Proximity interactome analysis of Lassa polymerase reveals eRF3a/GSPT1 as a druggable target for host-directed antivirals.

Completion of the Lassa virus (LASV) life cycle critically depends on the activities of the virally encoded, RNA-dependent RNA polymerase in replication and transcription of the viral RNA genome in the cytoplasm of infected cells. The contribution of cellular proteins to these processes remains unclear. Here, we applied proximity proteomics to define the interactome of LASV polymerase in cells under conditions that recreate LASV RNA synthesis. We engineered a LASV polymerase-biotin ligase (TurboID) fusion protein that retained polymerase activity and successfully biotinylated the proximal proteome, which allowed the identification of 42 high-confidence LASV polymerase interactors. We subsequently performed a small interfering RNA (siRNA) screen to identify those interactors that have functional roles in authentic LASV infection. As proof of principle, we characterized eukaryotic peptide chain release factor subunit 3a (eRF3a/GSPT1), which we found to be a proviral factor that physically associates with LASV polymerase. Targeted degradation of GSPT1 by a small-molecule drug candidate, CC-90009, resulted in strong inhibition of LASV infection in cultured cells. Our work demonstrates the feasibility of using proximity proteomics to illuminate and characterize yet-to-be-defined host-pathogen interactome, which can reveal new biology and uncover novel targets for the development of antivirals against highly pathogenic RNA viruses.

Proximity Profiling of the CFTR Interaction Landscape in Response to Orkambi.

Deletion of phenylalanine 508 (∆F508) of the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) anion channel protein is the leading cause of Cystic Fibrosis (CF). Here, we report the analysis of CFTR and ∆F508-CFTR interactomes using BioID (proximity-dependent biotin identification), a technique that can also detect transient associations. We identified 474 high-confidence CFTR proximity-interactors, 57 of which have been previously validated, with the remainder representing novel interaction space. The ∆F508 interactome, comprising 626 proximity-interactors was markedly different from its wild type counterpart, with numerous alterations in protein associations categorized in membrane trafficking and cellular stress functions. Furthermore, analysis of the ∆F508 interactome in cells treated with Orkambi identified several interactions that were altered as a result of this drug therapy. We examined two candidate CFTR proximity interactors, VAPB and NOS1AP, in functional assays designed to assess surface delivery and overall chloride efflux. VAPB depletion impacted both CFTR surface delivery and chloride efflux, whereas NOS1AP depletion only affected the latter. The wild type and ∆F508-CFTR interactomes represent rich datasets that could be further mined to reveal additional candidates for the functional rescue of ∆F508-CFTR.

Mechanism of action of Tripterygium wilfordii for treatment of idiopathic membranous nephropathy based on network pharmacology.

BACKGROUND: Although thunder god vine (Tripterygium wilfordii) has been widely used for treatment of idiopathic membranous nephropathy (IMN), the pharmacological mechanisms underlying its effects are still unclear. This study investigated potential therapeutic targets and the pharmacological mechanism of T. wilfordii for the treatment of IMN based on network pharmacology. METHODS: Active components of T. wilfordii were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. IMN-associated target genes were collected from the GeneCards, DisGeNET, and OMIM databases. VENNY 2.1 was used to identify the overlapping genes between active compounds of T. wilfordii and IMN target genes. The STRING database and Cytoscape 3.7.2 software were used to analyze interactions among overlapping genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the targets were performed using Rx64 4.0.2 software, colorspace, stringi, DOSE, clusterProfiler, and enrichplot packages. RESULTS: A total of 153 compound-related genes and 1485 IMN-related genes were obtained, and 45 core genes that overlapped between both categories were identified. The protein-protein interaction network and MCODE results indicated that the targets TP53, MAPK8, MAPK14, STAT3, IFNG, ICAM1, IL4, TGFB1, PPARG, and MMP1 play important roles in the treatment of T. wilfordii on IMN. Enrichment analysis showed that the main pathways of targets were the AGE signaling pathway, IL-17 signaling pathway, TNF signaling pathway, and Toll-like receptor signaling pathway. CONCLUSION: This study revealed potential multi-component and multi-target mechanisms of T. wilfordii for the treatment of IMN based on network pharmacological, and provided a scientific basis for further experimental studies.

Challenges in Discovering Drugs That Target the Protein-Protein Interactions of Disordered Proteins.

Protein-protein interactions (PPIs) outnumber proteins and are crucial to many fundamental processes; in consequence, PPIs are associated with several pathological conditions including neurodegeneration and modulating them by drugs constitutes a potentially major class of therapy. Classically, however, the discovery of small molecules for use as drugs entails targeting individual proteins rather than targeting PPIs. This is largely because discovering small molecules to modulate PPIs has been seen as extremely challenging. Here, we review the difficulties and limitations of strategies to discover drugs that target PPIs directly or indirectly, taking as examples the disordered proteins involved in neurodegenerative diseases.

In vitro anti-synovial sarcoma effect of diallyl trisulfide and mRNA profiling.

OBJECTIVE: Synovial sarcoma (SS) is a malignant soft tissue sarcoma and its natural history is a long, indolent clinical course followed by high rate of local recurrence and distant metastasis. Current therapies are still limited in increasing satisfactory of 5-year survival, especially for patients with recurrence and metastasis. Accordingly, finding new therapeutic drug for SS treatment is clinically urgent need. Diallyl trisulfide (DATS), a bioactive compound derived from garlic, is reported as a promising anti-cancer agent for various carcinomas. However, its effect on anti-SS remains unknown. This study investigated the anti-SS effect of DATS in human synovial sarcoma SW982 cells. METHODS: CCK-8 assay were used to examine the cell viability. High-content Imaging System was used to examine the apoptosis, intracellular ROS and autophagy. Flow cytometry was used to detect cell cycle. qPCR and Western blot were used to examine the expression of related mRNA and protein. High-throughput RNA-sequencing and bio-information analysis were used to investigate the mRNA profiling. RESULTS: The results showed a suppressive effect of DATS on tumor biology of SW982 cells including inducing apoptosis, triggering G2/M cell cycle arrest, elevating intracellular ROS and damaging mitochondria. Further high-throughput RNA-sequencing analysis clarified a comprehensive molecular portrait for DATS-induced transcriptional regulation. Besides, protein-protein interaction (PPI) analysis demonstrated that a network consisted of FOXM1, CCNA2, CCNB1, MYBL2, PLK1 and CDK1 might be response for DATS-induced G2/M cell cycle arrest and increased intracellular ROS. Notably, protein feature analysis revealed structure enrichment in microtubule network like kinesin motors domain, and tubulin domain. Molecular function analysis suggested that DATS-induced dysfunction of microtubule network might be the major cause for its effect on cell cycle arrest and successive apoptosis. Furthermore, 28 hub genes (including KIF2C, PLK1, CDK1, BIRC5, CCNB2, CENPF, TPX2, TOP2A and so on) were determined. Finally, pathway analysis showed that DATS-induced differentially expressed genes were mainly involved in cell cycle. CONCLUSION: Collectively, our findings for the first time provided the DATS-induced cellular response and transcriptional profiling of SW982 cells, which proposes that suppression of DATS on SS is multi-targeted and represent a therapeutic evidence for SS.

Network controllability solutions for computational drug repurposing using genetic algorithms.

Control theory has seen recently impactful applications in network science, especially in connections with applications in network medicine. A key topic of research is that of finding minimal external interventions that offer control over the dynamics of a given network, a problem known as network controllability. We propose in this article a new solution for this problem based on genetic algorithms. We tailor our solution for applications in computational drug repurposing, seeking to maximize its use of FDA-approved drug targets in a given disease-specific protein-protein interaction network. We demonstrate our algorithm on several cancer networks and on several random networks with their edges distributed according to the Erdos-Rényi, the Scale-Free, and the Small World properties. Overall, we show that our new algorithm is more efficient in identifying relevant drug targets in a disease network, advancing the computational solutions needed for new therapeutic and drug repurposing approaches.

Reveals of quercetin's therapeutic effects on oral lichen planus based on network pharmacology approach and experimental validation.

Oral lichen planus (OLP) is a localized autoimmune disease of the oral mucosa, with an incidence of up to 2%. Although corticosteroids are the first-line treatment, they cause several adverse effects. Quercetin, a naturally occurring compound, has fewer side-effects and provides long-term benefits. Besides, it has powerful anti­inflammatory activities. Here, we combined network pharmacology with experimental verification to predict and verify the key targets of quercetin against OLP. First, 66 quercetin-OLP common targets were analyzed from various databases. The protein-protein interaction (PPI) network was constructed. Topology analysis and MCODE cluster analysis of common targets were conducted to identify 12 key targets including TP53, IL-6 and IFN-γ and their connections. Gene functions and key signaling pathways, including reactive oxygen species metabolism, IL-17 pathway and AGE-RAGE pathway, were enriched by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Then, in vitro experiments showed that quercetin interfered with Th1/Th2 balance by acting on IL-6 and IFN-γ to modulate the immune system in treating OLP. Quercetin considerably affected the apoptosis and migration of T lymphocytes in OLP patients. Our study reveals the potential therapeutic targets and signaling pathways of quercetin associated with OLP, and establishes the groundwork for future clinical applications.

Utilizing network pharmacology and experimental validation to explore the potential molecular mechanisms of BanXia-YiYiRen in treating insomnia.

BanXia-YiYiRen (Pinellia Ternata and Coix Seed, BX-YYR) has been clinically proven to be an effective Chinese medicine compatible with the treatment of insomnia. However, the underlying mechanism of BX-YYR against insomnia remains unclear. This study aimed to explore the pharmacological mechanisms of BX-YYR in treating insomnia based on network pharmacology and experimental validation. The drug-disease targets were obtained using publicly available databases. The analysis revealed 21 active compounds and 101 potential targets of BX-YYR from the pharmacological database of Chinese medicine system and analysis platform (TCMSP) and 1020 related targets of insomnia from the GeneCards and Online Mendelian Inheritance in Man (OMIM) databases. Furthermore, 38 common targets of BX-YYR against insomnia were identified, and these common targets were used to construct a protein-protein interaction (PPI) network. The visual PPI network was constructed by Cytoscape software. The top three genes from PPI according to degree value are FOS, AKT1, and CASP3. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were applied to reveal the potential targets and signaling pathways involved in BX-YYR against insomnia, especially the serotonergic pathway. In addition, molecular docking revealed that baicalein, beta-sitosterol, and stigmasterol displayed strong binding to AKT1, FOS, PRKCA, and VEGFA. Experimental study found that BX-YYR against insomnia might play a role in improving sleep by modulating the serotonergic pathway. In summary, our findings revealed the underlying mechanism of BX-YYR against insomnia and provided an objective basis for further experimental study and clinical application.

Network Pharmacology Prediction: The Possible Mechanisms of Cinobufotalin against Osteosarcoma.

OBJECTIVE: To explore the active compounds and targets of cinobufotalin (huachansu) compared with the osteosarcoma genes to obtain the potential therapeutic targets and pharmacological mechanisms of action of cinobufotalin on osteosarcoma through network pharmacology. METHODS: The composition of cinobufotalin was searched by literature retrieval, and the target was selected from the CTD and TCMSP databases. The osteosarcoma genes, found from the GeneCards, OMIM, and other databases, were compared with the cinobufotalin targets to obtain potential therapeutic targets. The protein-protein interaction (PPI) network of potential therapeutic targets, constructed through the STRING database, was inputted into Cytoscape software to calculate the hub genes, using the NetworkAnalyzer. The hub genes were inputted into the Kaplan-Meier Plotter online database for exploring the survival curve. Functional enrichment analysis was identified using the DAVID database. RESULTS: 28 main active compounds of cinobufotalin were explored, including bufalin, adenosine, oleic acid, and cinobufagin. 128 potential therapeutic targets on osteosarcoma are confirmed among 184 therapeutic targets form cinobufotalin. The hub genes included TP53, ACTB, AKT1, MYC, CASP3, JUN, TNF, VEGFA, HSP90AA1, and STAT3. Among the hub genes, TP53, ACTB, MYC, TNF, VEGFA, and STAT3 affect the patient survival prognosis of sarcoma. Through function enrichment analysis, it is found that the main mechanisms of cinobufotalin on osteosarcoma include promoting sarcoma apoptosis, regulating the cell cycle, and inhibiting proliferation and differentiation. CONCLUSION: The possible mechanisms of cinobufotalin against osteosarcoma are preliminarily predicted through network pharmacology, and further experiments are needed to prove these predictions.

Interrelationship between 2019-nCov receptor DPP4 and diabetes mellitus targets based on protein interaction network.

Patients with diabetes are more likely to be infected with Coronavirus disease 2019 (COVID-19), and the risk of death is significantly higher than ordinary patients. Dipeptidyl peptidase-4 (DPP4) is one of the functional receptor of human coronavirus. Exploring the relationship between diabetes mellitus targets and DPP4 is particularly important for the management of patients with diabetes and COVID-19. We intend to study the protein interaction through the protein interaction network in order to find a new clue for the management of patients with diabetes with COVID-19. Diabetes mellitus targets were obtained from GeneCards database. Targets with a relevance score exceeding 20 were included, and DPP4 protein was added manually. The initial protein interaction network was obtained through String. The targets directly related to DPP4 were selected as the final analysis targets. Importing them into String again to obtain the protein interaction network. Module identification, gene ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were carried out respectively. The impact of DPP4 on the whole network was analyzed by scoring the module where it located. 43 DPP4-related proteins were finally selected from the diabetes mellitus targets and three functional modules were found by the cluster analysis. Module 1 was involved in insulin secretion and glucagon signaling pathway, module 2 and module 3 were involved in signaling receptor binding. The scoring results showed that LEP and apoB in module 1 were the highest, and the scores of INS, IL6 and ALB of cross module associated proteins of module 1 were the highest. DPP4 is widely associated with key proteins in diabetes mellitus. COVID-19 may affect DPP4 in patients with diabetes mellitus, leading to high mortality of diabetes mellitus combined with COVID-19. DPP4 inhibitors and IL-6 antagonists can be considered to reduce the effect of COVID-19 infection on patients with diabetes.

Inhibition of ACE2-Spike Interaction by an ACE2 Binder Suppresses SARS-CoV-2 Entry.

The emergence of SARS-CoV-2 variants is a significant concern in developing effective therapeutics and vaccines in the middle of the ongoing COVID-19 pandemic. Here, we have identified a novel small molecule that inhibited the interactions between SARS-CoV-2 spike RBDs and ACE2 by modulating ACE2 without impairing its enzymatic activity necessary for normal physiological functions. Furthermore, the identified compounds suppressed viral infection in cultured cells by inhibiting the entry of ancestral and variant SARS-CoV-2. Our study suggests that targeting ACE2 could be a novel therapeutic strategy to inhibit SARS-CoV-2 entry into host cells and prevent the development of COVID-19.

Identification of hub genes associated with COVID-19 and idiopathic pulmonary fibrosis by integrated bioinformatics analysis.

INTRODUCTION: The coronavirus disease 2019 (COVID-19), emerged in late 2019, was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The risk factors for idiopathic pulmonary fibrosis (IPF) and COVID-19 are reported to be common. This study aimed to determine the potential role of differentially expressed genes (DEGs) common in IPF and COVID-19. MATERIALS AND METHODS: Based on GEO database, we obtained DEGs from one SARS-CoV-2 dataset and five IPF datasets. A series of enrichment analysis were performed to identify the function of upregulated and downregulated DEGs, respectively. Two plugins in Cytoscape, Cytohubba and MCODE, were utilized to identify hub genes after a protein-protein interaction (PPI) network. Finally, candidate drugs were predicted to target the upregulated DEGs. RESULTS: A total of 188 DEGs were found between COVID-19 and IPF, out of which 117 were upregulated and 71 were downregulated. The upregulated DEGs were involved in cytokine function, while downregulated DEGs were associated with extracellular matrix disassembly. Twenty-two hub genes were upregulated in COVID-19 and IPF, for which 155 candidate drugs were predicted (adj.P.value < 0.01). CONCLUSION: Identifying the hub genes aberrantly regulated in both COVID-19 and IPF may enable development of molecules, encoded by those genes, as therapeutic targets for preventing IPF progression and SARS-CoV-2 infections.

Nrf2/Keap1/ARE signaling: Towards specific regulation.

The Nrf2 transcription factor governs the expression of hundreds genes involved in cell defense against oxidative stress, the hallmark of numerous diseases such as neurodegenerative, cardiovascular, some viral pathologies, diabetes and others. The main route for Nrf2 activity regulation is via interactions with the Keap1 protein. Under the normoxia the Keap1 binds the Nrf2 and targets it to the proteasomal degradation, while the Keap1 is regenerated. Upon oxidative stress the interactions between Nrf2 and Keap1 are interrupted and the Nrf2 activates the transcription of the protective genes. Currently, the Nrf2 system activation is considered as a powerful cytoprotective strategy for treatment of different pathologies, which pathogenesis relies on oxidative stress including viral diseases of pivotal importance such as COVID-19. The implementation of this strategy is accomplished mainly through the inactivation of the Keap1 "guardian" function. Two approaches are now developing: the Keap1 modification via electrophilic agents, which leads to the Nrf2 release, and direct interruption of the Nrf2:Keap1 protein-protein interactions (PPI). Because of theirs chemical structure, the Nrf2 electrophilic inducers could non-specifically interact with others cellular proteins leading to undesired effects. Whereas the non-electrophilic inhibitors of the Nrf2:Keap1 PPI could be more specific, thereby widening the therapeutic window.

The possible mechanism of Hippophae fructus oil applied in tympanic membrane repair identified based on network pharmacology and molecular docking.

OBJECTIVE: This study aimed to explore the mechanisms of Hippophae fructus oil (HFO) in the treatment of tympanic membrane (TM) perforation through network pharmacology-based identification. METHODS: The compounds and related targets of HFO were extracted from the TCMSP database, and disease information was obtained from the OMIM, GeneCards, PharmGkb, TTD, and DrugBank databases. A Venn diagram was generated to show the common targets of HFO and TM, and GO and KEGG analyses were performed to explore the potential biological processes and signaling pathways. The PPI network and core gene subnetwork were constructed using the STRING database and Cytoscape software. A molecular docking analysis was also conducted to simulate the combination of compounds and gene proteins. RESULTS: A total of 33 compounds and their related targets were obtained from the TCMSP database. After screening the 393 TM-related targets, 21 compounds and 22 gene proteins were selected to establish the network diagram. GO and KEGG enrichment analyses revealed that HFO may promote TM healing by influencing cellular oxidative stress and related signaling pathways. A critical subnetwork was obtained by analyzing the PPI network with nine core genes: CASP3, MMP2, IL1B, TP53, EGFR, CXCL8, ESR1, PTGS2, and IL6. In addition, a molecular docking analysis revealed that quercetin strongly binds the core proteins. CONCLUSION: According to the analysis, HFO can be utilized to repair perforations by influencing cellular oxidative stress. Quercetin is one of the active compounds that potentially plays an important role in TM regeneration by influencing 17 gene proteins.

Phosphoproteomics analysis of diabetic cardiomyopathy in aging-accelerated mice and effects of D-pinitol.

PURPOSE: The molecular mechanisms of diabetic cardiomyopathy (DCM) development and D-pinitol (DP) in its treatment remain unclear. The present study is to explore the underlying mechanism of DCM in an elderly diabetic mouse model and to seek the protective targets of DP by phosphoproteomics. EXPERIMENTAL DESIGN: We used streptozotocin to induce diabetes in SAMP8 and DP (150 mg/kg/day) intragastrically administrated to diabetic mice for 8 weeks. The heart tissues were harvested for label-free phosphoproteomic analysis from diabetic mice. Some differentially regulated phosphorylation sites were confirmed by parallel reaction monitoring. RESULTS: Our results showed that 612 phosphorylation sites on 454 proteins had their phosphorylation levels significantly changed in the heart of untreated diabetic mice (DM). Of these phosphorylation sites, 216 phosphorylation sites on 182 proteins were normalized after DP treatment. We analyzed the functional signaling pathways in the heart of DP treated diabetic mice (DMT), including glucagon signaling pathway, insulin signaling pathway, mitophagy, apoptosis, and longevity regulating pathway. Two consensus motifs identified were targeted by Src and epidermal growth factor receptor between DMT and DM groups. CONCLUSIONS AND CLINICAL RELEVANCE: Our study might help to better understand the mechanism of DCM, provide novel targets for estimating the protective effects of DP.

Choline-induced SLC5A7 impairs colorectal cancer growth by stabilizing p53 protein.

The members of the solute carrier (SLC) superfamily are vital membrane transporters in human cells. In the present study, we determine the expression and function of SLC5 family members in colorectal cancer (CRC). Expression analysis based on The Cancer Genome Atlas database and potential clinical relation analysis based on the Oncomine database indicate that SLC5A7 is downregulated and is predicted to correlate with the staging, and prognosis response of CRC. Additional results demonstrate that SLC5A7 is downregulated and correlates with good prognosis in patients with CRC. Ectopic expression of SLC5A7 either by overexpression, or uptake of choline efficiently inhibits CRC growth. Examination of the molecular mechanism reveals that SLC5A7 promotes p53 protein expression by directly interacting with and modifying p53 and disrupting the interaction between p53 and MDM2 in wild type p53 CRC cells. Our findings establish the clear correlation between SLC5A7 and tumour growth, providing a novel potential therapeutic target for CRC.

Transcription factor network analysis based on single cell RNA-seq identifies that Trichostatin-a reverses docetaxel resistance in prostate Cancer.

BACKGROUND: Overcoming drug resistance is critical for increasing the survival rate of prostate cancer (PCa). Docetaxel is the first cytotoxic chemotherapeutical approved for treatment of PCa. However, 99% of PCa patients will develop resistance to docetaxel within 3 years. Understanding how resistance arises is important to increasing PCa survival. METHODS: In this study, we modeled docetaxel resistance using two PCa cell lines: DU145 and PC3. Using the Passing Attributes between Networks for Data Assimilation (PANDA) method to model transcription factor (TF) activity networks in both sensitive and resistant variants of the two cell lines. We identified edges and nodes shared by both PCa cell lines that composed a shared TF network that modeled changes which occur during acquisition of docetaxel resistance in PCa. We subjected the shared TF network to connectivity map analysis (CMAP) to identify potential drugs that could disrupt the resistant networks. We validated the candidate drug in combination with docetaxel to treat docetaxel-resistant PCa in both in vitro and in vivo models. RESULTS: In the final shared TF network, 10 TF nodes were identified as the main nodes for the development of docetaxel resistance. CMAP analysis of the shared TF network identified trichostatin A (TSA) as a candidate adjuvant to reverse docetaxel resistance. In cell lines, the addition of TSA to docetaxel enhanced cytotoxicity of docetaxel resistant PCa cells with an associated reduction of the IC50 of docetaxel on the resistant cells. In the PCa mouse model, combination of TSA and docetaxel reduced tumor growth and final weight greater than either drug alone or vehicle. CONCLUSIONS: We identified a shared TF activity network that drives docetaxel resistance in PCa. We also demonstrated a novel combination therapy to overcome this resistance. This study highlights the usage of novel application of single cell RNA-sequencing and subsequent network analyses that can reveal novel insights which have the potential to improve clinical outcomes.

The role of AKR1 family in tamoxifen resistant invasive lobular breast cancer based on data mining.

BACKGROUND: Tamoxifen (TAM) resistance to invasive lobular cell carcinoma is a challenge for breast cancer treatment. This study explored the role of Aldo-keto reductase family 1 (AKR1) family in tamoxifen-resistant aggressive lobular breast cancer based on data mining. METHODS: TAM-resistant invasive lobular breast cancer gene chip was downloaded from the Gene Expression Omnibus (GEO) database (accession-numbered as GSE96670). The online analytical tool GEO2R was used to screen for differentially expressed genes in TAM-resistant invasive lobular breast cancer cells and TAM-sensitive counterparts. A protein-protein interaction (PPI) networks were constructed using the STRING online platform and the Cytoscape software. GeneMANIA and GSCALite online tools were used to reveal the potential role of these hub genes in breast cancer progression and TAM resistance development. And the used the GSE67916 microarray data set to verify the differentially expression of these hub genes in breast cancer. The protein expression levels of AKR1C1, AKR1C2 and AKR1C3 in TAM-sensitive and resistant breast cancer cells were compared. The TAM sensitivity of breast cancer cells with or without AKR1C1, AKR1C2 or AKR1C3 gene manipulation was evaluated by cell viability assay. RESULTS: A total of 184 differentially expressed genes were screened. Compared with TAM sensitive breast cancer cells, 162 were up-regulated and 22 were down-regulated. The study identified several hub genes in the PPI network that may be involved in the development of TAM resistance of breast cancer, including signal transducer and activator of transcription 1 (STAT1), estrogen receptor alpha (ESR1), fibronectin1 (FN1), cytochrome P4501B1 (CYP1B1), AKR1C1, AKR1C2, AKR1C3 and uridine diphosphate glucuronosyltransferase (UGT) 1A family genes (UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A7, UGT1A8, UGT1A9, UGT1A10). Compared with TAM-sensitive counterparts, the expression levels of AKR1C1, AKR1C2, and AKR1C3 were up-regulated in TAM-resistant breast cancer cells. CONCLUSIONS: Overexpression of each of these three genes significantly increased the resistance of breast cancer cells to TAM treatment, while their knockdown showed opposite effects, indicating that they are potential therapeutic target for the treatment of TAM-resistant breast cancer.

Elucidating the Mechanism of Action of Salvia miltiorrhiza for the Treatment of Acute Pancreatitis Based on Network Pharmacology and Molecular Docking Technology.

Using network pharmacology and molecular docking, this study investigated the molecular mechanisms by which the active components in Salvia miltiorrhiza can alleviate acute pancreatitis. Initially, the active components of Salvia miltiorrhiza and the targets collected from the GeneCards database were screened based on the platform of systematic pharmacology analysis of traditional Chinese medicine. Subsequently, the active components were intersected with the disease targets. Also, interactions among the targets were computed using the STRING database. Biological function and pathway enrichment were analyzed using the Cluster Profiler package in the R software. Protein-protein interaction and component target pathway network were constructed using the Cytoscape software. Ultimately, the key targets and their corresponding components in the network were verified using the AutoDock Vina software. The results showed Salvia miltiorrhiza had 111 targets for acute pancreatitis. The biological process (BP) analysis showed that the active components of Salvia miltiorrhiza induced a drug response, positive regulation of transcription by RNA polymerase II promoter, signal transduction, positive regulation of cell proliferation, and negative regulation of apoptosis. Furthermore, the KEGG enrichment analysis screened 118 (P < 0.05) signaling pathways, such as the pathways related to cancer, neuroactive ligand-receptor interaction, PI3K-Akt signaling pathway, and cAMP signaling pathway, to name a few. Finally, molecular docking showed that the active components of Salvia miltiorrhiza had a good binding affinity with their corresponding target proteins. Through network pharmacology, this study predicted the potential pharmacodynamic material basis and the mechanisms by which Salvia miltiorrhiza can treat acute pancreatitis. Moreover, this study provided a scientific basis for mining the pharmacodynamic components of Salvia miltiorrhiza and expanding the scope of its clinical use.

Research on the Mechanism of Guizhi to Treat Nephrotic Syndrome Based on Network Pharmacology and Molecular Docking Technology.

OBJECTIVE: Nephrotic syndrome (NS) is a common glomerular disease caused by a variety of causes and is the second most common kidney disease. Guizhi is the key drug of Wulingsan in the treatment of NS. However, the action mechanism remains unclear. In this study, network pharmacology and molecular docking were used to explore the underlying molecular mechanism of Guizhi in treating NS. METHODS: The active components and targets of Guizhi were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Hitpick, SEA, and Swiss Target Prediction database. The targets related to NS were obtained from the DisGeNET, GeneCards, and OMIM database, and the intersected targets were obtained by Venny2.1.0. Then, active component-target network was constructed using Cytoscape software. And the protein-protein interaction (PPI) network was drawn through the String database and Cytoscape software. Next, Gene Ontology (GO) and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by DAVID database. And overall network was constructed through Cytoscape. Finally, molecular docking was conducted using Autodock Vina. RESULTS: According to the screening criteria, a total of 8 active compounds and 317 potential targets of Guizhi were chosen. Through the online database, 2125 NS-related targets were identified, and 93 overlapping targets were obtained. In active component-target network, beta-sitosterol, sitosterol, cinnamaldehyde, and peroxyergosterol were the important active components. In PPI network, VEGFA, MAPK3, SRC, PTGS2, and MAPK8 were the core targets. GO and KEGG analyses showed that the main pathways of Guizhi in treating NS involved VEGF, Toll-like receptor, and MAPK signaling pathway. In molecular docking, the active compounds of Guizhi had good affinity with the core targets. CONCLUSIONS: In this study, we preliminarily predicted the main active components, targets, and signaling pathways of Guizhi to treat NS, which could provide new ideas for further research on the protective mechanism and clinical application of Guizhi against NS.