Molecular modeling studies to characterize N-phenylpyrimidin-2-amine selectivity for CDK2 and CDK4 through 3D-QSAR and molecular dynamics simulations

2016 ◽  
Vol 12 (4) ◽  
pp. 1250-1268 ◽  
Author(s):  
Tahir Ali Chohan ◽  
Jiong-Jiong Chen ◽  
Hai-Yan Qian ◽  
You-Lu Pan ◽  
Jian-Zhong Chen
Keyword(s):  
Molecular Dynamics ◽  
Molecular Modeling ◽  
Molecular Dynamics Simulations ◽  
3D Qsar ◽  
Structure Activity ◽  
Modeling Studies ◽  
Molecular Modeling Studies ◽  
Dynamics Simulations

Molecular modeling simulations were carried out to understand the structure–activity and selectivity correlation of N-phenylpyrimidin-2-amines binding to CDK2 and CDK4.

Molecular Modeling Studies of Anti-Alzheimer Agents by QSAR, Molecular Docking and Molecular Dynamics Simulations Techniques

2020 ◽  
Vol 16 (7) ◽  
pp. 903-927 ◽  
Author(s):  
Rahman Abdizadeh ◽  
Farzin Hadizadeh ◽  
Tooba Abdizadeh
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Modeling ◽  
Molecular Dynamics Simulations ◽  
Data Set ◽  
Ache Inhibitors ◽  
Modeling Studies ◽  
Qsar Models ◽  
Molecular Modeling Studies ◽  
Dynamics Simulations

Background: Acetylcholinesterase (AChE), a serine hydrolase, is an important drug target in the treatment of Alzheimer's disease (AD). Thus, novel AChE inhibitors were designed and developed as potential drug candidates, for significant therapy of AD. Objective: In this work, molecular modeling studies, including CoMFA, CoMFA-RF, CoMSIA, HQSAR and molecular docking and molecular dynamics simulations were performed on a series of AChE inhibitors to get more potent anti-Alzheimer drugs. Methods: 2D/3D-QSAR models including CoMFA, CoMFA-RF, CoMSIA, and HQSAR methods were carried out on 40 pyrimidinylthiourea derivatives as data set by the Sybylx1.2 program. Molecular docking and molecular dynamics simulations were performed using the MOE software and the Sybyl program, respectively. Partial least squares (PLS) model as descriptors was used for QSAR model generation. Results: The CoMFA (q2, 0.629; r2ncv, 0.901; r2pred, 0.773), CoMFA-RF (q2, 0.775; r2ncv, 0.910; r2pred, 0.824), CoMSIA (q2, 0.754; r2ncv, 0.919; r2pred, 0.874) and HQSAR models (q2, 0.823; r2ncv, 0.976; r2pred, 0.854) for training and test set yielded significant statistical results. Conclusion: These QSAR models were excellent, robust and had good predictive capability. Contour maps obtained from the QSAR models were validated by molecular dynamics simulationassisted molecular docking study. The resulted QSAR models could be useful for the rational design of novel potent AChE inhibitors in Alzheimer's treatment.

Sign in / Sign up

Export Citation Format

Share Document