Laufer Center for Physical & Quantitative Biology, Department of Biochemistry and Cell Biology, School of Medicine, Stony Brook University, NY 11794, USA.
Laufer Center for Physical & Quantitative Biology, Department of Pharmacological Sciences, School of Medicine, Stony Brook University, NY 11794, USA.
Curr Opin Struct Biol. 2024 Feb;84:102770. doi: 10.1016/j.sbi.2023.102770. Epub 2024 Jan 11.
The eukaryotic protein kinase domain has been a broadly explored target for drug discovery, despite limitations imposed by its high sequence conservation as a shared modular domain and the development of resistance to drugs. One way of addressing those limitations has been to target its potential allosteric sites, shortly called allo-targeting, in conjunction with, or separately from, its conserved catalytic/orthosteric site that has been widely exploited. Allosteric regulation has gained importance as an alternative to overcome the drawbacks associated with the indiscriminate effect of targeting the active site, and it turned out to be particularly useful for these highly promiscuous and broadly shared kinase domains. Yet, allo-targeting often faces challenges as the allosteric sites are not as clearly defined as its orthosteric sites, and the effect on the protein function may not be unambiguously assessed. A robust understanding of the consequence of site-specific allo-targeting on the conformational dynamics of the target protein is essential to design effective allo-targeting strategies. Recent years have seen important advances in in silico identification of druggable sites and distinguishing among them those sites expected to allosterically mediate conformational switches essential to signal transmission. The present opinion underscores the utility of such computational approaches applied to the kinase domain, with the help of comparison between computational predictions and experimental observations.
真核蛋白激酶结构域一直是药物发现的广泛探索靶点,尽管其作为共享模块域的高序列保守性以及对药物产生耐药性带来了限制。解决这些限制的一种方法是靶向其潜在的变构结合位点,简称变构靶向,与广泛利用的保守催化/正位结合位点结合或分开。变构调节作为克服靶向活性位点相关缺点的替代方法变得越来越重要,对于这些高度混杂和广泛共享的激酶结构域尤其有用。然而,变构靶向常常面临挑战,因为变构结合位点不如其正位结合位点那样明确,并且对蛋白质功能的影响可能无法明确评估。深入了解特定部位的变构靶向对靶蛋白构象动力学的影响,对于设计有效的变构靶向策略至关重要。近年来,在计算上识别可成药的变构结合位点并区分那些有望变构介导对信号转导至关重要的构象开关的变构结合位点方面取得了重要进展。本观点强调了在激酶结构域中应用此类计算方法的实用性,通过计算预测与实验观察之间的比较来实现。