CSIR-Indian Institute of Toxicology Research, Lucknow, Uttar Pradesh. India.
Department of Systems Biology and Bioinformatics, University of Rostock, Rostock. Germany.
Curr Pharm Des. 2017;23(32):4773-4793. doi: 10.2174/1381612823666170710152918.
The identification and validation of novel drug-target combinations are key steps in the drug discovery processes. Cancer is a complex disease that involves several genetic and environmental factors. High-throughput omics technologies are now widely available, however the integration of multi-omics data to identify viable anticancer drug-target combinations, that allow for a better clinical outcome when considering the efficacy-toxicity spectrum, is challenging. This review article provides an overview of systems approaches which help to integrate a broad spectrum of technologies and data. We focus on network approaches and investigate anticancer mechanism and biological targets of resveratrol using reverse pharmacophore mapping as an in-depth case study. The results of this case study demonstrate the use of systems approaches for a better understanding of the behavior of small molecule inhibitors in receptor binding sites. The presented network analysis approach helps in formulating hypotheses and provides mechanistic insights of resveratrol in neoplastic transformations.
鉴定和验证新的药物-靶标组合是药物发现过程中的关键步骤。癌症是一种复杂的疾病，涉及多种遗传和环境因素。高通量组学技术现在已经广泛应用，然而，整合多组学数据以识别可行的抗癌药物-靶标组合，在考虑疗效-毒性谱时，以获得更好的临床结果，是具有挑战性的。本文综述了有助于整合广泛技术和数据的系统方法。我们专注于网络方法，并使用反向药效基团映射作为深入的案例研究来研究白藜芦醇的抗癌机制和生物靶标。该案例研究的结果表明，系统方法可用于更好地理解小分子抑制剂在受体结合位点的行为。所提出的网络分析方法有助于形成假说，并提供白藜芦醇在肿瘤转化中的机制见解。
