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疟原虫氨肽酶的结构特征:基于分子对接和定量构效关系的联合计算方法。

Structural characterization of plasmodial aminopeptidase: a combined molecular docking and QSAR-based in silico approaches.

机构信息

School of Life Science, Linyi University, Linyi, 276000, China.

State Key Laboratory of Functions and Applications of Medicinal Plants, College of Basic Medical, Guizhou Medical University, Guiyang, 550004, Guizhou, China.

出版信息

Mol Divers. 2019 Nov;23(4):965-984. doi: 10.1007/s11030-019-09921-y. Epub 2019 Feb 7.

Abstract

Aminopeptidase M1 (PfAM1) is one of the key enzymes involved in the development of new antimalarials. To accelerate the discovery of inhibitors with selective activity against PfAM1 and microsomal neutral aminopeptidase (pAPN), in the present work, the optimum comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were built based on PfAM1 and pAPN inhibitors. The results of the developed 3D-QSAR models were as follows: PfAM1/CoMFA: [Formula: see text] = 0.740, [Formula: see text] = 0.7781; PfAM1/CoMSIA: [Formula: see text] = 0.740, [Formula: see text] = 0.7354; pAPN/CoMFA: [Formula: see text] = 0.612, [Formula: see text] = 0.7318; pAPN/CoMSIA: [Formula: see text] = 0.609, [Formula: see text] = 0.7480, and the models derived from MLR, PLSR and SVR methods provided high R values of 0.6960, 0.6965, 0.7971 for PfAM1, 0.7700, 0.7697, 0.8228 for pAPN and Q of 0.7004, 0.7004, 0.5632 for PfAM1, 0.7551, 0.7566 and 0.8394 for pAPN, respectively, indicating that the developed 3D-QSAR and 2D-QSAR models possess good ability for prediction of the relative compound activities. Furthermore, all inhibitors were docked into the active site of the PfAM1 and pAPN receptors, the hydrogen-bond interactions between the compound 33 with Glu497, Glu463 and Arg489 of the PfAM1, and the compound 4 with Ala348, Glu384 and Phe467 of the receptor pAPN are able to help to stabilize the conformation. The above results would provide helpful clues to predicting the binding activity of novel inhibitors and the foundation for understanding the interaction mechanism between the inhibitors and the receptors.

摘要

氨肽酶 M1(PfAM1)是参与开发新型抗疟药物的关键酶之一。为了加速对具有针对 PfAM1 和微粒体中性氨肽酶(pAPN)选择性活性的抑制剂的发现,在本工作中,基于 PfAM1 和 pAPN 抑制剂构建了最佳的比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)模型。所开发的 3D-QSAR 模型的结果如下:PfAM1/CoMFA:[公式:见文本]=0.740,[公式:见文本]=0.7781;PfAM1/CoMSIA:[公式:见文本]=0.740,[公式:见文本]=0.7354;pAPN/CoMFA:[公式:见文本]=0.612,[公式:见文本]=0.7318;pAPN/CoMSIA:[公式:见文本]=0.609,[公式:见文本]=0.7480,并且源自 MLR、PLSR 和 SVR 方法的模型为 PfAM1 提供了 0.6960、0.6965、0.7971 的高 R 值,为 pAPN 提供了 0.7700、0.7697、0.8228 的 R 值,为 PfAM1 提供了 0.7004、0.7004、0.5632 的 Q 值,为 pAPN 提供了 0.7551、0.7566 和 0.8394 的 Q 值,表明所开发的 3D-QSAR 和 2D-QSAR 模型具有良好的相对化合物活性预测能力。此外,所有抑制剂都对接入 PfAM1 和 pAPN 受体的活性部位,化合物 33 与 PfAM1 的 Glu497、Glu463 和 Arg489 之间的氢键相互作用,以及化合物 4 与受体 pAPN 的 Ala348、Glu384 和 Phe467 之间的氢键相互作用能够帮助稳定构象。上述结果将为预测新型抑制剂的结合活性提供有价值的线索,并为理解抑制剂与受体之间的相互作用机制奠定基础。

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