作为新型乙酰胆碱酯酶抑制剂的吡咯基肼基肼酮的硅学和体外筛选

E. Mateev, Ali Irfan, Alexandrina Mateeva, M. Kondeva-Burdina, Maya Georgieva, A. Zlatkov
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引用次数: 0

摘要

虚拟筛选正在成为一种高度应用的技术,并作为一种广泛使用的方法在搜索和识别潜在化合物方面获得了显著地位,与高通量筛选相比,它大大缩短了发现新型有效化合物所需的时间。最近,人们讨论了与单个软件对接相比,使用多个程序进行模拟的优越性。这项工作的目的是在寻找新型乙酰胆碱酯酶(AChE)抑制剂的过程中,应用共识对接、分子力学/广义伯恩表面积(MM/GBSA)自由结合能重新计算和体外评估等方法,对最近合成的吡咯基酰肼数据集进行研究。虚拟筛选采用了两个授权软件--GOLD 5.3 和 Glide,并确定了几个潜在的化疗药物。此外,还对 MM/GBSA 自由结合能进行了重新计算,以提高硅学结果的稳健性。排名前十的吡咯基酰肼的 MM/GBSA 分数介于 -60.44 至 -70.93 Kcal/mol 之间。随后,对排名靠前的化合物进行体外评估发现,12d 表现出最高的 AChE 抑制活性,在 10 μM 的浓度下抑制率为 55%。此外,这种突出的吡咯型 AChE 抑制剂与酶的活性位点形成了稳定的复合物。与活性氨基残基 Tyr72 和 Tyr286 的相互作用表明,12d 位于酶的外周阴离子位点附近。此外,利用 QikProp 进行的硅烷化药代动力学研究表明,12d 具有最佳的药代动力学特性。总之,本研究通过计算和实验结果的结合,发现了一种基于吡咯的新型 AChE 抑制剂 12d。
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In silico and in vitro screening of pyrrole-based Hydrazide-Hydrazones as novel acetylcholinesterase inhibitors
Virtual screening is emerging as a highly applied technique and gained prominence as widely used method for the search and identification of potential hits, significantly reducing the time needed to discover novel and effective compounds compared to high-throughput screening. Recently, the superiority of simulations with multiple programs compared to a single software docking has been discussed. The aim of this work was to apply consensus docking, molecular mechanics/generalized Born surface area (MM/GBSA) free binding energy recalculations, and in vitro evaluations on an in-house dataset of recently synthesized pyrrole-based hydrazide-hydrazones in the search for novel acetylcholinesterase (AChE) inhibitors. Two licensed softwares – GOLD 5.3 and Glide, were employed for the virtual screenings, and several chemotherapeutic potential hits were identified. Furthermore, MM/GBSA free binding energy recalculations were provided to enhance the robustness of the in silico results. The MM/GBSA scores of the top ten pyrrole-based hydrazide-hydrazones were ranging from -60.44 to -70.93 Kcal/mol. Subsequent, in vitro evaluations of the top ranked compounds revealed that 12d exhibited the highest AChE inhibitory activity, with a 55% inhibition rate at a concentration of 10 μM. Moreover, this prominent pyrrole-based AChE inhibitor formed stable complex with the active site of the enzyme. Interactions with the active amino residues Tyr72 and Tyr286 indicated that 12d was located near the peripheral anionic site of the enzyme. Additionally, in silicoADME investigations using QikProp demonstrated that 12d possesses optimal pharmacokinetic properties. In conclusion, this study identified a novel pyrrole-based AChE inhibitor 12d through a combination of computational and experimental findings.
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