scholarly journals Corrigendum: A Three-Dimensional Quanititative Structure-Activity Relationship (3D-QSAR) Model for Predicting the Enantioselectivity of Candida antarctica Lipase B

2011 ◽  
Vol 353 (9) ◽  
pp. 1405-1405 ◽  
Author(s):  
Paolo Braiuca ◽  
Knapic Lorena ◽  
Valerio Ferrario ◽  
Cynthia Ebert ◽  
Lucia Gardossi
Keyword(s):  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Structure Activity Relationship ◽  
Candida Antarctica ◽  
Candida Antarctica Lipase B ◽  
Activity Relationship ◽  
Candida Antarctica Lipase ◽  
Lipase B ◽  
Structure Activity

Towards further Understanding the Structural Requirements of Combretastatin- like Chalcones as Inhibitors of Microtubule Polymerization

2020 ◽  
Vol 16 (2) ◽  
pp. 155-166
Author(s):  
Naveen Dhingra ◽  
Anand Kar ◽  
Rajesh Sharma
Keyword(s):  
Three Dimensional ◽  
3D Qsar ◽  
Docking Study ◽  
Structure Activity Relationship ◽  
Docking Studies ◽  
Activity Relationship ◽  
Structural Requirement ◽  
Ligand Interaction ◽  
Microtubule Polymerization ◽  
Structure Activity

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.

Computational Atom-based Three-Dimensional Quantitative Structure-Activity Relationship (3D QSAR) Model for Predicting Anti-Dengue Agents

2021 ◽  
Vol 16 (10) ◽  
pp. 50-58
Author(s):  
Ali Qusay Khalid ◽  
Vasudeva Rao Avupati ◽  
Husniza Hussain ◽  
Tabarek Najeeb Zaidan
Keyword(s):  
Dengue Fever ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Contour Maps ◽  
Structure Activity ◽  
Bioactive Ligands

Dengue fever is a viral infection spread by the female mosquito Aedes aegypti. It is a virus spread by mosquitoes found all over the tropics with risk levels varying depending on rainfall, relative humidity, temperature and urbanization. There are no specific medications that can be used to treat the condition. The development of possible bioactive ligands to combat Dengue fever before it becomes a pandemic is a global priority. Few studies on building three-dimensional quantitative structure-activity relationship (3D QSAR) models for anti-dengue agents have been reported. Thus, we aimed at building a statistically validated atom-based 3D-QSAR model using bioactive ligands reported to possess significant anti-dengue properties. In this study, the Schrodinger PhaseTM atom-based 3D QSAR model was developed and was validated using known anti-dengue properties as ligand data. This model was also tested to see if there was a link between structural characteristics and anti-dengue activity of a series of 3-acyl-indole derivatives. The established 3D QSAR model has strong predictive capacity and is statistically significant [Model: R2 Training Set = 0.93, Q2 (R2 Test Set) = 0.72]. In addition, the pharmacophore characteristics essential for the reported anti-dengue properties were explored using combined effects contour maps (coloured contour maps: blue: positive potential and red: negative potential) of the model. In the pathway of anti-dengue drug development, the model could be included as a virtual screening method to predict novel hits.

scholarly journals 2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Manman Zhao ◽  
Lin Wang ◽  
Linfeng Zheng ◽  
Mengying Zhang ◽  
Chun Qiu ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Egfr Inhibitors ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
2D Qsar ◽  
Structure Activity

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.

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