Engin H Billur, Gursoy Attila, Nussinov Ruth, Keskin Ozlem
Center for Computational Biology and Bioinformatics and College of Engineering, Koc University, Rumelifeneri Yolu, 34450 Sariyer Istanbul, Turkey.
Curr Pharm Des. 2014;20(8):1201-7. doi: 10.2174/13816128113199990066.
The cellular network and its environment govern cell and organism behavior and are fundamental to the comprehension of function, misfunction and drug discovery. Over the last few years, drugs were observed to often bind to more than one target; thus, polypharmacology approaches can be advantageous, complementing the "one drug--one target" strategy. Targeting drug discovery from the systems biology standpoint can help in studies of network effects of mono- and poly-pharmacology. In this mini-review, we provide an overview of the usefulness of network description and tools for mono- and poly-pharmacology, and the ways through which protein interactions can help single- and multi-target drug discovery efforts. We further describe how, when combined with experimental data, modeled structural networks which can predict which proteins interact and provide the structures of their interfaces, can model the cellular pathways, and suggest which specific pathways are likely to be affected. Such structural networks may facilitate structure-based drug design; forecast side effects of drugs; and suggest how the effects of drug binding can propagate in multi-molecular complexes and pathways.
细胞网络及其环境决定细胞和生物体的行为,对于理解功能、功能失调及药物发现至关重要。在过去几年中,人们观察到药物常常会与不止一个靶点结合;因此,多药理学方法可能具有优势,可补充“一种药物——一个靶点”的策略。从系统生物学角度进行药物发现研究,有助于对单药理学和多药理学的网络效应展开研究。在本综述中,我们概述了网络描述和工具对单药理学和多药理学的作用,以及蛋白质相互作用有助于单靶点和多靶点药物发现的方式。我们还进一步描述了,当与实验数据相结合时,能够预测哪些蛋白质相互作用并提供其界面结构的建模结构网络,如何能够对细胞途径进行建模,并指出哪些特定途径可能会受到影响。此类结构网络可能有助于基于结构的药物设计;预测药物的副作用;并提示药物结合的效应如何在多分子复合物和途径中传播。