DocumentCode
2413169
Title
Overcoming drug resistance by co-targeting
Author
Ayati, Marzieh ; Taheri, Golnaz ; Arab, Shahriar ; Wong, Limsoon ; Eslahchi, Changiz
Author_Institution
Dept. of Comput. Sci., Sharif Univ. of Technol., Tehran, Iran
fYear
2010
fDate
18-21 Dec. 2010
Firstpage
198
Lastpage
202
Abstract
Removal or suppression of key proteins in an essential pathway of a pathogen is expected to disrupt the pathway and prohibit the pathogen from performing a vital function. Thus disconnecting multiple essential pathways should disrupt the survival of a pathogen even when it has multiple pathways to drug resistance. We consider a scenario where the drug-resistance pathways are unknown. To disrupt these pathways, we consider a cut set S of G, where G is a connected simple graph representing the protein interaction network of the pathogen, so that G-S splits to two partitions such that the endpoints of each pathway are in different partitions. If the difference between the sizes of the two partitions is high, the probability of existence of a functioning pathway in one partition is increased. Thus, we need to partition the graph into two balanced partitions. We approximate the balanced bipartitioning problem with spectral bipartitioning since finding (2, 1)-separator is NP-complete. We test our technique on E. coli and C. jejuni. We show that over 50% of genes in the cut sets are essential. Moreover, all proteins in the cut sets have fundamental roles in cell and inhibition of each of them is harmful for cell survival. Also, 20% and 17% of known targets are in the vertex cut of E. coli and C. jejuni. Hence our approach has produced plausible “co-targets” whose inhibition should counter a pathogen´s drug resistance.
Keywords
biology computing; cellular biophysics; complex networks; graph theory; microorganisms; molecular biophysics; optimisation; probability; proteins; C. jejuni; E. coli; NP-complete problem; balanced bipartitioning problem; cell survival; connected simple graph; cotargeting; drug resistance pathway disruption; functioning pathway existence probability; pathogen protein interaction network; pathogen survival disruption; protein removal; protein suppression; spectral bipartitioning; Drugs; Eigenvalues and eigenfunctions; Immune system; Laplace equations; Partitioning algorithms; Pathogens; Proteins;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedicine (BIBM), 2010 IEEE International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-8306-8
Electronic_ISBN
978-1-4244-8307-5
Type
conf
DOI
10.1109/BIBM.2010.5706562
Filename
5706562
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