scholarly journals Three-Dimensional Quantitative Structural Activity Relationship (3D-QSAR) Studies of Some 1,5-Diarylpyrazoles: Analogue Based Design of Selective Cyclooxygenase-2 Inhibitors

Molecules ◽  
2000 ◽  
Vol 5 (12) ◽  
pp. 945-955 ◽  
Author(s):  
Gautam Desiraju ◽  
Bulusu Gopalakrishnan ◽  
Ram Jetti ◽  
Dayam Raveendra ◽  
Jagarlapudi Sarma ◽  
...  
Keyword(s):  
Three Dimensional ◽  
3D Qsar ◽  
Cyclooxygenase 2 ◽  
Activity Relationship ◽  
Qsar Studies ◽  
Structural Activity Relationship ◽  
Quantitative Structural Activity Relationship ◽  
Cyclooxygenase 2 Inhibitors

3D-QSAR Studies of S-DABO Derivatives as Non-nucleoside HIV-1 Reverse Transcriptase Inhibitors

2019 ◽  
Vol 16 (8) ◽  
pp. 868-881
Author(s):  
Yueping Wang ◽  
Jie Chang ◽  
Jiangyuan Wang ◽  
Peng Zhong ◽  
Yufang Zhang ◽  
...  
Keyword(s):  
Reverse Transcriptase ◽  
Three Dimensional ◽  
Predictive Ability ◽  
3D Qsar ◽  
Binding Mode ◽  
Quantitative Structure Activity Relationship ◽  
Field Analysis ◽  
Reverse Transcriptase Inhibitors ◽  
Qsar Studies ◽  
Hiv 1

Background: S-dihydro-alkyloxy-benzyl-oxopyrimidines (S-DABOs) as non-nucleoside reverse transcriptase inhibitors have received considerable attention during the last decade due to their high potency against HIV-1. Methods: In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) of a series of 38 S-DABO analogues developed in our lab was studied using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). The Docking/MMFF94s computational protocol based on the co-crystallized complex (PDB ID: 1RT2) was used to determine the most probable binding mode and to obtain reliable conformations for molecular alignment. Statistically significant CoMFA (q2=0.766 and r2=0.949) and CoMSIA (q2=0.827 and r2=0.974) models were generated using the training set of 30 compounds on the basis of hybrid docking-based and ligand-based alignment. Results: The predictive ability of CoMFA and CoMSIA models was further validated using a test set of eight compounds with predictive r2 pred values of 0.843 and 0.723, respectively. Conclusion: The information obtained from the 3D contour maps can be used in designing new SDABO derivatives with improved HIV-1 inhibitory 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.

Computational Studies of 3D-QSAR on a Highly Active Series of Naturally Occurring Nonnucleoside Inhibitors of HIV-1 RT (NNRTI)

2020 ◽  
pp. 2050036
Author(s):  
Waqar Hussain ◽  
Arshia Majeed ◽  
Ammara Akhtar ◽  
Nouman Rasool
Keyword(s):  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Modeling ◽  
Qsar Analysis ◽  
Qsar Studies ◽  
Highly Active ◽  
Naturally Occurring ◽  
Zinc Database ◽  
Immunodeficiency Syndrome ◽  
Hiv 1

HIV is one of the deadliest viruses in the history of mankind, it is the root cause of Acquired Immunodeficiency Syndrome (AIDS) around the world. Despite the fact that the antiviral therapy used against HIV-1 infection is effective, there is also rapidly growing cases of drug resistance in the infected patient along with different severe side effects. Therefore, it is of dire and immediate need to find novel inhibitors against HIV-1 Reverse Transcriptase (RT). In this study, the potential of naturally occurring compounds extracted from plants has been studied with the help of Three-Dimensional-Quantitative Structure–Activity Relationships (3D-QSAR) analysis. A total of 20 compounds, retrieved from a ZINC database, were analyzed with the help of 3D-QSAR to identify a potential inhibitor of HIV-1 RT. By evaluation of seven models generated with the help of MIF analysis and 3D-QSAR modeling, compound 3 (ZINC ID: ZINC20759448) was observed to outperform others by showing optimal results in QSAR studies. This compound has also been biologically validated by a recently reported previous study. Thus, this compound can be used as a potential drug against infection caused by HIV-1, specifically AIDS.

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