scholarly journals An Effective Statistical Integrative Algorithm (Aeiapp) for Protein Prediction

2019 ◽  
Vol 8 (11) ◽  
pp. 132-137 ◽  
Keyword(s):  
Protein Interaction ◽  
Biological Networks ◽  
Protein Interaction Network ◽  
Protein Identification ◽  
Research Work ◽  
Interaction Network ◽  
Integrative Approach ◽  
Target Proteins ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

The task of predicting target proteins for new drug discovery is typically difficult. Target proteins are biologically most important to control a keen functional process. The recent research of experimental and computational -based approaches has been widely used to predict target proteins using biological networks analysis techniques. Perhaps with available methods and statistical algorithm needs to be modified and should be clearer to tag the main target. Meanwhile identifying wrong protein leads to unwanted molecular interaction and pharmacological activity. In this research work, a novel method to identify essential target proteins using integrative graph coloring algorithm has been proposed. The proposed integrative approach helps to extract essential proteins in protein-protein interaction network (PPI) by analyzing neighborhood of the active target protein. Experimental results reviewed based on protein-protein interaction network for homosapiens showed that AEIAPP based approach shows an improvement in the essential protein identification by assuming the source protein as biologically proven protein. The AEIAPP statistical model has been compared with other state of art approaches on human PPI for various diseases to produce good accurate outcome in faster manner with little memory consumption.

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

2020 ◽  
Author(s):  
SANGEETA KUMARI
Keyword(s):  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Curcuma Longa ◽  
Interaction Network ◽  
Functional Enrichment ◽  
Target Proteins ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

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.

scholarly journals An expanded protein-protein interaction network in Bacillus subtilis reveals a group of hubs: Exploration by an integrative approach

PROTEOMICS ◽  
2011 ◽  
Vol 11 (15) ◽  
pp. 2981-2991 ◽  
Author(s):  
Elodie Marchadier ◽  
Rut Carballido-López ◽  
Sophie Brinster ◽  
Céline Fabret ◽  
Peggy Mervelet ◽  
...  
Keyword(s):  
Bacillus Subtilis ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Integrative Approach ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

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

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Sangeeta Kumari ◽  
Hosahalli S. Subramanya
Keyword(s):  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Curcuma Longa ◽  
Interaction Network ◽  
Functional Enrichment ◽  
Target Proteins ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

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.

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

2020 ◽  
Author(s):  
SANGEETA KUMARI ◽  
Hosahalli S. Subramanya
Keyword(s):  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Curcuma Longa ◽  
Interaction Network ◽  
Functional Enrichment ◽  
Target Proteins ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

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.

scholarly journals Application of multiple omics and network projection analyses to drug repositioning for pathogenic mosquito-borne viruses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Takayuki Amemiya ◽  
Katsuhisa Horimoto ◽  
Kazuhiko Fukui
Keyword(s):  
Protein Interaction ◽  
Protein Interaction Network ◽  
Neglected Tropical Diseases ◽  
Drug Repositioning ◽  
Interaction Network ◽  
Public Health Issue ◽  
Target Proteins ◽  
Drug Candidates ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

AbstractPathogenic mosquito-borne viruses are a serious public health issue in tropical and subtropical regions and are increasingly becoming a problem in other climate zones. Drug repositioning is a rapid, pharmaco-economic approach that can be used to identify compounds that target these neglected tropical diseases. We have applied a computational drug repositioning method to five mosquito-borne viral infections: dengue virus (DENV), zika virus (ZIKV), West Nile virus (WNV), Japanese encephalitis virus (JEV) and Chikungunya virus (CHIV). We identified signature molecules and pathways for each virus infection based on omics analyses, and determined 77 drug candidates and 146 proteins for those diseases by using a filtering method. Based on the omics analyses, we analyzed the relationship among drugs, target proteins and the five viruses by projecting the signature molecules onto a human protein–protein interaction network. We have classified the drug candidates according to the degree of target proteins in the protein–protein interaction network for the five infectious diseases.

scholarly journals Protein-Protein Interaction Analysis through Network Topology (Oral Cancer)

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Fazal Wahab Khattak ◽  
Yousef Salamah Alhwaiti ◽  
Amjad Ali ◽  
Mohammad Faisal ◽  
Muhammad Hameed Siddiqi
Keyword(s):  
Oral Cancer ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Analysis ◽  
Research Work ◽  
Interaction Network ◽  
Role Playing ◽  
The Body ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

Oral cancer is a complex disorder. Its creation and spreading are due to the interaction of several proteins and genes in different biological thoroughfares. To study biological pathways, many high-yield methods have been used. Efforts to merge several data found at separate levels related to biological thoroughfares and interlinkage networks remain elusive. In our research work, we have proposed a technique known as protein-protein interaction network for analysis and exploring the genes involved in oral cancer disorders. The previous studies have not fully analyzed the proteins or genes involved in oral cancer. Our proposed technique is fully interactive and analyzes the data of oral cancer disorder more accurately and efficiently. The methods used here enabled us to observe the wide network consists of one mighty network comprising of 208 nodes 1572 edges which connect these nodes and various detached small networks. In our study, TP53 is a gene that occupied an important position in the network. TP53 has a 113-degree value and 0.03881821 BC value, indicating that TP53 is centrally localized in the network and is a significant bottleneck protein in the oral cancer protein-protein interaction network. These findings suggested that the pathogenesis of oral cancer variation was organized by means of an integrated PPI network, which is centered on TP53. Furthermore, our identification shows that TP53 is the key role-playing protein in the oral cancer network, and its significance in the cellular networks in the body is determined as well. As TP53 (tumor protein 53) is a vital player in the cell division process, the cells may not grow or divide disorderly; it fulfills the function of at least one of the gene groups in oral cancer. However, the latter progression in the area is any measure; the intention of developing these networks is to transfigure sketch of core disease development, prognosis, and treatment.

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