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Network Modeling Analysis in Health Informatics and Bioinformatics

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01.12.2018 | Original Article

Cancer drug target identification and node-level analysis of the network of MAPK pathways

verfasst von: V. K. MD Aksam, V. M. Chandrasekaran, Sundaramurthy Pandurangan

Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics | Ausgabe 1/2018

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Abstract

Mitogen-activated protein kinase (MAPK) pathways extensively studied in cancer and governing intertwined biological process challenges to identify the efficient drug target strategy. Cross-talks among ERK1/2, ERK5, JNK, and p38 amplify signaling flow and lead to the construction of the network of MAPK pathways. A topological analysis reveals that the network exponentially fits the degree distributions and targeting hub proteins causes detrimental to the network. We aim to identify novel drug targets controlling pathological consequences in the signaling flow than killing the cell. Intra-pathway node inhibition causes less perturbation in the network. We set the strategy of considering low degree (< 5) and intra-pathway nodes free from the intertwined regulations as preliminary isolation. Furthermore, nodes with less functionally diverse and significantly contributing to the cancer are isolated using GO annotations. Elements in the network of the MAPK pathways catalogued and analyzed using protein types, subcellular localization, cancerous/non-cancerous nature, target/non-targeted status, and inter- and intra-pathway properties to illustrate their roles in the complex mechanism of cancer. Over a decade of kinases as promising drug targets for cancer, other signal transduction supporting proteins also found to be equally competent. However, kinases interact with various other proteins to gain the higher degree. Similarly, translocation proteins interact with their partners in diverse location to gain the degree and functionally vital. Inhibition of kinases and translocation proteins may draw unexpected side effects. Non-targeted nodes Mos, PAC1, MKP4, 4EBP1, LAD, M3/6, RNPK, and SRF identified as cancer drug targets.

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Titel: Cancer drug target identification and node-level analysis of the network of MAPK pathways
verfasst von: V. K. MD Aksam
V. M. Chandrasekaran
Sundaramurthy Pandurangan
Publikationsdatum: 01.12.2018
Verlag: Springer Vienna
Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics / Ausgabe 1/2018
Print ISSN: 2192-6662
Elektronische ISSN: 2192-6670
DOI: https://doi.org/10.1007/s13721-018-0165-1

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