A side-effect free method for identifying cancer drug targets

• 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: QH301 Biology; RC0254 Neoplasms. Tumors. Oncology (including Cancer)
• 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

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the correct drug targets, due to side efect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn.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 Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc).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.