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Molecular engineering and activity improvement of acetylcholinesterase inhibitors: Insights from 3D-QSAR, docking, and molecular dynamics simulation studies. J Mol Graph Model 2022; 116:108239. [PMID: 35696774 DOI: 10.1016/j.jmgm.2022.108239] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 05/10/2022] [Accepted: 05/27/2022] [Indexed: 12/14/2022]
Abstract
The carbamate molecule rivastigmine was found to possess promising anti-acetylcholinesterase activity, enabling to target and occupy choline binding sites, and as a result, widely used to improve the treatment of Alzheimer's disease (AD). Higher dose of rivastigmine indicates rapid onset but more adverse effects, such as the large fluctuations in plasma concentration level and frequent incidence of gastrointestinal side effect. To solve the dilemma, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR), docking and molecular dynamics (MD) simulation strategy to construct a dismountable nanoplatform of inhibitor engineering, verification and application for improving the inhibitory activity per unit concentration. With the aid of 3D-QSAR method, we constructed a model by using 25 molecules reported, and verified well the rationality of these QSAR models by non-cross validation coefficient (r2 = 0.902). Docking and MD results show that rivastigmine, as a control, does target exactly the binding sites of acetylcholinesterase, those already observed experimentally, in turn, confirming the reliability of the present 3D-QSAR results. The method suggests that groups with electron-donating chemical property can improve the inhibitory activity, and screens out two novel inhibitors L-1 and L-2 with more activity from database (about 8000 compounds). Moreover, L-1 and L-2 not only target exactly the same binding sites of acetylcholinesterase as the rivastigmine does, but also hold stronger binding energy, showing a more powerful inhibitory ability. More broadly, this work showcases an approach in the engineering of carbamate inhibitors to enhance their inhibitory activity using electron-donating groups, which simplifies the design process of complex bioactive molecules.
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Precise Hapten Design of Sulfonamides by Combining Machine Learning and 3D-QSAR Approaches. FOOD ANAL METHOD 2022. [DOI: 10.1007/s12161-021-02179-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Tong J, Jiang G, Li L, Li Y. Molecular Docking and 3D QSAR Research of Indolocarbazole Series as Cyclin-Dependent Kinase Inhibitors. J STRUCT CHEM+ 2018. [DOI: 10.1134/s0022476618070065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Feng Y, Teng X, Gu J, Yu B, Luo Y, Ye L. Novel anti-cancer agents: design, synthesis, biological activity, molecular docking, and MD simulations of 2, 3, 4, 5-tetrahydro-1H-pyrido-[4,3-b]indole derivatives. Med Chem Res 2018. [DOI: 10.1007/s00044-018-2271-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Niu B, Lu Y, Wang J, Hu Y, Chen J, Chen Q, He G, Zheng L. 2D-SAR, Topomer CoMFA and molecular docking studies on avian influenza neuraminidase inhibitors. Comput Struct Biotechnol J 2018; 17:39-48. [PMID: 30595814 PMCID: PMC6305694 DOI: 10.1016/j.csbj.2018.11.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 11/15/2018] [Accepted: 11/23/2018] [Indexed: 12/18/2022] Open
Abstract
Avian influenza is a serious zoonotic infectious disease with huge negative impacts on local poultry farming, human health and social stability. Therefore, the design of new compounds against avian influenza has been the focus in this field. In this study, computational methods were applied to investigate the compounds with neuraminidase inhibitory activity. First, 2D-SAR model was built to recognize neuraminidase inhibitors (NAIs). As a result, the accuracy of 10 cross-validation and independent tests is 96.84% and 98.97%, respectively. Then, the Topomer CoMFA model was constructed to predict the inhibitory activity and analyses molecular fields. Two models were obtained by changing the cutting methods. The second model is employed to predict the activity (q2 = 0.784 and r2 = 0.982). Molecular docking was also used to further analyze the binding sites between NAIs and neuraminidase from human and avian virus. As a result, it is found that same binding Total Score has some differences, but the binding sites are basically the same. At last, some potential NAIs were screened and some optimal opinions were taken. It is expected that our study can assist to study and develop new types of NAIs.
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Affiliation(s)
- Bing Niu
- School of Life Sciences, Shanghai University, Shanghai 200444, China
| | - Yi Lu
- School of Life Sciences, Shanghai University, Shanghai 200444, China
| | - Jianying Wang
- School of Life Sciences, Shanghai University, Shanghai 200444, China
| | - Yan Hu
- School of Life Sciences, Shanghai University, Shanghai 200444, China
| | - Jiahui Chen
- School of Life Sciences, Shanghai University, Shanghai 200444, China
| | - Qin Chen
- School of Life Sciences, Shanghai University, Shanghai 200444, China
| | - Guangwu He
- Department of Radiology, Shanghai First People's Hospital, Baoshan Branch, Shanghai 200940, China
| | - Linfeng Zheng
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- Department of Radiology, Shanghai First People's Hospital, Baoshan Branch, Shanghai 200940, China
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Han D, Tan J, Zhou Z, Li C, Zhang X, Wang C. Combined topomer CoMFA and hologram QSAR studies of a series of pyrrole derivatives as potential HIV fusion inhibitors. Med Chem Res 2018. [DOI: 10.1007/s00044-018-2190-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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Abstract
Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98.99% by using tenfold cross-validation test and 97.67% by using independent set test. Then, in the 3D-QSAR model, the model with q2 = 0.565 (cross-validated correlation coefficient) and r2 = 0.888 (non-cross-validated correlation coefficient) was built to predict the activity of EGFR inhibitors. The mean absolute error (MAE) of the training set and test set was 0.308 log units and 0.526 log units, respectively. In addition, molecular docking was also employed to investigate the interaction between EGFR inhibitors and EGFR.
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Niu B, Zhao M, Su Q, Zhang M, Lv W, Chen Q, Chen F, Chu D, Du D, Zhang Y. 2D-SAR and 3D-QSAR analyses for acetylcholinesterase inhibitors. Mol Divers 2017; 21:413-426. [PMID: 28275924 DOI: 10.1007/s11030-017-9732-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2016] [Accepted: 02/20/2017] [Indexed: 12/12/2022]
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 [Formula: see text] (cross-validated correlation coefficient) and [Formula: see text](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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Affiliation(s)
- Bing Niu
- Shanghai Key Laboratory of Bio-Energy Crops, College of Life Science, Shanghai University, Shanghai, 200444, People's Republic of China.
| | - Manman Zhao
- Shanghai Key Laboratory of Bio-Energy Crops, College of Life Science, Shanghai University, Shanghai, 200444, People's Republic of China
| | - Qiang Su
- Shanghai Key Laboratory of Bio-Energy Crops, College of Life Science, Shanghai University, Shanghai, 200444, People's Republic of China
| | - Mengying Zhang
- Shanghai Key Laboratory of Bio-Energy Crops, College of Life Science, Shanghai University, Shanghai, 200444, People's Republic of China
| | - Wei Lv
- School of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai, 200444, People's Republic of China
| | - Qin Chen
- Shanghai Key Laboratory of Bio-Energy Crops, College of Life Science, Shanghai University, Shanghai, 200444, People's Republic of China
| | - Fuxue Chen
- Shanghai Key Laboratory of Bio-Energy Crops, College of Life Science, Shanghai University, Shanghai, 200444, People's Republic of China
| | - Dechang Chu
- Department of Life Science, Heze University, Heze, Shandong, 274500, People's Republic of China
| | - Dongshu Du
- Shanghai Key Laboratory of Bio-Energy Crops, College of Life Science, Shanghai University, Shanghai, 200444, People's Republic of China.
- Department of Life Science, Heze University, Heze, Shandong, 274500, People's Republic of China.
| | - Yuhui Zhang
- Changhai Hospital, Second Military Medical University, Shanghai, 200433, People's Republic of China.
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CoMFA and CoMSIA studies on 6,7-disubstituted-4-phenoxyquinoline derivatives as c-Met kinase inhibitors and anticancer agents. Med Chem Res 2015. [DOI: 10.1007/s00044-015-1450-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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