scholarly journals 3D-QSAR, Molecular Docking, and MD Simulations of Anthraquinone Derivatives as PGAM1 Inhibitors

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuwei Wang ◽  
Yifan Guo ◽  
Shaojia Qiang ◽  
Ruyi Jin ◽  
Zhi Li ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Rational Design ◽  
Binding Free Energy ◽  
3D Qsar ◽  
Md Simulations ◽  
Structure Activity Relationships ◽  
Structure Activity ◽  
Wide Range ◽  
Anthraquinone Derivatives

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.

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.

scholarly journals Investigating the Binding Mode of Reversible LSD1 Inhibitors Derived from Stilbene Derivatives by 3D-QSAR, Molecular Docking, and Molecular Dynamics Simulation

Molecules ◽  
2019 ◽  
Vol 24 (24) ◽  
pp. 4479
Author(s):  
Yongtao Xu ◽  
Zihao He ◽  
Min Yang ◽  
Yunlong Gao ◽  
Linfeng Jin ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Binding Free Energy ◽  
Clinical Stage ◽  
3D Qsar ◽  
Structure Activity Relationship ◽  
Field Analysis ◽  
Dynamics Simulation ◽  
Activity Relationship ◽  
Structure Activity ◽  
Stilbene Derivatives

Overexpression of lysine specific demethylase 1 (LSD1) has been found in many cancers. New anticancer drugs targeting LSD1 have been designed. The research on irreversible LSD1 inhibitors has entered the clinical stage, while the research on reversible LSD1 inhibitors has progressed slowly so far. In this study, 41 stilbene derivatives were studied as reversible inhibitors by three-dimensional quantitative structure–activity relationship (3D-QSAR). Comparative molecular field analysis (CoMFA q 2 = 0.623, r 2 = 0.987, r pred 2 = 0.857) and comparative molecular similarity indices analysis (CoMSIA q 2 = 0.728, r 2 = 0.960, r pred 2 = 0.899) were used to establish the model, and the structure–activity relationship of the compounds was explained by the contour maps. The binding site was predicted by two different kinds of software, and the binding modes of the compounds were further explored. A series of key amino acids Val288, Ser289, Gly314, Thr624, Lys661 were found to play a key role in the activity of the compounds. Molecular dynamics (MD) simulations were carried out for compounds 04, 17, 21, and 35, which had different activities. The reasons for the activity differences were explained by the interaction between compounds and LSD1. The binding free energy was calculated by molecular mechanics generalized Born surface area (MM/GBSA). We hope that this research will provide valuable information for the design of new reversible LSD1 inhibitors in the future.

3D-QSAR Assisted Design of Novel 7-Deazapurine Derivatives as TNNI3K Kinase Inhibitors Using Molecular Docking and Molecular Dynamics Simulation

2020 ◽  
Vol 17 (2) ◽  
pp. 155-168
Author(s):  
Pavithra K. Balasubramanian ◽  
Anand Balupuri ◽  
Swapnil P. Bhujbal ◽  
Seung Joo Cho
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
3D Qsar ◽  
Structure Activity Relationship ◽  
Dynamics Simulation ◽  
Activity Relationship ◽  
Dual Function ◽  
Contour Maps ◽  
Structure Activity

Background: Cardiac troponin I-interacting kinase (TNNI3K) is a cardiac-specific kinase that belongs to MAPKKK family. It is a dual-function kinase with tyrosine and serine/threonine kinase activity. Over-expression of TNNI3K results in various cardiovascular diseases such as cardiomyopathy, ischemia/reperfusion injury, heart failure, etc. Since, it is a cardiac-specific kinase and expressed only in heart tissue, it is an ideal molecular target to treat cardiac diseases. The main objective of the work is to study and understand the structure-activity relationship of the reported deazapurine derivatives and to use the 3D-QSAR and docking results to design potent and novel TNNI3K inhibitors of this series. Methods: In the present study, we have used molecular docking 3D QSAR, and molecular dynamics simulation to understand the structure-activity correlation of reported TNNI3K inhibitors and to design novel compounds of deazapurine derivatives with increased activity. Results: Both CoMFA (q2=0.669, NOC=5, r2=0.944) and CoMSIA (q2=0.783, NOC=5, r2=0.965) have resulted in satisfactory models. The models were validated using external test set, Leave-out- Five, bootstrapping, progressive scrambling, and rm2 metrics calculations. The validation procedures showed the developed models were robust and reliable. The docking results and the contour maps analysis helped in the better understanding of the structure-activity relationship. Conclusion: This is the first report on 3D-QSAR modeling studies of TNNI3K inhibitors. Both docking and MD results were consistent and showed good correlation with the previous experimental data. Based on the information obtained from contour maps, 31 novel TNNI3K inhibitors were designed. These designed compounds showed higher activity than the existing dataset compounds.

In silico study of 3-hydroxypyrimidine-2,4-diones as inhibitors of HIV RT-associated RNase H using molecular docking, molecular dynamics, 3D-QSAR, and pharmacophore models

2019 ◽  
Vol 43 (43) ◽  
pp. 17004-17017 ◽  
Author(s):  
Ya Gao ◽  
Yanming Chen ◽  
Yafeng Tian ◽  
Yilan Zhao ◽  
Fengshou Wu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Rational Design ◽  
3D Qsar ◽  
Rnase H ◽  
Ribonuclease H ◽  
Hiv Reverse Transcriptase ◽  
In Silico Study ◽  
Hiv Rt ◽  
Pharmacophore Models

Rational design and virtual screening of novel inhibitors of HIV reverse transcriptase associated ribonuclease H based on a combined molecular modeling study.

3D-QSAR, Docking, and Molecular Dynamics Simulations Studies on Quinazoline Derivatives as PAK4 Inhibitors

2021 ◽  
Vol 18 ◽  
Author(s):  
Xiao-Zhong Chen ◽  
Dai Chen ◽  
Yan Shen ◽  
Juan Wang ◽  
Yong Hu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Hydrophobic Interactions ◽  
3D Qsar ◽  
Structural Basis ◽  
High Biological Activity ◽  
Promising Target ◽  
Wide Range ◽  
Dynamics Simulations

Background: The p21-activated kinases 4 (PAK4) refer to a promising target for cancer treatment. Currently, a wide range of PAK4 inhibitors has been reported. Objective: To study the structural requirements of quinoline derivatives as PAK4 inhibitors and design novel PAK4 inhibitors. Method: In the present study, a set of quinazoline PAK4 inhibitors underwent CoMFA, CoMSIA, molecular docking, as well as molecular dynamics simulations. Results: The built CoMFA (q2=0.792, r2=0.994, r2pred =0.74) and CoMSIA (q2=0.873, r2=0.994, r2pred=0.81) models exhibited high robustness and prominent predicting ability. As revealed from the results of molecular docking and molecular dynamics simulations, hydrogen bond and hydrophobic interactions primarily impact the affinity of PAK4 inhibitors, and Leu398 acts as an amino acid that leads to significant stabilization of the mentioned inhibitors. Moreover, the present study developed five novel molecules exhibiting high biological activity predicted and satisfactory ADME properties. Conclusion: The structural basis of PAK4 with respect to the activities of its inhibitors was revealed, which may be conducive to designing novel PAK4 inhibitors.

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