Identification of potential quinoxalinone-based aldose reductase inhibitors by 3D-QSAR, molecular docking and molecular dynamics

RSC Advances ◽  
2016 ◽  
Vol 6 (57) ◽  
pp. 51716-51724 ◽  
Author(s):  
Dan Zhou ◽  
Jianbo Chen ◽  
Yi Xu
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Aldose Reductase ◽  
Inhibitory Activity ◽  
3D Qsar ◽  
Qsar Model ◽  
Structural Factors ◽  
Factors Affecting ◽  
Aldose Reductase Inhibitors ◽  
Reductase Inhibitors

The 3D-QSAR model of aldose reductase (ARIs) inhibitors is built to gain insights into the key structural factors affecting the inhibitory activity. Based on the model, six new potential ARIs were designed.

Quinoxalinones Based Aldose Reductase Inhibitors: 2D and 3D‐QSAR Analysis

2019 ◽  
Vol 38 (8-9) ◽  
pp. 1800149
Author(s):  
Vijay H. Masand ◽  
Nahed N. Elsayed ◽  
Sumersingh D. Thakur ◽  
Nandkishor Gawhale ◽  
Mithilesh M. Rathore
Keyword(s):  
Aldose Reductase ◽  
3D Qsar ◽  
Qsar Analysis ◽  
Aldose Reductase Inhibitors ◽  
Reductase Inhibitors ◽  
2D And 3D

Kinetics and molecular docking studies of kaempferol and its prenylated derivatives as aldose reductase inhibitors

2012 ◽  
Vol 197 (2-3) ◽  
pp. 110-118 ◽  
Author(s):  
Hyun Ah Jung ◽  
Hye Eun Moon ◽  
Sang Ho Oh ◽  
Byung-Woo Kim ◽  
Hee Sook Sohn ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Aldose Reductase ◽  
Docking Studies ◽  
Molecular Docking Studies ◽  
Aldose Reductase Inhibitors ◽  
Reductase Inhibitors

scholarly journals In Silico Screening of Sesquiterpene Lactones as Aldose Reductase Inhibitors

2021 ◽  
Vol 28 (2) ◽  
pp. 64-69
Author(s):  
A.M. Alhassan ◽  
I. Malami
Keyword(s):  
Molecular Docking ◽  
Binding Energy ◽  
Aldose Reductase ◽  
In Silico ◽  
Sesquiterpene Lactones ◽  
Docking Simulation ◽  
Binding Energies ◽  
In Silico Docking ◽  
Aldose Reductase Inhibitors ◽  
Reductase Inhibitors

Aldose reductase, a key enzyme of the polyol pathway catalyses NADPH-dependent reduction of glucose to sorbitol. Increased activity of this enzyme is considered a major factor contributing to the development of diabetic complications hence could be an important target in the treatment of these complications. In this work, a database of sesquiterpenes was prepared and screened for their drug-like properties based on the Lipinski’s rule of 5. The co-crystallised structure of aldose reductase was obtained from the Protein Databank and prepared for docking. In silico docking experiments was performed on Autodock tools using 198 sesquiterpene lactones that passed screening, and compounds with the lowest binding energy and favourable binding interactions were selected for molecular docking simulation. Six of the best ranking compounds selected had binding energies ranging from–11.96 Kcal/mol to -9.45 Kcal/mol  and were comparable to the energy of the standard inhibitor Idd594 used in the study. They also show good complementarity in their binding to the residues of the binding pocket. The results suggest that dehydrooopodin (1), 11(S),13-dihydrolactucopicrin (2), and Chrysanin (3) offered potential inhibitory activities toward aldose reductase and may serve as lead compounds for in vivo validation as aldose reductase inhibitors. Keywords: Sesquiterpene lactones, Aldose reductase, Binding energy, Molecular docking, Autodock

scholarly journals Computational Investigation of Adenosine 5′- (α, β-methylene)- diphosphate (AMPCP) Derivatives as Ecto-5′-nucleotidase (CD73) Inhibitors by Using 3D-QSAR, Molecular Docking, and Molecular Dynamics Simulations

2021 ◽  
Author(s):  
Jiatong Wen ◽  
Heng Zhang ◽  
Churen Meng ◽  
Di Zhou ◽  
Gang Chen ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Tumor Cells ◽  
Binding Free Energy ◽  
3D Qsar ◽  
Qsar Model ◽  
Field Analysis ◽  
Dynamics Simulation ◽  
Comfa Model ◽  
Structure Activity

Abstract CD73, as a surface enzyme anchored on the outside of the cell membrane via glycosylphosphatidylinositol (GPI), can convert the AMP in the tumor cell microenvironment into adenosine to promote the growth of tumor cells. It has been overexpressed in many different types of human tumors, such as gastric cancer, pancreatic cancer, liver cancer and other tumor cells. Therefore, targeted inhibitors of CD73 are considered as potential tumor treatment methods. Due to the low bioavailability of nucleoside CD73 inhibitors, it is necessary to develop new inhibitors. In this study, through molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular dynamics (MD) simulations, a series of CD73 inhibitors were calculated and studied to reveal their structure-activity relationships. Through molecular docking studies, explore the possible mode of interaction between inhibitors and protein. Subsequently, a 3D-QSAR model was established by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). For the best CoMFA model, the Q2 and R2 values ​​are 0.708 and 0.983, respectively, while for the best CoMSIA model, the Q2 and R2 values ​​are 0.809 and 0.992, respectively. In addition, the stability of the complex formed by the two inhibitors and CD73 was evaluated by molecular dynamics simulation, and the results are consistent with the results of molecular docking and 3D-QSAR research. Finally, the binding free energy was calculated by the surface area method (MM-GBSA), and the results are consistent with the activities that Van Der Waals and Coulomb contribute the most during the binding process of the molecule to the CD73 protein. In conclusion, our research provides valuable information for the further development of CD73 inhibitors.

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