The Psychonauts’ Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological 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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Quantitative structure-activity relationship and molecular docking studies of some series of imidazole derivatives as anti-hepatitis C drug

Bayero Journal of Pure and Applied Sciences ◽

10.4314/bajopas.v11i2.8 ◽

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

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Quantitative Structure Activity Relationship (QSAR) Based on Electronic Descriptors and Docking Studies of Quinazoline Derivatives for Anticancer Activity

Oriental Journal Of Chemistry ◽

10.13005/ojc/340517 ◽

2018 ◽

Vol 34 (5) ◽

pp. 2361-2369

Author(s):

Herlina Rasyid ◽

Bambang Purwono ◽

Ria Armunanto

Keyword(s):

External Validation ◽

Quantitative Structure Activity Relationship ◽

Structure Activity Relationship ◽

Docking Studies ◽

Activity Relationship ◽

Quantitative Structure ◽

Qsar Analysis ◽

Structure Activity ◽

B3lyp Method ◽

Quinazoline Derivatives

Quantitative structure-activity relationship (QSAR) based on electronic descriptors had been conducted on 2,3-dihydro-[1,4]dioxino[2,3-f]quinazoline analogues as anticancer using DFT/B3LYP method. The best QSAR equation described as follow: Log IC50 = -11.688 + (-35.522×qC6) + (-21.055×qC10) + (-85.682×qC12) + (-32.997×qO22) + (-85.129 EHOMO) + (19.724×ELUMO). Statistical value of R2 = 0.8732, rm2 = 0.7935, r2-r02/r2 = 0.0118, PRESS = 1.5727 and Fcalc/Ftable = 2.4067 used as external validation. Atomic net charge showed as the most important descriptor to predict activity and design new molecule. Following QSAR analysis, Lipinski rules was applied to filter the design compound due to physicochemical properties and resulted that all filtered compounds did not violate the rules. Docking analysis was conducted to determine interaction between proposed compounds and EGFR protein. Critical hydrogen bond was found in Met769 residue suggesting that proposed compounds could be used to inhibit EGFR protein.

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