School of Information Science and Technology, Northeast Normal University, Changchun, China.
Institution of Computational Biology, Northeast Normal University, Changchun, China.
Curr Drug Targets. 2019;20(5):551-564. doi: 10.2174/1389450120666181204164721.
Membrane proteins play crucial physiological roles in vivo and are the major category of drug targets for pharmaceuticals. The research on membrane protein is a significant part in the drug discovery. The biological process is a cycled network, and the membrane protein is a vital hub in the network since most drugs achieve the therapeutic effect via interacting with the membrane protein. In this review, typical membrane protein targets are described, including GPCRs, transporters and ion channels. Also, we conclude network servers and databases that are referring to the drug, drug-target information and their relevant data. Furthermore, we chiefly introduce the development and practice of modern medicines, particularly demonstrating a series of state-of-the-art computational models for the prediction of drug-target interaction containing network-based approach and machine-learningbased approach as well as showing current achievements. Finally, we discuss the prospective orientation of drug repurposing and drug discovery as well as propose some improved framework in bioactivity data, created or improved predicted approaches, alternative understanding approaches of drugs bioactivity and their biological processes.
膜蛋白在体内发挥着至关重要的生理作用，是药物的主要靶点类别。对膜蛋白的研究是药物发现的重要组成部分。生物过程是一个循环网络，而膜蛋白是网络中的重要枢纽，因为大多数药物通过与膜蛋白相互作用来达到治疗效果。在这篇综述中，描述了典型的膜蛋白靶点，包括 GPCRs、转运体和离子通道。此外，我们还总结了涉及药物、药物靶点信息及其相关数据的网络服务器和数据库。此外，我们主要介绍了现代药物的发展和实践，特别是展示了一系列用于预测药物-靶点相互作用的最先进的计算模型，包括基于网络的方法和基于机器学习的方法，并展示了当前的成果。最后，我们讨论了药物重定位和药物发现的前瞻性方向，并提出了一些改进的生物活性数据框架、创建或改进的预测方法、药物生物活性及其生物过程的替代理解方法。
