Drug Repositioning

In a short time, the COVID-19 pandemic has left the world with over 25 million cases and staggering death tolls that are still rising. Treatments for SARS-CoV-2 infection are desperately needed as there are currently no approved drug therapies. With limited knowledge of viral mechanisms, a network controllability method of prioritizing existing drugs for repurposing efforts is optimal for quickly moving through the drug approval pipeline using limited, available, virus-specific data. Based on network topology and controllability, 16 proteins involved in translation, cellular transport, cellular stress, and host immune response are predicted as regulators of the SARS-CoV-2 infected cell. Of the 16, eight are prioritized as possible drug targets where two, PVR and SCARB1, are previously unexplored. Known compounds targeting these genes are suggested for viral inhibition study. Prioritized proteins in agreement with previous analysis and viral inhibition studies verify the ability of network controllability to predict biologically relevant candidates.