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杂合描述符-联合指数:含咪唑硫脲的谷氨酰环化酶抑制剂用于设计新型抗阿尔茨海默病候选物的案例研究。

Hybrid descriptors-conjoint indices: a case study on imidazole-thiourea containing glutaminyl cyclase inhibitors for design of novel anti-Alzheimer's candidates.

机构信息

Department of Pharmaceutical Sciences, Guru Jambheshwar University of Science & Technology, Hisar, India.

Department of Chemistry, Kurukshetra University, Kurukshetra, India.

出版信息

SAR QSAR Environ Res. 2023 May;34(5):361-381. doi: 10.1080/1062936X.2023.2212175.

Abstract

Clinical studies show that the pyroglutamate alteration of amyloid-β (Aβ) catalysed by metalloenzyme glutaminyl cyclase results in the formation of the more neurotoxic pGlu-Aβ, and inhibition of glutaminyl cyclase can bring down the load of pGlu-Aβ in the brain and reduces Alzheimer's disease pathology with improvement in cognition. The present study involves the identification of activity-modulating structural features of 188 inhibitors of glutaminyl cyclase under the influence of index of ideality of correlation (IIC) and correlation intensity index (CII) as prediction parameters. The QSAR models developed employing IIC and CII were found to be statistically better and had better predictability than the models developed without them. The best model (split 4) showed values of 0.8155 and 0.8218 for calibration and validation sets, respectively. The structural features classified from QSAR models were used to design some new glutaminyl cyclase inhibitors. Among the designed ligands, ligand 5 possesses the highest pIC value (6.30) as well as binding affinity (-6.2 kcal/mol) and creates hydrogen bonds with TRP 329, π-alkyl interactions with ILE 303 and TYR 299, π-π stacking interaction with PHE 325 and interactions with ZN 391. All novel designed ligands have better pIC values and binding affinities.

摘要

临床研究表明,金属酶谷氨酰胺环化酶催化的淀粉样蛋白-β(Aβ)焦谷氨酸化导致更具神经毒性的 pGlu-Aβ的形成,而抑制谷氨酰胺环化酶可以降低大脑中 pGlu-Aβ的负荷,并通过改善认知来减少阿尔茨海默病的病理。本研究涉及在相关理想指数(IIC)和相关强度指数(CII)的影响下,鉴定 188 种谷氨酰胺环化酶抑制剂的活性调节结构特征,作为预测参数。采用 IIC 和 CII 开发的 QSAR 模型被发现比没有这些模型的模型在统计学上更好,具有更好的可预测性。最佳模型(分割 4)分别显示出 0.8155 和 0.8218 的校准和验证集 值。从 QSAR 模型分类的结构特征被用于设计一些新的谷氨酰胺环化酶抑制剂。在所设计的配体中,配体 5 具有最高的 pIC 值(6.30)以及结合亲和力(-6.2 kcal/mol),并与 TRP 329 形成氢键,与 ILE 303 和 TYR 299 形成 π-烷基相互作用,与 PHE 325 形成 π-π 堆积相互作用,与 ZN 391 相互作用。所有新设计的配体都具有更好的 pIC 值和结合亲和力。

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