Agić Dejan, Karnaš Maja, Tomić Sanja, Komar Mario, Karačić Zrinka, Rastija Vesna, Bešlo Drago, Šubarić Domagoj, Molnar Maja
Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia.
Divison of Organic Chemistry and Biochemistry, Ruđer Bošković Institute, Zagreb, Croatia.
J Biomol Struct Dyn. 2023 Sep-Oct;41(16):7567-7581. doi: 10.1080/07391102.2022.2123044. Epub 2022 Sep 15.
Dipeptidyl peptidase III (DPP III) is a zinc-dependent enzyme that sequentially hydrolyzes biologically active peptides by cleaving dipeptides from their N-termini. Although its fundamental role is not been fully elucidated, human DPP III (hDPP III) has been recognized in several pathophysiological processes of interest for drug development. In this article 27 quinazolinone-Schiff's bases were studied for their inhibitory activity against hDPP III combining an in vitro experiment with a computational approach. The biochemical assay showed that most compounds exhibited inhibitory activity at the 100 μM concentration. The best QSAR model included descriptors from the following 2D descriptor groups: information content indices, 2D autocorrelations, and edge adjacency indices. Five compounds were found to be the most potent inhibitors with IC values below 10 µM, while molecular docking predicted that these compounds bind to the central enzyme cleft and interact with residues of the substrate binding subsites. Molecular dynamics simulations of the most potent inhibitor (IC=0.96 µM) provided valuable information explaining the role of PHE109, ARG319, GLU327, GLU329, and ILE386 in the mechanism of the inhibitor binding and stabilization. This is the first study that gives insight into quinazolinone-Schiff's bases binding to this metalloenzyme.Communicated by Ramaswamy H. Sarma.
二肽基肽酶III(DPP III)是一种锌依赖性酶,通过从生物活性肽的N端切割二肽来依次水解这些肽。尽管其基本作用尚未完全阐明,但人DPP III(hDPP III)已在药物开发感兴趣的几个病理生理过程中得到确认。在本文中,结合体外实验和计算方法,研究了27种喹唑啉酮-席夫碱对hDPP III的抑制活性。生化分析表明,大多数化合物在100μM浓度下表现出抑制活性。最佳的定量构效关系(QSAR)模型包括来自以下二维描述符组的描述符:信息含量指数、二维自相关和边缘邻接指数。发现有五种化合物是最有效的抑制剂,其半数抑制浓度(IC)值低于10μM,而分子对接预测这些化合物与酶的中心裂隙结合,并与底物结合亚位点的残基相互作用。对最有效的抑制剂(IC = 0.96μM)进行分子动力学模拟,提供了有价值的信息,解释了苯丙氨酸109、精氨酸319、谷氨酸327、谷氨酸329和异亮氨酸386在抑制剂结合和稳定机制中的作用。这是第一项深入研究喹唑啉酮-席夫碱与这种金属酶结合的研究。由拉马斯瓦米·H·萨尔马传达。