scholarly journals Identification of potent histone deacetylase 8 inhibitors using pharmacophore-based virtual screening, three-dimensional quantitative structure–activity relationship, and docking study

2015 ◽  
pp. 21 ◽  
Author(s):  
Sudhan Debnath ◽  
Tanusree Debnath ◽  
Swapan Majumdar ◽  
Arunasree Kalle ◽  
Vema Aparna
Keyword(s):  
Virtual Screening ◽  
Histone Deacetylase ◽  
Three Dimensional ◽  
Docking Study ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Histone Deacetylase 8

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.

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