scholarly journals The Universal 3D QSAR Model for Dopamine D2 Receptor Antagonists

2019 ◽  
Vol 20 (18) ◽  
pp. 4555 ◽  
Author(s):  
Agata Zięba ◽  
Justyna Żuk ◽  
Damian Bartuzi ◽  
Dariusz Matosiuk ◽  
Antti Poso ◽  
...  

In order to search for novel antipsychotics acting through the D2 receptor, it is necessary to know the structure–activity relationships for dopamine D2 receptor antagonists. In this context, we constructed the universal three-dimensional quantitative structure–activity relationship (3D- QSAR) model for competitive dopamine D2 receptor antagonists. We took 176 compounds from chemically different groups characterized by the half maximal inhibitory concentration (IC50)from the CHEMBL database and docked them to the X-ray structure of the human D2 receptor in the inactive state. Selected docking poses were applied for Comparative Molecular Field Analysis (CoMFA) alignment. The obtained CoMFA model is characterized by a cross-validated coefficient Q2 of 0.76 with an optimal component of 5, R2 of 0.92, and an F value of 338.9. The steric and electrostatic field contributions are 67.4% and 32.6%, respectively. The statistics obtained prove that the CoMFA model is significant. Next, the IC50 of the 16 compounds from the test set was predicted with R2 of 0.95. Finally, a progressive scrambling test was carried out for additional validation. The CoMFA fields were mapped onto the dopamine D2 receptor binding site, which enabled a discussion of the structure–activity relationship based on ligand–receptor interactions. In particular, it was found that one of the desired steric interactions covers the area of a putative common allosteric pocket suggested for some other G protein-coupled receptors (GPCRs), which would suggest that some of the known dopamine receptor antagonists are bitopic in their essence. The CoMFA model can be applied to predict the potential activity of novel dopamine D2 receptor antagonists.

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Manman Zhao ◽  
Lin Wang ◽  
Linfeng Zheng ◽  
Mengying Zhang ◽  
Chun Qiu ◽  
...  

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.


Author(s):  
Shobana Sugumar

  Objective: To find out novel inhibitors for histamine 4 receptor (H4R), the target for various allergic and inflammatory pathophysiological conditions.Methods: Homology modeling of H4R was performed using easy modeler and validated using structure analysis and verification server, and with the modeled structure, virtual screening, pharmacophore modeling, and quantitative structure activity relationship (QSAR) studies were performed using the Schrodinger 9.3 software.Results: Among all the synthetic and natural ligands, hesperidin, vitexin, and diosmin were found to have the highest dock score, and with that, a five-point pharmacophore model was developed consisting of two hydrogen bond acceptor and three ring atoms, and the pharmacophore hypothesis yielded a statistically significant three-dimensional QSAR (3D-QSAR) model with a correlation coefficient of r2=0.8962 as well as good predictive power.Conclusion: The pharmacophore-based 3D-QSAR model generated from natural antihistamines can provide intricate structural knowledge about a new class of anti-allergic and anti-inflammatory drug research.


2020 ◽  
Vol 16 (2) ◽  
pp. 155-166
Author(s):  
Naveen Dhingra ◽  
Anand Kar ◽  
Rajesh Sharma

Background: Microtubules are dynamic filamentous cytoskeletal structures which play several key roles in cell proliferation and trafficking. They are supposed to contribute in the development of important therapeutic targeting tumor cells. Chalcones are important group of natural compounds abundantly found in fruits & vegetables that are known to possess anticancer activity. We have used QSAR and docking studies to understand the structural requirement of chalcones for understanding the mechanism of microtubule polymerization inhibition. Methods: Three dimensional (3D) QSAR (CoMFA and CoMSIA), pharmacophore mapping and molecular docking studies were performed for the generation of structure activity relationship of combretastatin-like chalcones through statistical models and contour maps. Results: Structure activity relationship revealed that substitution of electrostatic, steric and donor groups may enhance the biological activity of compounds as inhibitors of microtubule polymerization. From the docking study, it was clear that compounds bind at the active site of tubulin protein. Conclusion: The given strategies of modelling could be an encouraging way for designing more potent compounds as well as for the elucidation of protein-ligand interaction.


2013 ◽  
Vol 56 (22) ◽  
pp. 9199-9221 ◽  
Author(s):  
Jeremy Shonberg ◽  
Carmen Klein Herenbrink ◽  
Laura López ◽  
Arthur Christopoulos ◽  
Peter J. Scammells ◽  
...  

ChemInform ◽  
2010 ◽  
Vol 32 (23) ◽  
pp. no-no
Author(s):  
Lin Chu ◽  
Jennifer E. Hutchins ◽  
Ann E. Weber ◽  
Jane-Ling Lo ◽  
Yi-Tien Yang ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document