scholarly journals Phosphorylation-Mediated Molecular Pathway Changes in Human Pituitary Neuroendocrine Tumors Identified by Quantitative Phosphoproteomics

Cells ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 2225
Author(s):  
Jiajia Li ◽  
Siqi Wen ◽  
Biao Li ◽  
Na Li ◽  
Xianquan Zhan
Keyword(s):  
Protein Phosphorylation ◽  
Neuroendocrine Tumors ◽  
Drug Targets ◽  
Smooth Muscle Contraction ◽  
Bacterial Invasion ◽  
Transport Pathway ◽  
Human Pituitary ◽  
Pathway Network ◽  
Precious Resource ◽  
Cellular Components

To investigate the biological role of protein phosphorylation in human nonfunctional pituitary neuroendocrine tumors (NF-PitNETs), proteins extracted from NF-PitNET and control tissues were analyzed with tandem mass tag (TMT)-based quantitative proteomics coupled with TiO2 enrichment of phosphopeptides. A total of 595 differentially phosphorylated proteins (DPPs) with 1412 phosphosites were identified in NF-PitNETs compared to controls (p < 0.05). KEGG pathway network analysis of 595 DPPs identified nine statistically significant signaling pathways, including the spliceosome pathway, the RNA transport pathway, proteoglycans in cancer, SNARE interactions in vesicular transport, platelet activation, bacterial invasion of epithelial cells, tight junctions, vascular smooth muscle contraction, and protein processing in the endoplasmic reticulum. GO analysis revealed that these DPPs were involved in multiple cellular components (CCs), biological processes (BPs), and molecule functions (MFs). The kinase analysis of 595 DPPs identified seven kinases, including GRP78, WSTF, PKN2, PRP4, LOK, NEK1, and AMPKA1, and the substrate of these kinases could provide new ideas for seeking drug targets for NF-PitNETs. The randomly selected DPP calnexin was further confirmed with immunoprecipitation (IP) and Western blot (WB). These findings provide the first DPP profiling, phosphorylation-mediated molecular network alterations, and the key kinase profiling in NF-PitNET pathogenesis, which are a precious resource for understanding the biological roles of protein phosphorylation in NF-PitNET pathogenesis and discovering effective phosphoprotein biomarkers and therapeutic targets and drugs for the management of NF-PitNETs.

Pathogenic Genes Selection Model of Genetic Disease based on Network Motifs Slicing Feedback

2019 ◽  
Vol 16 (5) ◽  
pp. 392-401
Author(s):  
Shengli Zhang ◽  
Zekun Tong ◽  
Haoyu Yin ◽  
Yifan Feng
Keyword(s):  
Genetic Disease ◽  
Drug Targets ◽  
Selection Model ◽  
Network Motifs ◽  
Gene Set ◽  
Pathway Network ◽  
Gene Pathway ◽  
Pathogenic Genes ◽  
Pathogenic Gene ◽  
Selection Of

Background: Finding the pathogenic gene is very important for understanding the pathogenesis of the disease, locating effective drug targets and improving the clinical level of medical treatment. However, the existing methods for finding the pathogenic genes still have limitations, for instance the computational complexity is high, and the combination of multiple genes and pathways has not been considered to search for highly related pathogenic genes and so on. Methods: We propose a pathogenic genes selection model of genetic disease based on Network Motifs Slicing Feedback (NMSF). We find a point set which makes the conductivity of the motif minimum then use it to substitute for the original gene pathway network. Based on the NMSF, we propose a new pathogenic genes selection model to expand pathogenic gene set. Results: According to the gene set we have obtained, selection of key genes will be more accurate and convincing. Finally, we use our model to screen the pathogenic genes and key pathways of liver cancer and lung cancer, and compare the results with the existing methods. Conclusion: The main contribution is to provide a method called NMSF which simplifies the gene pathway network to make the selection of pathogenic gene simple and feasible. The fact shows our result has a wide coverage and high accuracy and our model has good expeditiousness and robustness.

Profiling of 1,350 neuroendocrine tumors for identification of multiple potential drug targets.

2014 ◽  
Vol 32 (15_suppl) ◽  
pp. 4113-4113 ◽  
Author(s):  
Igor A. Astsaturov ◽  
Steven J. Cohen ◽  
Paul F. Engstrom ◽  
Sherri Z. Millis
Keyword(s):  
Neuroendocrine Tumors ◽  
Drug Targets ◽  
Potential Drug ◽  
Potential Drug Targets

scholarly journals Compound Functional Prediction Using Multiple Unrelated Morphological Profiling Assays

2017 ◽  
Vol 23 (3) ◽  
pp. 243-251 ◽  
Author(s):  
France Rose ◽  
Sreetama Basu ◽  
Elton Rexhepaj ◽  
Anne Chauchereau ◽  
Elaine Del Nery ◽  
...  
Keyword(s):  
Drug Target ◽  
Drug Targets ◽  
Fluorescent Dyes ◽  
Wide Spectrum ◽  
Ensemble Classifier ◽  
Functional Prediction ◽  
Unknown Compound ◽  
Therapeutic Drugs ◽  
Highly Correlated ◽  
Cellular Components

Phenotypic cell–based assays have proven to be efficient at discovering first-in-class therapeutic drugs mainly because they allow for scanning a wide spectrum of possible targets at once. However, despite compelling methodological advances, posterior identification of a compound’s mechanism of action (MOA) has remained difficult and highly refractory to automated analyses. Methods such as the cell painting assay and multiplexing fluorescent dyes to reveal broadly relevant cellular components were recently suggested for MOA prediction. We demonstrated that adding fluorescent dyes to a single assay has limited impact on MOA prediction accuracy, as monitoring only the nuclei stain could reach compelling levels of accuracy. This observation suggested that multiplexed measurements are highly correlated and nuclei stain could possibly reflect the general state of the cell. We then hypothesized that combining unrelated and possibly simple cell-based assays could bring a solution that would be biologically and technically more relevant to predict a drug target than using a single assay multiplexing dyes. We show that such a combination of past screen data could rationally be reused in screening facilities to train an ensemble classifier to predict drug targets and prioritize a possibly large list of unknown compound hits at once.

scholarly journals Disrupting Gram-Negative Bacterial Outer Membrane Biosynthesis through Inhibition of the Lipopolysaccharide Transporter MsbA

2018 ◽  
Vol 62 (11) ◽  
Author(s):  
Mary Kate Alexander ◽  
Anh Miu ◽  
Angela Oh ◽  
Mike Reichelt ◽  
Hoangdung Ho ◽  
...  
Keyword(s):  
Outer Membrane ◽  
Drug Targets ◽  
Multidrug Resistant ◽  
Gram Negative Bacteria ◽  
Transport Pathway ◽  
Gram Negative ◽  
Content Type ◽  
Outer Leaflet ◽  
New Antibiotics ◽  
Outer Membrane Biogenesis

ABSTRACTThere is a critical need for new antibacterial strategies to counter the growing problem of antibiotic resistance. In Gram-negative bacteria, the outer membrane (OM) provides a protective barrier against antibiotics and other environmental insults. The outer leaflet of the outer membrane is primarily composed of lipopolysaccharide (LPS). Outer membrane biogenesis presents many potentially compelling drug targets as this pathway is absent in higher eukaryotes. Most proteins involved in LPS biosynthesis and transport are essential; however, few compounds have been identified that inhibit these proteins. The inner membrane ABC transporter MsbA carries out the first essential step in the trafficking of LPS to the outer membrane. We conducted a biochemical screen for inhibitors of MsbA and identified a series of quinoline compounds that killEscherichia colithrough inhibition of its ATPase and transport activity, with no loss of activity against clinical multidrug-resistant strains. Identification of these selective inhibitors indicates that MsbA is a viable target for new antibiotics, and the compounds we identified serve as useful tools to further probe the LPS transport pathway in Gram-negative bacteria.

scholarly journals Network Pharmacology-based Elucidation of Molecular Biological Mechanisms of Kanglaite Injection for Treatment of Pancreatic Ductal Adenocarcinoma

2020 ◽  
Author(s):  
Bowen Xu ◽  
Wenchao Dan ◽  
Jie Lj ◽  
Xiaoxiao Zhang ◽  
Luchang Cao ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Drug Targets ◽  
Differentially Expressed ◽  
Ductal Adenocarcinoma ◽  
Network Pharmacology ◽  
Biological Mechanisms ◽  
Pathway Network ◽  
Gene Pathway

Abstract Background: Kanglaite injection (KLTi) has shown good clinical efficacy in the treatment of pancreatic ductal adenocarcinoma (PDAC). However, its molecular biological mechanisms are still unclear. This study used network pharmacology approach to investigate the molecular biological mechanisms of KLTi.Methods: Compounds in KLTi were screened using TCMSP and drug targets were obtained from the DRUGBANK. Next, the GEO database was searched for differentially expressed genes in cancerous tissues and healthy tissues of PDAC patients to identify targets. Subsequently, the protein-protein interaction data of KLTi and PDAC targets were constructed by BisoGenet. A visual analysis was done to extract KLTi candidate genes for PDAC. The candidate genes were enriched using GO and KEGG by Metascape, and the gene-pathway network was constructed to further screen the key genes.Results: A total of 10 active compounds and 36 drug targets were screened for KLTi, 919 differentially expressed genes associated with PDAC were identified from GEO, and 139 KLTi candidate genes against PDAC were excavated by BisoGenet. The gene-pathway network showed RELA, NFKB1, IKBKG, JUN, MAPK1, TP53, and AKT1 as the core genes, predicting that KLTi intervenes in PDAC by acting on these genes.Conclusions: Our study suggested that KLTi plays an anti-PDAC role by intervening in the cell cycle, inducing apoptosis, regulating protein binding, inhibiting nerve invasion, and down-regulating the NF-κB, MAPK, and PI3K-Akt signaling pathways. In addition, it might also directly participate in the pancreatic cancer pathway. These results provide new evidence and therapeutic direction for subsequent clinical applications and basic research on KLTi in PDAC.

scholarly journals PvP01-DB: computational structural and functional characterization of soluble proteome of PvP01 strain of Plasmodium vivax

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Ankita Singh ◽  
Rahul Kaushik ◽  
Dheeraj Kumar Chaurasia ◽  
Manpreet Singh ◽  
B Jayaram
Keyword(s):  
Plasmodium Vivax ◽  
Drug Targets ◽  
Active Sites ◽  
Functional Characterization ◽  
Complete Information ◽  
Drug Candidates ◽  
Web Resource ◽  
Quantum Leap ◽  
Public Resources ◽  
Cellular Components

Abstract Despite Plasmodium vivax being the main offender in the majority of malarial infections, very little information is available about its adaptation and development in humans. Its capability for activating relapsing infections through its dormant liver stage and resistance to antimalarial drugs makes it as one of the major challenges in eradicating malaria. Noting the immediate necessity for the availability of a comprehensive and reliable structural and functional repository for P. vivax proteome, here we developed a web resource for the new reference genome, PvP01, furnishing information on sequence, structure, functions, active sites and metabolic pathways compiled and predicted using some of the state-of-the-art methods in respective fields. The PvP01 web resource comprises organized data on the soluble proteome consisting of 3664 proteins in blood and liver stages of malarial cycle. The current public resources represent only 163 proteins of soluble proteome of PvP01, with complete information about their molecular function, biological process and cellular components. Also, only 46 proteins of P. vivax have experimentally determined structures. In this milieu of extreme scarcity of structural and functional information, PvP01 web resource offers meticulously validated structures of 3664 soluble proteins. The sequence and structure-based functional characterization led to a quantum leap from 163 proteins available presently to whole soluble proteome offered through PvP01 web resource. We believe PvP01 web resource will serve the researchers in identifying novel protein drug targets and in accelerating the development of structure-based new drug candidates to combat malaria. Database Availability: http://www.scfbio-iitd.res.in/PvP01

Src and PI3 K inhibitors affect the virulence factors ofEntamoeba histolytica

Parasitology ◽  
2012 ◽  
Vol 140 (2) ◽  
pp. 202-209 ◽  
Author(s):  
L. LÓPEZ-CONTRERAS ◽  
V. I. HERNÁNDEZ-RAMÍREZ ◽  
Y. FLORES-GARCÍA ◽  
B. CHÁVEZ-MUNGUÍA ◽  
P. TALAMÁS-ROHANA
Keyword(s):  
Actin Cytoskeleton ◽  
Protein Phosphorylation ◽  
Protein Kinases ◽  
Proteolytic Activity ◽  
Entamoeba Histolytica ◽  
Virulence Factors ◽  
Drug Targets ◽  
Phagocytic Capacity ◽  
Src Inhibitor

SUMMARYProtein kinases (PKs) of parasitic protozoa are being evaluated as drug targets. A large number of protein kinases within the protein kinome ofEntamoeba histolyticastrongly suggest that protein phosphorylation is a key component of pathogenesis regulation by this parasite. PI3 K and Src are kinases previously described in this parasite, but their role is poorly understood. Here, the effect of Src-1-inhibitor and PI3 K inhibitor (Wortmannin) on the virulence factors ofE. histolyticawas evaluated. Results show that both inhibitors affect the actin cytoskeleton and the amoebic movement. Also, the proteolytic activity is diminished by Wortmannin, but not by Src-inhibitor-1; however, the phagocytic capacity is diminished by Wortmannin and Src-1-inhibitor. Finally, we found that the virulencein vivoofE. histolyticais affected by Wortmannin but not by Src-1-inhibitor. This study opens the way for the design of anti-amoebic drugs based on kinase inhibition.

Inflammation and metabolic dysfunction: links to cardiovascular diseases

2012 ◽  
Vol 302 (11) ◽  
pp. H2148-H2165 ◽  
Author(s):  
Annika Taube ◽  
Raphaela Schlich ◽  
Henrike Sell ◽  
Kristin Eckardt ◽  
Juergen Eckel
Keyword(s):  
Cardiovascular Disease ◽  
Adipose Tissue ◽  
Drug Targets ◽  
Pigment Epithelium ◽  
Phenotypic Change ◽  
Metabolic Dysfunction ◽  
Lipocalin 2 ◽  
Fatty Acid Binding ◽  
Cellular Components

Abdominal obesity is a major risk factor for cardiovascular disease, and recent studies highlight a key role of adipose tissue dysfunction, inflammation, and aberrant adipokine release in this process. An increased demand for lipid storage results in both hyperplasia and hypertrophy, finally leading to chronic inflammation, hypoxia, and a phenotypic change of the cellular components of adipose tissue, collectively leading to a substantially altered secretory output of adipose tissue. In this review we have assessed the adipo-vascular axis, and an overview of adipokines associated with cardiovascular disease is provided. This resulted in a first list of more than 30 adipokines. A deeper analysis only considered adipokines that have been reported to impact on inflammation and NF-κB activation in the vasculature. Out of these, the most prominent link to cardiovascular disease was found for leptin, TNF-α, adipocyte fatty acid-binding protein, interleukins, and several novel adipokines such as lipocalin-2 and pigment epithelium-derived factor. Future work will need to address the potential role of these molecules as biomarkers and/or drug targets.

scholarly journals A network pharmacology approach to explore and validate the potential targets underlying the effect of Ginsenoside on Osteoporosis

2021 ◽  
Author(s):  
Qingliu Zhen ◽  
Ling Guo ◽  
Xiaoyue Zhen ◽  
Zhaoyang Cui ◽  
Chao Jiang ◽  
...  
Keyword(s):  
Network Analysis ◽  
Signaling Pathways ◽  
Protein Interaction ◽  
Drug Targets ◽  
Target Gene ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Target Proteins ◽  
Cellular Components

Abstract Objective This study aim to investigate the potential targets involving the effect of ginsenoside on osteoporosis using a network pharmacology approach. Methods Ginsenoside and its drug targets associated to osteoporosis (OP) were identified by using network analysis. First, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), DrugBank database, Pharmmapper database and Cytoscape software were used to mine information relevant to Ginsenoside ingredients and Ginsenoside -related targets. Second, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of ginsenoside-target gene and ginsenoside-OP target gene were performed in String, Phenopedia, DisGeNET database and Metascape software. Eventually, the protein to protein interaction (PPI) of key ginsenoside-OP targets were created by String database and Cytoscape software. The validation of the binding of ginsenoside to target proteins was plotted by utilizing SwissDock tool, UCSF Chimera and Pymol software. Results A total of 8 important active ingredients of ginsenosides were obtained in the TCMSP. Eighty potential targets of ginsenoside and 1304 related targets involved in OP were subjected to network analysis, and the 17 intersection targets were indicated to be linked to ginsenoside treating OP. GO and KEGG analysis showed the top 10 items of biological processes, cellular components, molecular functions and signaling pathways in the 80 targets of ginsenoside. Then, 14 key targets were determined to be the most crucial genes by protein to protein interaction (PPI) analysis. In the 14 intersection potential targets, 10 signaling pathways were defined by Metascape software. Validation plots of four target proteins IL1B, TNF, IFNG, NFKBIA binding to ginsenoside rh2 was drew, lastly. Conclusion This study investigated the potential targets and signaling pathways of ginsenoside during the treatment of OP, which might be beneficial to elucidate the mechanism concerned to the action of ginsenoside and might supply a better understanding of its anti-OP effects.

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