The Institute of Mathematical Sciences, Chennai, 600113, India.
B.S. Abdur Rahman Crescent Institute of Science & Technology, Vandalur, Chennai, 600048, India.
Sci Rep. 2018 Apr 27;8(1):6669. doi: 10.1038/s41598-018-25042-2.
Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective 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 effective 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 Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc).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 effective candidates for drug development.
确定有效且副作用小的药物靶点仍然是一项极具挑战性的任务。如果未能发现由于多效基因的副作用而导致的正确药物靶点，可能会导致潜在药物被非法撤回。通过几种蛋白质互作组分析方法，可以简化疾病的复杂性，以研究其机制并确定有效的药物靶点。其中，中心性度量在识别候选药物靶点方面一直具有重要意义。在这里，我们提出了一种分析癌症复杂网络的综合方法，并描述了核心度、功能连通性和中心性（KFC）在识别有效药物靶点方面的重要性。本质上，我们从列出真实实验数据集的途径数据库中提取了参与导致癌症的途径的蛋白质。这些蛋白质之间的相互作用被映射以构建互作组。互作组的综合分析使我们能够揭示药物被撤回的可能原因，从而为制药行业提供潜在的避免这些原因的机会（例如 ESR1、HDAC2、F2、PLG、PPARA、RXRA 等）。根据我们的 KFC 标准，我们已经确定了十个蛋白质（GRB2、FYN、PIK3R1、CBL、JAK2、LCK、LYN、SYK、JAK1 和 SOCS3）作为药物开发的有效候选物。
