Potent LeuBAT inhibitors designed in silico as next-generation duloxetine analogs for enhanced major depressive disorder treatment

Major Depressive Disorder (MDD), a leading global health challenge, urgently requires advanced therapeutics to mitigate its widespread impact. In this study, a series of duloxetine (DLX) analogs were designed and evaluated using a comprehensive in silico workflow incorporating quantum chemical calculations, ADMET profiling, molecular docking, and molecular dynamics (MD) simulations. Density Functional Theory (DFT) calculations at the B3LYP/6-311G level were performed to assess electronic properties such as the HOMO-LUMO energy gap, dipole moment, electronegativity, and chemical softness. Among the designed compounds, DLX48 demonstrated superior quantum descriptors while retaining the electronic characteristics of the parent molecule. ADMET predictions using ADMETlab 3.0 and ProTox-II revealed that DLX48 complies with major drug-likeness rules (Lipinski, Pfizer), exhibits improved aqueous solubility (Log S = - 3.21), optimal lipophilicity (Log P = 2.87), and shows no predicted hepatotoxicity or genotoxicity. Molecular docking against the LeuBAT (Δ13 mutant) transporter revealed a significant increase in binding affinity for DLX48 (-12.45 kcal/mol), with an inhibition constant (Ki) of 742.09 pM-indicating markedly enhanced target engagement compared to DLX. Long-timescale MD simulations (300 ns) confirmed the thermodynamic stability and favorable dynamic behavior of the DLX48-LeuBAT complex, supported by lower RMSD/RMSF values, persistent hydrogen bonding, reduced solvent exposure, and constrained conformational fluctuations. Collectively, these in silico findings nominate DLX48 as a promising central nervous system (CNS)-active lead compound with enhanced pharmacological efficacy and a reduced toxicity profile, warranting further preclinical investigation for the treatment of depression and anxiety disorders.

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Journal
Scientific Reports
Published
2026-01-12
DOI
https://doi.org/10.1038/s41598-025-31085-z
Primary Topic
Computational Drug Discovery Methods
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article
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article

Potent LeuBAT inhibitors designed in silico as next-generation duloxetine analogs for enhanced major depressive disorder treatment

Mehdi Yoosefian, Tahmineh Mokhtari, Kasim Sakran Abass, Hedieh Bayramzadeh
Scientific Reports
Computational Drug Discovery Methods
article

Potent LeuBAT inhibitors designed in silico as next-generation duloxetine analogs for enhanced major depressive disorder treatment

Mehdi Yoosefian, Tahmineh Mokhtari, Kasim Sakran Abass, Hedieh Bayramzadeh
article en

Abstract

Major Depressive Disorder (MDD), a leading global health challenge, urgently requires advanced therapeutics to mitigate its widespread impact. In this study, a series of duloxetine (DLX) analogs were designed and evaluated using a comprehensive in silico workflow incorporating quantum chemical calculations, ADMET profiling, molecular docking, and molecular dynamics (MD) simulations. Density Functional Theory (DFT) calculations at the B3LYP/6-311G level were performed to assess electronic properties such as the HOMO-LUMO energy gap, dipole moment, electronegativity, and chemical softness. Among the designed compounds, DLX48 demonstrated superior quantum descriptors while retaining the electronic characteristics of the parent molecule. ADMET predictions using ADMETlab 3.0 and ProTox-II revealed that DLX48 complies with major drug-likeness rules (Lipinski, Pfizer), exhibits improved aqueous solubility (Log S = - 3.21), optimal lipophilicity (Log P = 2.87), and shows no predicted hepatotoxicity or genotoxicity. Molecular docking against the LeuBAT (Δ13 mutant) transporter revealed a significant increase in binding affinity for DLX48 (-12.45 kcal/mol), with an inhibition constant (Ki) of 742.09 pM-indicating markedly enhanced target engagement compared to DLX. Long-timescale MD simulations (300 ns) confirmed the thermodynamic stability and favorable dynamic behavior of the DLX48-LeuBAT complex, supported by lower RMSD/RMSF values, persistent hydrogen bonding, reduced solvent exposure, and constrained conformational fluctuations. Collectively, these in silico findings nominate DLX48 as a promising central nervous system (CNS)-active lead compound with enhanced pharmacological efficacy and a reduced toxicity profile, warranting further preclinical investigation for the treatment of depression and anxiety disorders.

Scientific ReportsVol. 16(1)
University of Kirkuk (IQ), Graduate University of Advanced Technology (IR), University of California System (US)
Good health and well-being
Openalex Percentile: Top 89%
Computational Drug Discovery Methods
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