scholarly journals Analysis of Protein Interaction Networks to Prioritize Drug Targets of Neglected-Diseases Pathogens

10.5772/38463 ◽  
2012 ◽  
Author(s):  
Aldo Segura-Cabrera ◽  
Carlos A. ◽  
Mario A. ◽  
Xianwu Guo ◽  
Gildardo Rivera ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Drug Targets ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Neglected Diseases

scholarly journals Association between ALS and retroviruses: evidence from bioinformatics analysis

2019 ◽  
Vol 20 (S24) ◽  
Author(s):  
Jon P. Klein ◽  
Zhifu Sun ◽  
Nathan P. Staff
Keyword(s):  
Protein Interaction ◽  
Drug Targets ◽  
Large Scale ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Pathway Enrichment Analysis ◽  
Protein Database ◽  
Core Cluster

Abstract Background Emerging evidence suggests retroviruses play a role in the pathophysiology of amyotrophic lateral sclerosis (ALS). Specifically, activation of ancient viral genes embedded in the human genome is theorized to lead to motor neuron degeneration. We explore whether connections exist between ALS and retroviruses through protein interaction networks (PIN) and pathway analysis, and consider the potential roles in drug target discovery. Protein database and pathway/network analytical software including Ingenuity Pathway BioProfiler, STRING, and CytoScape were utilized to identify overlapping protein interaction networks and extract core cluster (s) of retroviruses and ALS. Results Topological and statistical analysis of the ALS-PIN and retrovirus-PIN identified a shared, essential protein network and a core cluster with significant connections with both networks. The identified core cluster has three interleukin molecules IL10, Il-6 and IL-1B, a central apoptosis regulator TP53, and several major transcription regulators including MAPK1, ANXA5, SQSTM1, SREBF2, and FADD. Pathway enrichment analysis showed that this core cluster is associated with the glucocorticoid receptor singling and neuroinflammation signaling pathways. For confirmation purposes, we applied the same methodology to the West Nile and Polio virus, which demonstrated trivial connectivity with ALS, supporting the unique connection between ALS and retroviruses. Conclusions Bioinformatics analysis provides evidence to support pathological links between ALS and retroviral activation. The neuroinflammation and apoptotic regulation pathways are specifically implicated. The continuation and further analysis of large scale genome studies may prove useful in exploring genes important in retroviral activation and ALS, which may help discover new drug targets.

scholarly journals Network and pathway expansion of genetic disease associations identifies successful drug targets

2020 ◽  
Author(s):  
Aidan MacNamara ◽  
Nikolina Nakic ◽  
Ali Amin ◽  
Cong Guo ◽  
Karsten B. Sieber ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Drug Targets ◽  
Empirical Test ◽  
Clinical Trial Data ◽  
Protein Interaction Networks ◽  
Genetic Evidence ◽  
Interaction Networks ◽  
Genetic Associations ◽  
Disease Associations ◽  
Network Propagation

AbstractIt is widely accepted that genetic evidence of disease association acts as a sound basis for the selection of drug targets for complex common diseases and that propagation of genetic evidence through gene or protein interaction networks can accurately infer novel disease associations at genes for which no direct genetic evidence can be observed. However, an empirical test of the utility of combining these beliefs for drug discovery has been lacking.In this study, we examine genetic associations arising from an analysis of 648 UK Biobank GWAS and evaluate whether targets identified as proxies of direct genetic hits are enriched for successful drug targets, as measured by historical clinical trial data.We find that protein networks formed from specific functional linkages such as protein complexes and ligand-receptor pairs are suitable for even naïve guilt-by-association network propagation approaches. In addition, more sophisticated approaches applied to global protein-protein interaction networks and pathway databases, also successfully retrieve targets enriched for clinically successful drug targets. We conclude that network propagation of genetic evidence should be used for drug target identification.

scholarly journals Network and pathway expansion of genetic disease associations identifies successful drug targets

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Aidan MacNamara ◽  
Nikolina Nakic ◽  
Ali Amin Al Olama ◽  
Cong Guo ◽  
Karsten B. Sieber ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Drug Targets ◽  
Empirical Test ◽  
Clinical Trial Data ◽  
Protein Interaction Networks ◽  
Genetic Evidence ◽  
Interaction Networks ◽  
Genetic Associations ◽  
Disease Associations ◽  
Network Propagation

AbstractGenetic evidence of disease association has often been used as a basis for selecting of drug targets for complex common diseases. Likewise, the propagation of genetic evidence through gene or protein interaction networks has been shown to accurately infer novel disease associations at genes for which no direct genetic evidence can be observed. However, an empirical test of the utility of combining these approaches for drug discovery has been lacking. In this study, we examine genetic associations arising from an analysis of 648 UK Biobank GWAS and evaluate whether targets identified as proxies of direct genetic hits are enriched for successful drug targets, as measured by historical clinical trial data. We find that protein networks formed from specific functional linkages such as protein complexes and ligand–receptor pairs are suitable for even naïve guilt-by-association network propagation approaches. In addition, more sophisticated approaches applied to global protein–protein interaction networks and pathway databases, also successfully retrieve targets enriched for clinically successful drug targets. We conclude that network propagation of genetic evidence can be used for drug target identification.

scholarly journals Deubiquitinases and the new therapeutic opportunities offered to cancer

2015 ◽  
Vol 22 (1) ◽  
pp. T35-T54 ◽  
Author(s):  
Roland Pfoh ◽  
Ira Kay Lacdao ◽  
Vivian Saridakis
Keyword(s):  
Thyroid Cancer ◽  
Protein Interaction ◽  
Adrenocortical Carcinoma ◽  
Drug Targets ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Regulatory Mechanisms ◽  
Potential Drug ◽  
Diagnosis And Prognosis ◽  
Potential Drug Targets

Deubiquitinases (DUBs) play important roles and therefore are potential drug targets in various diseases including cancer and neurodegeneration. In this review, we recapitulate structure–function studies of the most studied DUBs including USP7, USP22, CYLD, UCHL1, BAP1, A20, as well as ataxin 3 and connect them to regulatory mechanisms and their growing protein interaction networks. We then describe DUBs that have been associated with endocrine carcinogenesis with a focus on prostate, ovarian, and thyroid cancer, pheochromocytoma, and adrenocortical carcinoma. The goal is enhancing our understanding of the connection between dysregulated DUBs and cancer to permit the design of therapeutics and to establish biomarkers that could be used in diagnosis and prognosis.

Sign in / Sign up

Export Citation Format

Share Document