The molecular mechanisms associated with PIN7, a protein-protein interaction network of seven pleiotropic proteins

Molecular Mechanisms ◽

Interaction Network ◽

P53 Signaling ◽

Age Related ◽

P53 Signaling Pathway ◽

The protein-protein interaction network of seven pleiotropic proteins (PIN7) contains proteins with multiple functions in the aging and age-related diseases (TPPII, CDK2, MYBBP1A, p53, SIRT6, SIRT7, and BSG). At the present work, the pathway enrichment, the gene function prediction and the protein node prioritization analysis were applied for the examination of main molecular mechanisms driving PIN7 and the extended network. Seven proteins of PIN7 were used as an input for the analysis by GeneMania, a Cytoscape application, which constructs the protein interaction network. The software also extends it using the interactions retrieved from databases of experimental and predicted protein-protein and genetic interactions. The analysis identified the p53 signaling pathway as the most dominant mediator of PIN7. The extended PIN7 was also analyzed by Cytohubba application, which showed that the top-ranked protein nodes belong to the group of histone acetyltransferases and histone deacetylases. These enzymes are involved in the reverse epigenetic regulation mechanisms linked to the regulation of PTK2, NFκB, and p53 signaling interaction subnetworks of the extended PIN7. The analysis emphasized the role of PTK2 signaling, which functions upstream of the p53 signaling pathway and its interaction network includes all members of the sirtuin family. Further, the analysis suggested the involvement of molecular mechanisms related to metastatic cancer (prostate cancer, small cell lung cancer), hemostasis, the regulation of the thyroid hormones and the cell cycle G1/S checkpoint. The additional data-mining analysis showed that the small protein interaction network MYBBP1A-p53-TPPII-SIRT6-CD147 controls Warburg effect and MYBBP1A-p53-TPPII-SIRT7-BSG influences mTOR signaling and autophagy. Further investigations of the detail mechanisms of these interaction networks would be beneficial for the development of novel treatments for aging and age-related diseases.

The molecular mechanisms associated with PIN7, a protein-protein interaction network of seven pleiotropic proteins

10.7287/peerj.preprints.27547v1 ◽

2019 ◽

Author(s):

Jarmila Nahálková

Keyword(s):

Signaling Pathway ◽

Protein Interaction ◽

Molecular Mechanisms ◽

Interaction Network ◽

P53 Signaling ◽

Age Related ◽

P53 Signaling Pathway ◽

Network Pharmacology study of Curcuma longa L.: Potential Target Proteins and their Functional Enrichment Analysis.

10.21203/rs.3.rs-31985/v2 ◽

2020 ◽

Author(s):

SANGEETA KUMARI

Keyword(s):

Signaling Pathway ◽

Mechanism Of Action ◽

Protein Interaction ◽

Curcuma Longa ◽

Interaction Network ◽

Functional Enrichment ◽

Target Proteins ◽

Abstract Objective This study’s primary goal is unraveling the mechanism of action of bioactives of Curcuma longa L. at the molecular level using protein-protein interaction network.Results We used target proteins to create protein-protein interaction network (PPIN) and identified significant node and edge attributes of PPIN. We identified the cluster of proteins in the PPIN, which were used to identify enriched pathways. . We identified closeness centrality and jaccard score as most important node and edge attribute of the PPIN respectively. The enriched pathways of various clusters were overlapped suggesting synergistic mechanism of action. The three pathways found to be common among three clusters were Gonadotropin-releasing hormone receptor pathway, Endothelin signaling pathway, and Inflammation mediated by chemokine and cytokine signaling pathway.

Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias

10.1101/2021.01.14.425874 ◽

2021 ◽

Author(s):

Nikoleta Vavouraki ◽

James E. Tomkins ◽

Eleanna Kara ◽

Henry Houlden ◽

John Hardy ◽

...

Keyword(s):

Machine Learning ◽

Protein Interaction ◽

Molecular Mechanisms ◽

Topological Analysis ◽

Interaction Network ◽

Hereditary Spastic Paraplegias ◽

Core Proteins ◽

AbstractThe Hereditary Spastic Paraplegias are a group of neurodegenerative diseases characterized by spasticity and weakness in the lower body. Despite the identification of causative mutations in over 70 genes, the molecular aetiology remains unclear. Due to the combination of genetic diversity and variable clinical presentation, the Hereditary Spastic Paraplegias are a strong candidate for protein-protein interaction network analysis as a tool to understand disease mechanism(s) and to aid functional stratification of phenotypes. In this study, experimentally validated human protein-protein interactions were used to create a protein-protein interaction network based on the causative Hereditary Spastic Paraplegia genes. Network evaluation as a combination of both topological analysis and functional annotation led to the identification of core proteins in putative shared biological processes such as intracellular transport and vesicle trafficking. The application of machine learning techniques suggested a functional dichotomy linked with distinct sets of clinical presentations, suggesting there is scope to further classify conditions currently described under the same umbrella term of Hereditary Spastic Paraplegias based on specific molecular mechanisms of disease.

Network pharmacology study of Curcuma longa L.: potential target proteins and their functional enrichment analysis

BMC Research Notes ◽

10.1186/s13104-020-05301-0 ◽

2020 ◽

Vol 13 (1) ◽

Author(s):

Sangeeta Kumari ◽

Hosahalli S. Subramanya

Keyword(s):

Signaling Pathway ◽

Mechanism Of Action ◽

Protein Interaction ◽

Curcuma Longa ◽

Interaction Network ◽

Functional Enrichment ◽

Target Proteins ◽

Abstract Objective This study’s primary goal is unraveling the mechanism of action of bioactives of Curcuma longa L. at the molecular level using protein–protein interaction network. Results We used target proteins to create protein–protein interaction network (PPIN) and identified significant node and edge attributes of PPIN. We identified the cluster of proteins in the PPIN, which were used to identify enriched pathways. We identified closeness centrality and jaccard score as most important node and edge attribute of the PPIN respectively. The enriched pathways of various clusters were overlapped suggesting synergistic mechanism of action. The three pathways found to be common among three clusters were Gonadotropin-releasing hormone receptor pathway, Endothelin signaling pathway, and Inflammation mediated by chemokine and cytokine signaling pathway.

Network Pharmacology Study of Curcuma Longa: Potential Target Proteins and their Functional Enrichment Analysis.

10.21203/rs.3.rs-31985/v1 ◽

2020 ◽

Author(s):

SANGEETA KUMARI

Keyword(s):

Signaling Pathway ◽

Mechanism Of Action ◽

Protein Interaction ◽

Curcuma Longa ◽

Interaction Network ◽

Enrichment Analysis ◽

Function Module ◽

Abstract Objective: This study’s primary goal is unraveling the mechanism of action of bioactives of Curcuma longa L. at the molecular level using protein-protein interaction network.Results: We used target proteins to create protein-protein interaction network (PPI) and identified significant node and edge attributes of PPI. To find the function module, we identified the cluster of proteins which were further queried to GO enrichment analysis. Closeness centrality and jaccard score identified as most important node and edge attribute of the protein-protein interaction network respectively. The mapped pathways of various function module of the network were overlapped and showed synergistic mechanism of action. Three most important identified pathways were Gonadotropin-releasing hormone receptor pathway, Endothelin signaling pathway, and Inflammation mediated by chemokine and cytokine signaling pathway.

Exploring The Molecular Mechanisms of Classical Hodgkin Lymphoma Through Bioinformatics Analysis

10.21203/rs.3.rs-586729/v1 ◽

2021 ◽

Author(s):

Zhu Lili ◽

Zhu YuKun ◽

Zhuangzhuang Tian ◽

Yongsheng Li ◽

Liyu Cao

Keyword(s):

Hodgkin Lymphoma ◽

Protein Interaction ◽

Molecular Mechanisms ◽

Kegg Pathway ◽

Interaction Network ◽

Enrichment Analysis ◽

Hub Genes ◽

Abstract Background Classic Hodgkin lymphoma (CHL) is the most common HL in the modern society. Although the treatment of cHL has made great progress, its molecular mechanisms have yet to be deciphered. Objectives The purpose of this study is to find out the crucial potential genes and pathways associated with cHL. Methods We downloaded the cHL microarray dataset (GSE12453) from Gene Expression Omnibus (GEO) database and to identify the differentially expressed genes (DEGs) between cHL samples and normal samples through the limma package in R. Then, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were carried out. Finally, we constructed the protein-protein interaction network to screen out the hub genes using Search Tool for the Retrieval of Interacting Genes (STRING) database. Results We screened out 788 DEGs in the cHL dataset, such as BATF3, IER3, RAB13 and FCRL2. GO functional enrichment analysis indicated that the DEGs were related with regulation of lymphocyte activation, secretory granule lumen and chemokine activity. KEGG pathway analysis showed that the genes enriched in Prion disease, Complement and coagulation cascades and Parkinson disease Coronavirus disease-COVID-19 pathway. Protein-protein interaction network construction identified 10 hub genes (IL6, ITGAM, CD86, FN1, MMP9, CXCL10, CCL5, CD19, IFNG, SELL, UBB) in the network. Conclusions In the present investigation, we identified several pathways and hub genes related to the occurrence and development of cHL, which may provide an important basis for further research and novel therapeutic targets and prognostic indicators for cHL.

Abstract 1629: A protein-protein interaction network for RalB-TBK1 signaling pathway in KRAS mutant non small cell lung cancer

10.1158/1538-7445.am2011-1629 ◽

2011 ◽

Author(s):

Jae-Young Kim ◽

Bin Fang ◽

John Koomen ◽

Guolin Zhang ◽

Eric B. Haura

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Signaling Pathway ◽

Protein Interaction ◽

Interaction Network ◽

Small Cell ◽

Small Cell Lung ◽

The molecular mechanisms associated with PIN7, a protein-protein interaction network of seven pleiotropic proteins

Journal of Theoretical Biology ◽

10.1016/j.jtbi.2019.110124 ◽

2020 ◽

Vol 487 ◽

pp. 110124 ◽

Cited By ~ 1

Author(s):

Jarmila Nahálková

Keyword(s):

Protein Interaction ◽

Molecular Mechanisms ◽

Interaction Network ◽

Network Pharmacology study of Curcuma longa L.: Potential Target Proteins and their Functional Enrichment Analysis.

10.21203/rs.3.rs-31985/v3 ◽

2020 ◽

Author(s):

SANGEETA KUMARI ◽

Hosahalli S. Subramanya

Keyword(s):

Signaling Pathway ◽

Mechanism Of Action ◽

Protein Interaction ◽

Curcuma Longa ◽

Interaction Network ◽

Functional Enrichment ◽

Target Proteins ◽

Abstract ObjectiveThis study’s primary goal is unraveling the mechanism of action of bioactives of Curcuma longa L. at the molecular level using protein-protein interaction network.ResultsWe used target proteins to create protein-protein interaction network (PPIN) and identified significant node and edge attributes of PPIN. We identified the cluster of proteins in the PPIN, which were used to identify enriched pathways. We identified closeness centrality and jaccard score as most important node and edge attribute of the PPIN respectively. The enriched pathways of various clusters were overlapped suggesting synergistic mechanism of action. The three pathways found to be common among three clusters were Gonadotropin-releasing hormone receptor pathway, Endothelin signaling pathway, and Inflammation mediated by chemokine and cytokine signaling pathway.

A Computational Framework to Identify Cross Association between Complex Disorders by Protein-Protein Interaction Network Analysis

Current Bioinformatics ◽

10.2174/1574893615999200724145434 ◽

2020 ◽

Vol 15 ◽

Author(s):

Nikhila T Suresh ◽

Vimina E R ◽

U. Krishnakumar

Keyword(s):

Blood Pressure ◽

Signaling Pathway ◽

Protein Interaction ◽

Interaction Network ◽

Complex Disorders ◽

Associated Proteins ◽

Key Genes ◽

Objective: It is a known fact that numerous complex disorders do not happen in isolation indicating the plausible set of shared causes common to several different sicknesses. Hence, analysis of comorbidity can be utilized to explore association between several disorders. In this study, we have proposed a network-based computational approach, in which genes are organized based on the topological characteristics of the constructed Protein-Protein Interaction Network (PPIN) followed by a network prioritization scheme, to identify distinctive key genes and biological pathways shared among diseases. Methods: The proposed approach is initiated from constructed PPIN of any randomly chosen disease genes in order to infer its associations with other diseases in terms of shared pathways, co-expression, co-occurrence etc. For this, initially proteins associated to any disease based on random choice were identified. Secondly, PPIN is organized through topological analysis to define hub genes. Finally, using a prioritization algorithm a ranked list of newly predicted multimorbidity-associated proteins is generated. Using Gene Ontology (GO), cellular pathways involved in multimorbidity-associated proteins are mined. Result and Conclusion: The proposed methodology is tested using three disorders namely Diabetes, Obesity and blood pressure at an atomic level and the results suggest the comorbidity of other complex diseases that have associations with the proteins included in disease of present study through shared proteins and pathways. For diabetes, we have obtained key genes like GAPDH, TNF, IL6, AKT1, ALB, TP53, IL10, MAPK3, TLR4 and EGF with key pathways like P53 pathway, VEGF signaling pathway, Ras Pathway, Interleukin signaling pathway, Endothelin signaling pathway, Huntington disease etc. Study on other disorders such as obesity and blood pressure also revealed promising results.