Diaminomaleonitrile derivatives as new potential antichagasic compounds: a study of structure–activity relationships

2021 ◽  
Author(s):  
Aldo S de Oliveira ◽  
Lucas dos S Mello ◽  
Camila H Ogihara ◽  
Thiago H Döring ◽  
David L Palomino-Salcedo ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Schiff Bases ◽  
Correlation Coefficients ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Binding Energies ◽  
Quantitative Structure ◽  
Hydrophobic Contact ◽  
Structure Activity ◽  
High Yields

Background: Schiff bases are synthetically accessible compounds that have been used in medicinal chemistry. Methods & results: In this work, 27 Schiff bases derived from diaminomaleonitrile were synthesized in high yields (80–98%). Molecular docking studies suggested that the Schiff bases interact with the catalytic site of cruzain. The most active cruzain inhibitor, analog 13 (IC50 = 263 nM), was predicted to form an additional hydrophobic contact with Met68 in the binding site of the enzyme. A strong correlation between the IC50 values and ChemScore binding energies was observed (R = 0.99). Kernel-based 2D quantitative structure–activity relationship models for the whole dataset yielded sound correlation coefficients (R2 = 0.844; Q2 = 0.719). Conclusion: These novel and potent cruzain inhibitors are worthwhile starting points in further Chagas disease drug discovery programs.

scholarly journals Discovery of Novel 1,2,4-Oxadiazole Derivatives as Potent Caspase-3 Activator for Cancer Treatment

Chemistry ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 373-381
Author(s):  
Ankur Vaidya
Keyword(s):  
Hydrogen Bonding ◽  
Molecular Docking ◽  
Caspase 3 ◽  
Predictive Ability ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Quantitative Structure ◽  
Structure Activity ◽  
Docking Program ◽  
Oxadiazole Derivatives

In the present study, a quantitative structure–activity relationship (QSAR) and docking studies were accomplished on a series of 1,2,4-oxadiazoles. The results of QSARs are reliable and have high predictive ability for both the internal (q2 = 0.610) and external (pred_r2 = 0.553) datasets with least standard error (SE; i.e., 0.130) and four principal components, which signifies the reliability of the generated model. Molecular docking was also reported by the GOLD docking program, which showed that the hydrogen bonding may be responsible for the activity, and may be further increased upon adding high electronegative substitutions.

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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