Kuzu Guray, Keskin Ozlem, Gursoy Attila, Nussinov Ruth
Center for Computational Biology and Bioinformatics and College of Engineering, Koc University Rumelifeneri Yolu, Istanbul, Turkey.
Methods Mol Biol. 2012;819:59-74. doi: 10.1007/978-1-61779-465-0_5.
Conformational selection emerges as a theme in macromolecular interactions. Data validate it as a prevailing mechanism in protein-protein, protein-DNA, protein-RNA, and protein-small molecule drug recognition. This raises the question of whether this fundamental biomolecular binding mechanism can be used to improve drug docking and discovery. Actually, in practice this has already been taking place for some years in increasing numbers. Essentially, it argues for using not a single conformer, but an ensemble. The paradigm of conformational selection holds that because the ensemble is heterogeneous, within it there will be states whose conformation matches that of the ligand. Even if the population of this state is low, since it is favorable for binding the ligand, it will bind to it with a subsequent population shift toward this conformer. Here we suggest expanding it by first modeling all protein interactions in the cell by using Prism, an efficient motif-based protein-protein interaction modeling strategy, followed by ensemble generation. Such a strategy could be particularly useful for signaling proteins, which are major targets in drug discovery and bind multiple partners through a shared binding site, each with some-minor or major-conformational change.
构象选择成为大分子相互作用中的一个主题。数据证实它是蛋白质-蛋白质、蛋白质-DNA、蛋白质-RNA和蛋白质-小分子药物识别中的一种普遍机制。这就提出了一个问题,即这种基本的生物分子结合机制是否可用于改进药物对接和发现。实际上,在实践中,这种情况已经存在了数年,而且越来越多。从本质上讲,它主张使用的不是单一构象体,而是一个集合。构象选择的范式认为,由于集合是异质的,其中会存在构象与配体匹配的状态。即使这种状态的数量很少,由于它有利于与配体结合,它将与配体结合,随后群体向这种构象体转移。在这里,我们建议通过首先使用Prism(一种基于基序的高效蛋白质-蛋白质相互作用建模策略)对细胞中的所有蛋白质相互作用进行建模,然后生成集合来扩展它。这样的策略对于信号蛋白可能特别有用,信号蛋白是药物发现中的主要靶点,通过一个共享的结合位点与多个伙伴结合,每个伙伴都有一些——小的或大的——构象变化。