N-Phenyl-3-sulfamoyl-benzamide derivatives as anti-hepatitis B virus agent candidates. Integrated computational studies

This study used a combined approach of atom-based 3D-QSAR modeling and molecular docking to investigate 44 N-phenyl-3-sulfamoyl-benzamide derivatives as potential inhibitors of the hepatitis B virus (HBV). The developed QSAR model demonstrated strong statistical robustness, with a good correlation coefficient for the training set (R2 = 0.94), a cross-validated coefficient (Q2cv = = 0.65), and a correlation coefficient for the test set (R2 = 0.85) using three PLS- -components. Contour maps explained the modified areas within the compounds, clarifying hydrogen bond donors, hydrophobic interactions and electrostatic effects. The docking studies supported the findings of the 3D-QSAR model and explained the molecule?s interactions with the receptors. Overall, the model and the docking analysis provide valuable insights into designing molecules with enhanced activity against the hepatitis B virus.

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Publication Details

Journal
Journal of the Serbian Chemical Society
Published
2025-01-01
DOI
https://doi.org/10.2298/jsc250430060l
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50
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article

N-Phenyl-3-sulfamoyl-benzamide derivatives as anti-hepatitis B virus agent candidates. Integrated computational studies

Abderahmane Belafriekh, Marwa Alaqarbeh, Aicha Laoud
1 citations
Journal of the Serbian Chemical Society
Computational Drug Discovery Methods
1.50
article

N-Phenyl-3-sulfamoyl-benzamide derivatives as anti-hepatitis B virus agent candidates. Integrated computational studies

Abderahmane Belafriekh, Marwa Alaqarbeh, Aicha Laoud
article en
1 citations

Abstract

This study used a combined approach of atom-based 3D-QSAR modeling and molecular docking to investigate 44 N-phenyl-3-sulfamoyl-benzamide derivatives as potential inhibitors of the hepatitis B virus (HBV). The developed QSAR model demonstrated strong statistical robustness, with a good correlation coefficient for the training set (R2 = 0.94), a cross-validated coefficient (Q2cv = = 0.65), and a correlation coefficient for the test set (R2 = 0.85) using three PLS- -components. Contour maps explained the modified areas within the compounds, clarifying hydrogen bond donors, hydrophobic interactions and electrostatic effects. The docking studies supported the findings of the 3D-QSAR model and explained the molecule?s interactions with the receptors. Overall, the model and the docking analysis provide valuable insights into designing molecules with enhanced activity against the hepatitis B virus.

Journal of the Serbian Chemical SocietyVol. 90(10)
University Frères Mentouri Constantine 1 (DZ), Al-Balqa Applied University (JO), Université Constantine 2 (DZ), University of Blida (DZ)
Good health and well-being
Openalex Percentile: Top 14%
Computational Drug Discovery Methods
1.50
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