Dataset Information

Human, vector and parasite Hsp90 proteins: A comparative bioinformatics analysis.

ABSTRACT: The treatment of protozoan parasitic diseases is challenging, and thus identification and analysis of new drug targets is important. Parasites survive within host organisms, and some need intermediate hosts to complete their life cycle. Changing host environment puts stress on parasites, and often adaptation is accompanied by the expression of large amounts of heat shock proteins (Hsps). Among Hsps, Hsp90 proteins play an important role in stress environments. Yet, there has been little computational research on Hsp90 proteins to analyze them comparatively as potential parasitic drug targets. Here, an attempt was made to gain detailed insights into the differences between host, vector and parasitic Hsp90 proteins by large-scale bioinformatics analysis. A total of 104 Hsp90 sequences were divided into three groups based on their cellular localizations; namely cytosolic, mitochondrial and endoplasmic reticulum (ER). Further, the parasitic proteins were divided according to the type of parasite (protozoa, helminth and ectoparasite). Primary sequence analysis, phylogenetic tree calculations, motif analysis and physicochemical properties of Hsp90 proteins suggested that despite the overall structural conservation of these proteins, parasitic Hsp90 proteins have unique features which differentiate them from human ones, thus encouraging the idea that protozoan Hsp90 proteins should be further analyzed as potential drug targets.

SUBMITTER: Faya N

PROVIDER: S-EPMC4688443 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Human, vector and parasite Hsp90 proteins: A comparative bioinformatics analysis.

Faya Ngonidzashe N Penkler David L DL Tastan Bishop Özlem Ö

FEBS open bio 20151114

The treatment of protozoan parasitic diseases is challenging, and thus identification and analysis of new drug targets is important. Parasites survive within host organisms, and some need intermediate hosts to complete their life cycle. Changing host environment puts stress on parasites, and often adaptation is accompanied by the expression of large amounts of heat shock proteins (Hsps). Among Hsps, Hsp90 proteins play an important role in stress environments. Yet, there has been little computat ...[more]

PMID: 26793431

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Project description:BackgroundProtein classification is a task of paramount importance in various fields of biology. Despite the great momentum of modern implementation of protein classification, machine learning techniques such as Random Forest and Neural Network could not always be used for several reasons: data collection, unbalanced classification or labelling of the data.As an alternative, I propose the use of a bioinformatics pipeline to search for and classify information from protein databases. Hence, to evaluate the efficiency and accuracy of the pipeline, I focused on the carotenoid biosynthetic genes and developed a filtering approach to retrieve orthologs clusters in two well-studied plants that belong to the Brassicaceae family: Arabidopsis thaliana and Brassica rapa Pekinensis group. The result obtained has been compared with previous studies on carotenoid biosynthetic genes in B. rapa where phylogenetic analysis was conducted.ResultsThe developed bioinformatics pipeline relies on commercial software and multiple databeses including the use of phylogeny, Gene Ontology terms (GOs) and Protein Families (Pfams) at a protein level. Furthermore, the phylogeny is coupled with "population analysis" to evaluate the potential orthologs. All the steps taken together give a final table of potential orthologs. The phylogenetic tree gives a result of 43 putative orthologs conserved in B. rapa Pekinensis group. Different A. thaliana proteins have more than one syntenic ortholog as also shown in a previous finding (Li et al., BMC Genomics 16(1):1-11, 2015).ConclusionsThis study demonstrates that, when the biological features of proteins of interest are not specific, I can rely on a computational approach in filtering steps for classification purposes. The comparison of the results obtained here for the carotenoid biosynthetic genes with previous research confirmed the accuracy of the developed pipeline which can therefore be applied for filtering different types of datasets.

Project description:BackgroundAortic dissection (AD) poses a great threat to the life of patients; however, there is currently no documentation of a clear pathogenic mechanism of this disease. In recent years, β-aminopropionitrile (BAPN)-induced AD in rodents has been widely used in basic research, which provides a good platform for exploring the pathogenesis of AD and drug modification. This study aimed to identify molecular markers and pathways for the diagnosis and treatment of AD by comparing a murine AD model and human AD transcriptome through a bioinformatics analysis.MethodsWe constructed a BAPN-induced mice model and performed high-throughput sequencing analysis. The GSE147026 dataset of patients was obtained from the Gene Expression Omnibus database. We performed a subsequent bioinformatics analysis of human AD and the murine AD model using R software. The DESeq software package was used to analyze the differentially expressed genes (DEGs). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to analyze the enrichment pathways. Protein-protein interaction network construction and hub gene selection were based on STRING software analysis. Stepwise identification of potential drugs was performed online, while hub genes were validated immunohistochemically.ResultsWe compared the murine AD model and human AD transcriptome and found that both differentially expressed 463 genes. The cytokine-cytokine receptor interaction, tuberculosis, and phagosome pathways were significantly enriched. CDC20, CCNB2, and CCNB1 may be associated with AD development. Protein-drug interactions were also identified.ConclusionsThis study is the first to reveal transcriptional changes in a murine BAPN-induced AD model versus human AD transcriptome. Furthermore, we identified the important hub genes, related pathways, and potential drugs by analyzing the overlapping DEGs between human AD and the murine AD model. Our results provide a basis for the further identification of potential molecular markers for diagnosing and treating AD.

Dataset Information

Human, vector and parasite Hsp90 proteins: A comparative bioinformatics analysis.

Publications

Human, vector and parasite Hsp90 proteins: A comparative bioinformatics analysis.

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