scholarly journals Quantitative structure-activity relationship and molecular docking studies of some series of imidazole derivatives as anti-hepatitis C drug

2019 ◽  
Vol 11 (2) ◽  
pp. 57
Author(s):  
A.S. Bello ◽  
A Uzairu ◽  
G.A. Shallangwa ◽  
A Ibrahim ◽  
Y.A. Gatugel
Keyword(s):  
Molecular Docking ◽  
Hepatitis C ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Docking Studies ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Molecular Docking Studies ◽  
Imidazole Derivatives ◽  
Structure Activity

scholarly journals A Quantitative Structure-Activity Relationship and Molecular Modeling Study on a Series of Biaryl Imidazole Derivatives Acting as H+/K+-ATPase Inhibitors

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Neeraj Agarwal ◽  
Anubha Bajpai ◽  
Vivek Srivastava ◽  
Satya P. Gupta
Keyword(s):  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Docking Studies ◽  
Activity Relationship ◽  
Electronic Interaction ◽  
Quantitative Structure ◽  
Qsar Study ◽  
Imidazole Derivatives ◽  
Structure Activity ◽  
Atpase Inhibitors

The H+/K+-ATPase or proton pump is a magnesium-dependant enzyme which causes the exchange of a proton against a potassium ion through a membrane. Over activity of this enzyme causes hyperacidity by producing more of hydrochloric acid inside the stomach. This enzyme, therefore, has been found to be a good target for designing compounds to treat hyperacidity. A quantitative structure-activity relationship (QSAR) study has been made on a novel series of biaryl imidazole derivatives acting as H+/K+-ATPase inhibitors. The H+/K+-ATPase inhibition activity of these compounds is found to be significantly correlated with global topological charge indices (GTCIs) and the total polar surface area (TPSA) of the molecules, indicating the involvement of strong electronic interaction between the molecule and the receptor. Based on the correlations obtained, some new H+/K+-ATPase inhibitors are predicted. The docking studies of these predicted compounds exhibit that these compounds will have even better interaction with the receptor than those already marketed. Thus, they can prove more potent drugs for the treatment of hyperacidity.

scholarly journals The Psychonauts’ Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity

2021 ◽  
Vol 14 (8) ◽  
pp. 720
Author(s):  
Valeria Catalani ◽  
Michelle Botha ◽  
John Martin Corkery ◽  
Amira Guirguis ◽  
Alessandro Vento ◽  
...  
Keyword(s):  
Biological Activity ◽  
Computational Models ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Docking Studies ◽  
Health Concern ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
High Biological Activity ◽  
Structure Activity

Designer benzodiazepines (DBZDs) represent a serious health concern and are increasingly reported in polydrug consumption-related fatalities. When new DBZDs are identified, very limited information is available on their pharmacodynamics. Here, computational models (i.e., quantitative structure-activity relationship/QSAR and Molecular Docking) were used to analyse DBZDs identified online by an automated web crawler (NPSfinder®) and to predict their possible activity/affinity on the gamma-aminobutyric acid A receptors (GABA-ARs). The computational software MOE was used to calculate 2D QSAR models, perform docking studies on crystallised GABA-A receptors (6HUO, 6HUP) and generate pharmacophore queries from the docking conformational results. 101 DBZDs were identified online by NPSfinder®. The validated QSAR model predicted high biological activity values for 41% of these DBDZs. These predictions were supported by the docking studies (good binding affinity) and the pharmacophore modelling confirmed the importance of the presence and location of hydrophobic and polar functions identified by QSAR. This study confirms once again the importance of web-based analysis in the assessment of drug scenarios (DBZDs), and how computational models could be used to acquire fast and reliable information on biological activity for index novel DBZDs, as preliminary data for further investigations.

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