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计算机模拟肿瘤学药物重新定位与多药理学

In Silico Oncology Drug Repositioning and Polypharmacology.

作者信息

Cheng Feixiong

机构信息

Center for Complex Networks Research, Northeastern University, Boston, MA, USA.

出版信息

Methods Mol Biol. 2019;1878:243-261. doi: 10.1007/978-1-4939-8868-6_15.

Abstract

Network-aided in silico approaches have been widely used for prediction of drug-target interactions and evaluation of drug safety to increase the clinical efficiency and productivity during drug discovery and development. Here we review the advances and new progress in this field and summarize the translational applications of several new network-aided in silico approaches we developed recently. In addition, we describe the detailed protocols for a network-aided drug repositioning infrastructure for identification of new targets for old drugs, failed drugs in clinical trials, and new chemical entities. These state-of-the-art network-aided in silico approaches have been used for the discovery and development of broad-acting and targeted clinical therapies for various complex diseases, in particular for oncology drug repositioning. In this chapter, the described network-aided in silico protocols are appropriate for target-centric drug repositioning to various complex diseases, but expertise is still necessary to perform the specific oncology projects based on the cancer targets of interest.

摘要

网络辅助的计算机模拟方法已被广泛用于预测药物-靶点相互作用和评估药物安全性,以提高药物发现和开发过程中的临床效率和生产力。在此,我们回顾该领域的进展和新成果,并总结我们最近开发的几种新型网络辅助计算机模拟方法的转化应用。此外,我们描述了一种网络辅助药物重新定位基础设施的详细方案,用于识别旧药的新靶点、临床试验中失败的药物以及新化学实体。这些最先进的网络辅助计算机模拟方法已用于各种复杂疾病的广谱和靶向临床治疗的发现和开发,特别是用于肿瘤学药物重新定位。在本章中,所描述的网络辅助计算机模拟方案适用于针对各种复杂疾病的以靶点为中心的药物重新定位,但基于感兴趣的癌症靶点开展特定的肿瘤学项目仍需要专业知识。

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