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2D-SAR and 3D-QSAR analyses for acetylcholinesterase inhibitors

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Abstract

Alzheimer’s disease (AD) accounts for almost three quarters of dementia patients and interferes people’s normal life. Great progress has been made recently in the study of Acetylcholinesterase (AChE), known as one of AD’s biomarkers. In this study, acetylcholinesterase inhibitors (AChEI) were collected to build a two-dimensional structure–activity relationship (2D-SAR) model and three-dimensional quantitative structure–activity relationship (3D-QSAR) model based on feature selection method combined with random forest. After calculation, the prediction accuracy of the 2D-SAR model was 89.63% by using the tenfold cross-validation test and 87.27% for the independent test set. Three cutting ways were employed to build 3D-QSAR models. A model with the highest \({q}^{2}\) (cross-validated correlation coefficient) and \({r}^{2 }\)(non-cross-validated correlation coefficient) was obtained to predict AChEI activity. The mean absolute error (MAE) of the training set and the test set was 0.0689 and 0.5273, respectively. In addition, molecular docking was also employed to reveal that the ionization state of the compounds had an impact upon their interaction with AChE. Molecular docking results indicate that Ser124 might be one of the active site residues.

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Acknowledgements

The author would like to thank scholarship from Shanghai Municipal Education Commission, the National Natural Science Foundation of China (81271384, 81371623, 31571171 and 31100838, Shanghai Key Laboratory of Bio-energy Crops (13DZ2272100), the Shanghai Natural Science Foundation (Grant No. 15ZR1414900), the Key Laboratory of Medical Electrophysiology (Southwest Medical University) of Ministry of Education of China (Grant No. 201502), and the Young Teachers of Shanghai Universities Training Program. We also would like to thank Mingyue Zheng Professor from the State Key Laboratory of Drug Research of Chinese Academy of Sciences for helping compute the ionization of the compounds at physiological pH 7.4.

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    1. Shanghai Key Laboratory of Bio-Energy Crops, College of Life Science, Shanghai University, Shanghai, 200444, People’s Republic of China

      Bing Niu, Manman Zhao, Qiang Su, Mengying Zhang, Qin Chen, Fuxue Chen & Dongshu Du

    2. School of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai, 200444, People’s Republic of China

      Wei Lv

    3. Department of Life Science, Heze University, Heze, Shandong, 274500, People’s Republic of China

      Dechang Chu & Dongshu Du

    4. Changhai Hospital, Second Military Medical University, Shanghai, 200433, People’s Republic of China

      Yuhui Zhang

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    Niu, B., Zhao, M., Su, Q. et al. 2D-SAR and 3D-QSAR analyses for acetylcholinesterase inhibitors. Mol Divers 21, 413–426 (2017). https://doi.org/10.1007/s11030-017-9732-0

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