scholarly journals Studies on molecular mechanism between SHP2 and pyridine derivatives by 3D-QSAR, molecular docking and MD simulations

2021 ◽  
pp. 101346
Author(s):  
Fangfang Wang ◽  
Wei Yang ◽  
Zhonglin Li ◽  
Bo Zhou
2020 ◽  
Vol 304 ◽  
pp. 112702 ◽  
Author(s):  
Wenli Yan ◽  
Guimei Lin ◽  
Rong Zhang ◽  
Zhen Liang ◽  
Lixian Wu ◽  
...  

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuwei Wang ◽  
Yifan Guo ◽  
Shaojia Qiang ◽  
Ruyi Jin ◽  
Zhi Li ◽  
...  

PGAM1 is overexpressed in a wide range of cancers, thereby promoting cancer cell proliferation and tumor growth, so it is gradually becoming an attractive target. Recently, a series of inhibitors with various structures targeting PGAM1 have been reported, particularly anthraquinone derivatives. In present study, the structure–activity relationships and binding mode of a series of anthraquinone derivatives were probed using three-dimensional quantitative structure–activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, r2 = 0.97, q2 = 0.81) and comparative molecular similarity indices analysis (CoMSIA, r2 = 0.96, q2 = 0.82) techniques were performed to produce 3D-QSAR models, which demonstrated satisfactory results, especially for the good predictive abilities. In addition, molecular dynamics (MD) simulations technology was employed to understand the key residues and the dominated interaction between PGAM1 and inhibitors. The decomposition of binding free energy indicated that the residues of F22, K100, V112, W115, and R116 play a vital role during the ligand binding process. The hydrogen bond analysis showed that R90, W115, and R116 form stable hydrogen bonds with PGAM1 inhibitors. Based on the above results, 7 anthraquinone compounds were designed and exhibited the expected predictive activity. The study explored the structure–activity relationships of anthraquinone compounds through 3D-QSAR and molecular dynamics simulations and provided theoretical guidance for the rational design of new anthraquinone derivatives as PGAM1 inhibitors.


2020 ◽  
Vol 11 (4) ◽  
pp. 3043-3052 ◽  
Author(s):  
Wenli Yan ◽  
Guimei Lin ◽  
Rong Zhang ◽  
Zhen Liang ◽  
Wenjuan Wu

The bioactivities and molecular mechanism of two novel antioxidant peptides were investigated by 3D-QSAR, in vitro evaluation and MD simulations.


Molecules ◽  
2018 ◽  
Vol 23 (11) ◽  
pp. 2924 ◽  
Author(s):  
Gaomin Zhang ◽  
Yujie Ren

Cyclin-dependent kinase 2 (CDK2) is a potential target for treating cancer. Purine heterocycles have attracted particular attention as the scaffolds for the development of CDK2 inhibitors. To explore the interaction mechanism and the structure–activity relationship (SAR) and to design novel candidate compounds as potential CDK2 inhibitors, a systematic molecular modeling study was conducted on 35 purine derivatives as CDK2 inhibitors by combining three-dimensional quantitative SAR (3D-QSAR), virtual screening, molecular docking, and molecular dynamics (MD) simulations. The predictive CoMFA model (q2 = 0.743, r pred 2 = 0.991), the CoMSIA model (q2 = 0.808, r pred 2 = 0.990), and the Topomer CoMFA model (q2 = 0.779, r pred 2 = 0.962) were obtained. Contour maps revealed that the electrostatic, hydrophobic, hydrogen bond donor and steric fields played key roles in the QSAR models. Thirty-one novel candidate compounds with suitable predicted activity (predicted pIC50 > 8) were designed by using the results of virtual screening. Molecular docking indicated that residues Asp86, Glu81, Leu83, Lys89, Lys33, and Gln131 formed hydrogen bonds with the ligand, which affected activity of the ligand. Based on the QSAR model prediction and molecular docking, two candidate compounds, I13 and I60 (predicted pIC50 > 8, docking score > 10), with the most potential research value were further screened out. MD simulations of the corresponding complexes of these two candidate compounds further verified their stability. This study provided valuable information for the development of new potential CDK2 inhibitors.


Oncotarget ◽  
2017 ◽  
Vol 8 (15) ◽  
pp. 25612-25627 ◽  
Author(s):  
Jun Zhang ◽  
Qing-Qing Hao ◽  
Xin Liu ◽  
Zhi Jing ◽  
Wen-Qing Jia ◽  
...  

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