{"title":"Two scenarios for overcoming drug resistance by co-targeting.","authors":"Golnaz Taheri, Marzieh Ayati, Limsoon Wong, Changiz Eslahchi","doi":"10.1504/IJBRA.2015.067338","DOIUrl":null,"url":null,"abstract":"<p><p>Removal of proteins on an essential pathway of a pathogen is expected to prohibit the pathogen from performing a vital function. To disrupt these pathways, we consider a cut set S of simple graph G, where G representing the PPI network of the pathogen. After removing S, if the difference of sizes of two partitions is high, the probability of existence of a functioning pathway is increased. We need to partition the graph into balanced partitions and approximate it with spectral bipartitioning. We consider two scenarios: in the first, we do not have any information on drug targets; in second, we consider information on drug targets. Our databases are E. coli and C. jejuni. In the first scenario, 20% and 17% of proteins in cut of E. coli and C. jejuni are drug targets and in the second scenario 53% and 63% of proteins in cut are drug targets respectively. </p>","PeriodicalId":35444,"journal":{"name":"International Journal of Bioinformatics Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJBRA.2015.067338","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Bioinformatics Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJBRA.2015.067338","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 2
Abstract
Removal of proteins on an essential pathway of a pathogen is expected to prohibit the pathogen from performing a vital function. To disrupt these pathways, we consider a cut set S of simple graph G, where G representing the PPI network of the pathogen. After removing S, if the difference of sizes of two partitions is high, the probability of existence of a functioning pathway is increased. We need to partition the graph into balanced partitions and approximate it with spectral bipartitioning. We consider two scenarios: in the first, we do not have any information on drug targets; in second, we consider information on drug targets. Our databases are E. coli and C. jejuni. In the first scenario, 20% and 17% of proteins in cut of E. coli and C. jejuni are drug targets and in the second scenario 53% and 63% of proteins in cut are drug targets respectively.
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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