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新型腙衍生物作为 α-淀粉酶抑制剂的定量构效关系研究及相关理想指数。

Quantitative structure activity relationship studies of novel hydrazone derivatives as α-amylase inhibitors with index of ideality of correlation.

机构信息

Department of Chemistry, Kurukshetra University, Kurukshetra, India.

Department of Chemistry, COBS&H, CCS Haryana Agricultural University, Hisar, India.

出版信息

J Biomol Struct Dyn. 2022 Jul;40(11):4933-4953. doi: 10.1080/07391102.2020.1863861. Epub 2020 Dec 24.

Abstract

The present manuscript describes the synthesis, -amylase inhibition, studies and in-depth quantitative structure-activity relationship (QSAR) of a library of aroyl hydrazones based on benzothiazole skeleton. All the compounds of the developed library are characterized by various spectral techniques. -Amylase inhibitory potential of all compounds has been explored, where compound exhibits remarkable -amylase inhibition of 87.5% at 50 µg/mL. Robust QSAR models are made by using the balance of correlation method in CORAL software. The chemical structures at different concentration with optimal descriptors are represented by SMILES. A data set of 66 SMILES of 22 hydrazones at three distinct concentrations are prepared. The significance of the index of ideality of correlation (IIC) with applicability domain (AD) is also studied at depth. A QSAR model with best  = 0.8587 for split 1 is considered as a leading model. The outliers and promoters of increase and decrease of endpoint are also extracted. The binding modes of the most active compound, that is, in the active site of α-amylase () are also explored by molecular docking studies. Compound displays high resemblance in binding mode and pose with the standard drug acarbose. Molecular dynamics simulations performed on protein-ligand complex for 100 ns, the protein gets stabilised after 20 ns and remained below 2 Å for the remaining simulation. Moreover, the deviation observed in RMSF during simulation for each amino acid residue with respect to Cα carbon atom is insignificant.

摘要

本手稿描述了基于苯并噻唑骨架的芳酰腙的合成、-淀粉酶抑制、研究和深入的定量构效关系(QSAR)。所开发库中的所有化合物均通过各种光谱技术进行了表征。对所有化合物的 -淀粉酶抑制潜力进行了探索,其中化合物在 50μg/mL 时表现出显著的 -淀粉酶抑制作用,抑制率为 87.5%。使用 CORAL 软件中的平衡相关法建立了稳健的 QSAR 模型。使用 SMILES 代表不同浓度下的化学结构和最佳描述符。准备了一组 66 个 SMILES 的 22 个腙,在三个不同浓度下。还深入研究了相关指数理想性 (IIC) 与适用性域 (AD) 的显著性。具有最佳 split 1  = 0.8587 的 QSAR 模型被认为是主导模型。还提取了端点增加和减少的异常值和促进剂。通过分子对接研究还探索了最活性化合物,即,在 α-淀粉酶 ()的活性部位的结合模式。化合物在结合模式和构象上与标准药物阿卡波糖高度相似。对蛋白-配体复合物进行了 100ns 的分子动力学模拟,在 20ns 后蛋白得到稳定,并且在剩余的模拟中保持在 2Å 以下。此外,在模拟过程中每个氨基酸残基相对于 Cα碳原子的 RMSF 观察到的偏差不显著。

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