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

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.

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An Effective Statistical Integrative Algorithm (Aeiapp) for Protein Prediction

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.k1253.0981119 ◽

2019 ◽

Vol 8 (11) ◽

pp. 132-137 ◽

Cited By ~ 1

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.

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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 ◽

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.

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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 ◽

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.

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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 ◽

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.

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