A side-effect free method for identifying cancer drug targets

Identifying efective drug targets, with little or no side efects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side efect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity,...

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Main Authors: Ashraf, Md. Izhar, Ong, Seng Kai *, Mujawar, Shama *, Pawar, Shrikant, More, Pallavi, Somnath, Paul, Lahiri, Chandrajit *
Format: Article
Language:English
Published: Nature Publishing Group 2018
Subjects:
Online Access:http://eprints.sunway.edu.my/899/1/Chandrajit%20Side%20Effect%20Free%20Method.pdf
http://eprints.sunway.edu.my/899/
http://doi.org/10.1038/s41598-018-25042-2
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spelling my.sunway.eprints.8992019-04-26T09:05:09Z http://eprints.sunway.edu.my/899/ A side-effect free method for identifying cancer drug targets Ashraf, Md. Izhar Ong, Seng Kai * Mujawar, Shama * Pawar, Shrikant More, Pallavi Somnath, Paul Lahiri, Chandrajit * QH301 Biology RC0254 Neoplasms. Tumors. Oncology (including Cancer) Identifying efective drug targets, with little or no side efects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side efect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identifcation of efective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying efective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as efective candidates for drug development. Nature Publishing Group 2018-04-27 Article PeerReviewed text en http://eprints.sunway.edu.my/899/1/Chandrajit%20Side%20Effect%20Free%20Method.pdf Ashraf, Md. Izhar and Ong, Seng Kai * and Mujawar, Shama * and Pawar, Shrikant and More, Pallavi and Somnath, Paul and Lahiri, Chandrajit * (2018) A side-effect free method for identifying cancer drug targets. Scientific Reports, 8 (1). ISSN 2045-2322 http://doi.org/10.1038/s41598-018-25042-2 doi:10.1038/s41598-018-25042-2
institution Sunway University
building Sunway Campus Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Sunway University
content_source Sunway Institutional Repository
url_provider http://eprints.sunway.edu.my/
language English
topic QH301 Biology
RC0254 Neoplasms. Tumors. Oncology (including Cancer)
spellingShingle QH301 Biology
RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Ashraf, Md. Izhar
Ong, Seng Kai *
Mujawar, Shama *
Pawar, Shrikant
More, Pallavi
Somnath, Paul
Lahiri, Chandrajit *
A side-effect free method for identifying cancer drug targets
description Identifying efective drug targets, with little or no side efects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side efect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identifcation of efective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying efective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as efective candidates for drug development.
format Article
author Ashraf, Md. Izhar
Ong, Seng Kai *
Mujawar, Shama *
Pawar, Shrikant
More, Pallavi
Somnath, Paul
Lahiri, Chandrajit *
author_facet Ashraf, Md. Izhar
Ong, Seng Kai *
Mujawar, Shama *
Pawar, Shrikant
More, Pallavi
Somnath, Paul
Lahiri, Chandrajit *
author_sort Ashraf, Md. Izhar
title A side-effect free method for identifying cancer drug targets
title_short A side-effect free method for identifying cancer drug targets
title_full A side-effect free method for identifying cancer drug targets
title_fullStr A side-effect free method for identifying cancer drug targets
title_full_unstemmed A side-effect free method for identifying cancer drug targets
title_sort side-effect free method for identifying cancer drug targets
publisher Nature Publishing Group
publishDate 2018
url http://eprints.sunway.edu.my/899/1/Chandrajit%20Side%20Effect%20Free%20Method.pdf
http://eprints.sunway.edu.my/899/
http://doi.org/10.1038/s41598-018-25042-2
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