An interactomic approach for identification of putative drug targets in Listeria monocytogenes

Q4 Health Professions
Nikita Chordia, N. Sharma, Anil Kumar
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引用次数: 4

Abstract

A wide variety of human population is infected with Listeria monocytogenes, which causes listeriosis, a deadly disease with mortality rate of about 30%. The major hindrance to cure listeriosis is the unavailability of specific or selectable drug targets. At present, antibiotics used to cure the disease are not specific and insufficient to manage the disease efficiently. Therefore, in order to search specific drugs, here, we used interactome analysis to search specific drug targets which may provide novel templates for drug designing having better efficacy without any potential adverse effects. The complete genome of L. monocytogenes having 2846 proteins has been analysed. We found 11 proteins as putative drug targets. The sequence and interactome analyses revealed that 11 proteins are non-homologous to human, but essential for pathogen and hence may be considered as potential therapeutic targets.
单核细胞增生李斯特菌推定药物靶点鉴定的相互作用方法
各种各样的人群感染单核细胞增生李斯特菌,导致李斯特菌病,这是一种死亡率约为30%的致命疾病。治疗李斯特菌病的主要障碍是缺乏特定或可选择的药物靶点。目前,用于治疗该病的抗生素不具有特异性,不足以有效地控制该病。因此,为了寻找特异性药物,我们采用相互作用组分析的方法,寻找特异性药物靶点,为药物设计提供新的模板,使其具有更好的疗效,并且没有潜在的不良反应。对单核增生乳杆菌2846个蛋白的全基因组进行了分析。我们发现了11种可能的药物靶点蛋白。序列和相互作用组分析表明,其中11个蛋白与人非同源,但对病原菌是必需的,因此可能被认为是潜在的治疗靶点。
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来源期刊
International Journal of Bioinformatics Research and Applications
International Journal of Bioinformatics Research and Applications Health Professions-Health Information Management
CiteScore
0.60
自引率
0.00%
发文量
26
期刊介绍: Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.
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