Evidence map›Paper›PMID 41526406›Full record

ArticleScientific reports2026

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

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

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mehdi Yoosefian *Department of Chemistry, Graduate University of Advanced Technology, Kerman, Iran. myoosefian7@gmail.com.
Hedieh BayramzadehDepartment of Chemistry, Graduate University of Advanced Technology, Kerman, Iran.
Kasim Sakran AbassDepartment of Physiology, Biochemistry, and Pharmacology, College of Veterinary Medicine, University of Kirkuk, Kirkuk, 36001, Iraq.
Tahmineh Mokhtari *Department of Entomology and Nematology and UCD Comprehensive Cancer Center, University of California, Davis, CA, USA. tmokhtari@ucdavis.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Antidepressive AgentsDuloxetine HydrochlorideMajor Depressive DisorderComputer SimulationDrug DesignHumansMolecular Docking SimulationMolecular Dynamics SimulationAntidepressive AgentsDuloxetine HydrochlorideADMET predictionDrug designDuloxetine hydrochlorideMolecular dynamics simulationSerotonin and noradrenaline reuptake inhibitors

Identifiers

PMID41526406
PMCPMC12800040

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.