Structure‐Based Analysis of Sertraline’s Binding Affinity With CYP2B6: An In Silico DFT and Molecular Docking Approach

Sertraline, a widely prescribed selective serotonin reuptake inhibitor (SSRI), is primarily metabolized by cytochrome P450 enzymes, particularly CYP2B6, CYP2C19, and CYP3A4. However, the molecular basis of its interaction with CYP2B6 and the determinants of its binding stability remain incompletely understood. In this study, sertraline optimization was performed using density functional theory (DFT) at the B3LYP/6–311 + G(d,p) level. The reactivity of sertraline was examined via its frontier molecular orbitals. The HOMO and LUMO energies were found to be −5.53 eV and −1.03 eV, respectively, and 10 regions of chemical activity were identified. In this study, molecular docking simulations were performed using the Molecular Operating Environment (MOE) to investigate the binding mode, energetics, and key interactions between sertraline and CYP2B6. The docking results indicate that sertraline occupies the active site of CYP2B6 with a favorable binding orientation, characterized by a calculated binding free energy (ΔG) of −8.22 kcal/mol. The complex is primarily stabilized by a network of noncovalent interactions. Hydrogen bonds are formed between sertraline and several important active‐site residues, including glutamate, glycine, histidine, aspartate, tyrosine, and arginine. In addition, hydrophobic contacts and π–π stacking between the chlorophenyl group of sertraline and aromatic binding pocket residues also stabilize the complex. Together, these findings elucidate the molecular basis of sertraline binding to CYP2B6 and explain its metabolic selectivity, aiding the interpretation of interindividual variability in its metabolism.

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Publication Details

Journal
Journal of Chemistry
Published
2026-01-01
DOI
https://doi.org/10.1155/joch/8437866
Primary Topic
Pharmacogenetics and Drug Metabolism
Type
article
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article

Structure‐Based Analysis of Sertraline’s Binding Affinity With CYP2B6: An In Silico DFT and Molecular Docking Approach

Journal of Chemistry
Pharmacogenetics and Drug Metabolism
article

Structure‐Based Analysis of Sertraline’s Binding Affinity With CYP2B6: An In Silico DFT and Molecular Docking Approach

article en

Abstract

Sertraline, a widely prescribed selective serotonin reuptake inhibitor (SSRI), is primarily metabolized by cytochrome P450 enzymes, particularly CYP2B6, CYP2C19, and CYP3A4. However, the molecular basis of its interaction with CYP2B6 and the determinants of its binding stability remain incompletely understood. In this study, sertraline optimization was performed using density functional theory (DFT) at the B3LYP/6–311 + G(d,p) level. The reactivity of sertraline was examined via its frontier molecular orbitals. The HOMO and LUMO energies were found to be −5.53 eV and −1.03 eV, respectively, and 10 regions of chemical activity were identified. In this study, molecular docking simulations were performed using the Molecular Operating Environment (MOE) to investigate the binding mode, energetics, and key interactions between sertraline and CYP2B6. The docking results indicate that sertraline occupies the active site of CYP2B6 with a favorable binding orientation, characterized by a calculated binding free energy (ΔG) of −8.22 kcal/mol. The complex is primarily stabilized by a network of noncovalent interactions. Hydrogen bonds are formed between sertraline and several important active‐site residues, including glutamate, glycine, histidine, aspartate, tyrosine, and arginine. In addition, hydrophobic contacts and π–π stacking between the chlorophenyl group of sertraline and aromatic binding pocket residues also stabilize the complex. Together, these findings elucidate the molecular basis of sertraline binding to CYP2B6 and explain its metabolic selectivity, aiding the interpretation of interindividual variability in its metabolism.

Journal of ChemistryVol. 2026(1)
University of Jiroft (IR), Islamic Azad University Kerman (IR)
Affordable and clean energy
Openalex Percentile: Top 10%
Pharmacogenetics and Drug Metabolism
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