Computational Investigation of Montelukast and Its Structural Derivatives for Binding Affinity to Dopaminergic and Serotonergic Receptors: Insights from a Comprehensive Molecular Simulation
<b>Background/Objectives</b>: Montelukast (MLK), a leukotriene receptor antagonist, has been associated with neuropsychiatric side effects. This study aimed to rationally modify MLK’s structure to reduce these risks by optimizing its interactions with dopamine D2 (DRD2) and serotonin 5-H...
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MDPI AG
2025-04-01
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| author | Nasser Alotaiq Doni Dermawan |
| author_facet | Nasser Alotaiq Doni Dermawan |
| author_sort | Nasser Alotaiq |
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| description | <b>Background/Objectives</b>: Montelukast (MLK), a leukotriene receptor antagonist, has been associated with neuropsychiatric side effects. This study aimed to rationally modify MLK’s structure to reduce these risks by optimizing its interactions with dopamine D2 (DRD2) and serotonin 5-HT1A receptors using computational molecular simulation techniques. <b>Methods</b>: A library of MLK derivatives was designed and screened using structural similarity analysis, molecular docking, molecular dynamics (MD) simulations, MM/PBSA binding free energy calculations, and ADME-Tox predictions. Structural similarity analysis, based on Tanimoto coefficient fingerprinting, compared MLK derivatives to known neuropsychiatric drugs. Docking was performed to assess initial receptor binding, followed by 100 ns MD simulations to evaluate binding stability. MM/PBSA calculations quantified binding affinities, while ADME-Tox profiling predicted pharmacokinetic and toxicity risks. <b>Results</b>: Several MLK derivatives showed enhanced DRD2 and 5-HT1A binding. MLK_MOD-42 and MLK_MOD-43 emerged as the most promising candidates, exhibiting MM/PBSA binding free energies of −31.92 ± 2.54 kcal/mol and −27.37 ± 2.22 kcal/mol for DRD2 and −30.22 ± 2.29 kcal/mol and −28.19 ± 2.14 kcal/mol for 5-HT1A, respectively. Structural similarity analysis confirmed that these derivatives share key pharmacophoric features with atypical antipsychotics and anxiolytics. However, off-target interactions were not assessed, which may influence their overall safety profile. ADME-Tox analysis predicted improved oral bioavailability and lower neurotoxicity risks. <b>Conclusions</b>: MLK_MOD-42 and MLK_MOD-43 exhibit optimized receptor interactions and enhanced pharmacokinetics, suggesting potential neuropsychiatric applications. However, their safety and efficacy remain to be validated through in vitro and in vivo studies. Until such validation is performed, these derivatives should be considered as promising candidates with optimized receptor binding rather than confirmed safer alternatives. |
| format | Article |
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| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
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| series | Pharmaceuticals |
| spelling | doaj-art-b1d1bd312e034b4b99bab56b097c70772025-08-20T02:18:04ZengMDPI AGPharmaceuticals1424-82472025-04-0118455910.3390/ph18040559Computational Investigation of Montelukast and Its Structural Derivatives for Binding Affinity to Dopaminergic and Serotonergic Receptors: Insights from a Comprehensive Molecular SimulationNasser Alotaiq0Doni Dermawan1Health Sciences Research Center (HSRC), Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13317, Saudi ArabiaDepartment of Applied Biotechnology, Faculty of Chemistry, Warsaw University of Technology, 00-661 Warsaw, Poland<b>Background/Objectives</b>: Montelukast (MLK), a leukotriene receptor antagonist, has been associated with neuropsychiatric side effects. This study aimed to rationally modify MLK’s structure to reduce these risks by optimizing its interactions with dopamine D2 (DRD2) and serotonin 5-HT1A receptors using computational molecular simulation techniques. <b>Methods</b>: A library of MLK derivatives was designed and screened using structural similarity analysis, molecular docking, molecular dynamics (MD) simulations, MM/PBSA binding free energy calculations, and ADME-Tox predictions. Structural similarity analysis, based on Tanimoto coefficient fingerprinting, compared MLK derivatives to known neuropsychiatric drugs. Docking was performed to assess initial receptor binding, followed by 100 ns MD simulations to evaluate binding stability. MM/PBSA calculations quantified binding affinities, while ADME-Tox profiling predicted pharmacokinetic and toxicity risks. <b>Results</b>: Several MLK derivatives showed enhanced DRD2 and 5-HT1A binding. MLK_MOD-42 and MLK_MOD-43 emerged as the most promising candidates, exhibiting MM/PBSA binding free energies of −31.92 ± 2.54 kcal/mol and −27.37 ± 2.22 kcal/mol for DRD2 and −30.22 ± 2.29 kcal/mol and −28.19 ± 2.14 kcal/mol for 5-HT1A, respectively. Structural similarity analysis confirmed that these derivatives share key pharmacophoric features with atypical antipsychotics and anxiolytics. However, off-target interactions were not assessed, which may influence their overall safety profile. ADME-Tox analysis predicted improved oral bioavailability and lower neurotoxicity risks. <b>Conclusions</b>: MLK_MOD-42 and MLK_MOD-43 exhibit optimized receptor interactions and enhanced pharmacokinetics, suggesting potential neuropsychiatric applications. However, their safety and efficacy remain to be validated through in vitro and in vivo studies. Until such validation is performed, these derivatives should be considered as promising candidates with optimized receptor binding rather than confirmed safer alternatives.https://www.mdpi.com/1424-8247/18/4/5595-HT1AD2 dopaminemolecular dockingmolecular dynamicsmontelukastpharmacophore modeling |
| spellingShingle | Nasser Alotaiq Doni Dermawan Computational Investigation of Montelukast and Its Structural Derivatives for Binding Affinity to Dopaminergic and Serotonergic Receptors: Insights from a Comprehensive Molecular Simulation Pharmaceuticals 5-HT1A D2 dopamine molecular docking molecular dynamics montelukast pharmacophore modeling |
| title | Computational Investigation of Montelukast and Its Structural Derivatives for Binding Affinity to Dopaminergic and Serotonergic Receptors: Insights from a Comprehensive Molecular Simulation |
| title_full | Computational Investigation of Montelukast and Its Structural Derivatives for Binding Affinity to Dopaminergic and Serotonergic Receptors: Insights from a Comprehensive Molecular Simulation |
| title_fullStr | Computational Investigation of Montelukast and Its Structural Derivatives for Binding Affinity to Dopaminergic and Serotonergic Receptors: Insights from a Comprehensive Molecular Simulation |
| title_full_unstemmed | Computational Investigation of Montelukast and Its Structural Derivatives for Binding Affinity to Dopaminergic and Serotonergic Receptors: Insights from a Comprehensive Molecular Simulation |
| title_short | Computational Investigation of Montelukast and Its Structural Derivatives for Binding Affinity to Dopaminergic and Serotonergic Receptors: Insights from a Comprehensive Molecular Simulation |
| title_sort | computational investigation of montelukast and its structural derivatives for binding affinity to dopaminergic and serotonergic receptors insights from a comprehensive molecular simulation |
| topic | 5-HT1A D2 dopamine molecular docking molecular dynamics montelukast pharmacophore modeling |
| url | https://www.mdpi.com/1424-8247/18/4/559 |
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