A multiple-step screening protocol to identify norepinephrine and dopamine reuptake inhibitors for depression

Wang, Panpan; Yan, Fengmei; Dong, Jianghong; Wang, Shengqiang; Shi, Yu; Zhu, Mengdan; zuo, Yuting; Ma, Hui; Xue, Ruirui; Zhai, Dingjie; Song, Xiaoyu

doi:10.1039/d2cp05676c

Cited by 7 publications

(5 citation statements)

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“…As endocrine hormones, NE and E can affect the the bodys' mood by modulating the sensitivity of neuronal synapses and neurotransmitters [22]. NE can return to the synaptic space under the action of NE transporter protein, and also form E by acting on phenylmethylamine-N-methyltransferase, which easily lead to fear and tension [23]. It had been reported that the blue spot located in the brain stem was activated due to the changes in stress and hormone levels during pregnancy, thus releasing a large number of NE to participate in the regulation of the nervous system, which was easy to cause tension and depression [24].…”

Section: Discussionmentioning

confidence: 99%

Effect of Single Intravenous Injection of Esketamine on Postpartum Depression after Labor Analgesia and Potential Mechanisms: A Randomized, Double-blinded Controlled Trial

Ling

Zhu

Yan

et al. 2023

Preprint

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Background：The study was designed to investigate effects of single intravenous injection of esketamine on the incidence of postpartum depression (PPD) after labor analgesia and explore the potential mechanisms. Methods：A total of 120 women who underwent labor analgesia by epidural analgesia pump were enrolled and divided into two groups randomly. Esketamine at a dose of 0.2 mg/kg was intravenously injected after fetal disengagement in the test group and placebo was administered in the control group. The occurrence of PPD and side effects after delivery were recorded. Some indicators related to stress and inflammation were measured before labor analgesia and at 24 hours, 1 week, and 6 weeks after delivery in this study. Data were analyzed by independent t-test, repeated measures analysis of variance and Chi-square test in SPSS software (version 25.0). It was considered statistically significant since a p value less than 0.05. Results：The incidence of PPD was significantly decreased both for one week and six weeks after delivery by using of esketamine (3.4% vs 15.3%, p = 0.004 and 5.2% vs 18.6%, p = 0.006, respectively) . There were also significant differences between the stress and inflammation-related indicators in different time points in this study, while the side effects for 48 hours after delivery were similar between the two groups. Conclusions：Single intravenous injection of esketamine after delivery in participants underwent labor analgesia can decrease the occurrence of postpartum depression for one week and six weeks after delivery, while the side effects were not increased. The antidepressant effects of esketamine may be related to the reduction of stress response and inflammation.

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Section: Discussionmentioning

confidence: 99%

Effect of Single Intravenous Injection of Esketamine on Postpartum Depression after Labor Analgesia and Potential Mechanisms: A Randomized, Double-blinded Controlled Trial

Ling

Zhu

Yan

et al. 2023

Preprint

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“…As a result, six compounds could be considered as novel NDRIs candidates for antidepressants including four compounds with high activities and two with balance actives acting on NET and DAT. This work supplied promising novel NDRIs for depression with cognitive dysfunction or other related neurodegenerative disorders and also shed new insight on identifying dual targets with a homological nontarget and was highly efficient and cost effective …”

Section: Drug Design Targeting Slcsmentioning

confidence: 95%

“…This work supplied promising novel NDRIs for depression with cognitive dysfunction or other related neurodegenerative disorders and also shed new insight on identifying dual targets with a homological nontarget and was highly efficient and cost effective. 219 Figure 8 depicts computer-aided drug design (CADD) tools including SBDD and ligand-based drug design (LBDD) that could be integrated with AI techniques to identify novel molecules that bind and modulate distinct conformations of target proteins like SLCs. In the past several decades, SBDD has been successfully used in developing drugs against many targets.…”

Section: ■ Drug Design Targeting Slcsmentioning

confidence: 99%

Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives

Tu,

Fu,

Zheng

et al. 2024

J. Chem. Inf. Model.

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Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a quarter of them are emerging as attractive therapeutic targets for multiple complex diseases, e.g., depression, cancer, and diabetes. However, only 44 unique transporters (∼9.8% of the SLC superfamily) with 3D structures and specific binding sites have been reported. To design innovative and effective drugs targeting diverse SLCs, there are a number of obstacles that need to be overcome. However, computational chemistry, including physics-based molecular modeling and machine learning-and deep learning-based artificial intelligence (AI), provides an alternative and complementary way to the classical drug discovery approach. Here, we present a comprehensive overview on recent advances and existing challenges of the computational techniques in structure-based drug design of SLCs from three main aspects: (i) characterizing multiple conformations of the proteins during the functional process of transportation, (ii) identifying druggability sites especially the cryptic allosteric ones on the transporters for substrates and drugs binding, and (iii) discovering diverse small molecules or synthetic protein binders targeting the binding sites. This work is expected to provide guidelines for a deep understanding of the structure and function of the SLC superfamily to facilitate rational design of novel modulators of the transporters with the aid of state-of-the-art computational chemistry technologies including artificial intelligence.

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“…After that, the produced ligand and the protein from the grid were put into the Ligand Docking window. Then, the most effective binding method of the active compound within the protein's binding site with the correct orientation was examined [18].…”

Section: Molecular Docking Through Maestro Schrödingermentioning

confidence: 99%

Structural Characterization and Molecular Docking Screening of Most Potent 1,2,4-Triazine Sulfonamide Derivatives as Anti-Cancer Agents

et al. 2023

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One of the biggest problems facing contemporary medicine is cancer. New approaches to therapy are required due to the difficult and prolonged treatment, the numerous adverse properties of the medications employed, and the developing confrontation of neoplastic cells to treatment. Ten 1,2,4-triazine sulfonamide derivatives (1–10) were chosen for the first time in the current work, and their chemical structures were examined by DFT studies. The in silico flexible docking analysis of the chosen receptors involved in cancer development and metastasis (3RHK, 5GTY, 6PL2, and 7JXH) revealed that the selected compounds are the most promising. The binding affinity of compounds 10, 2, 6, and 4 is much better than the standard drug, Erlotinib, whereas compounds 9, 3, 1, and 7 showed better affinities as compared to standard drugs Neratinib and Tepotinib in the case of 3RHK receptor. The binding affinity against the 5GTY receptor of compounds 10, 5, and 3 is much better than the standard drug Tepotinib, and compounds 7, 6, 2, 4, 1, 8, and 9 showed better than Erlonitib and Neratinib. The binding affinity against the 6PL2 receptor of compounds 8, 3, 5, 4, 9, and 1 is much better than the standard drug Tepotinib. Compounds 10, 6, 7, and 2 were better than Erlotinib and Neratinib. All selected drugs showed better binding affinities than the standard anti-cancer drug Neratinib in the case of the 7JXH receptor, whereas compounds 2, 10, 5, 9, and 8 are better than Erlotinib. In silico ADME experiments supported the identified compounds’ drug similarity. According to the MEP calculations, compounds 3 through 10 can interact non-covalently. The interactions might take the form of σ- and π-hole interactions. Softest compound 4 has the smallest energy gap, with an E-gap value of 3.25 Ev. Compound 4 has the largest energy gap at 3.41 eV. Compound 5 superior electron donor has the highest HOMO energy (6.5470 eV for HOMO). Compound 2 has the lowest LUMO energy, which suggests that it would be the best electron acceptor (ELUMO = 5.766364 eV).

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A multiple-step screening protocol to identify norepinephrine and dopamine reuptake inhibitors for depression

Abstract: Depression has severely impaired the health of the people all over the world. Cognitive dysfunction due to depression has exerted serious economic burden to family and society induced by the...

Cited by 7 publications

References 68 publications

Effect of Single Intravenous Injection of Esketamine on Postpartum Depression after Labor Analgesia and Potential Mechanisms: A Randomized, Double-blinded Controlled Trial

Effect of Single Intravenous Injection of Esketamine on Postpartum Depression after Labor Analgesia and Potential Mechanisms: A Randomized, Double-blinded Controlled Trial

Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives

Structural Characterization and Molecular Docking Screening of Most Potent 1,2,4-Triazine Sulfonamide Derivatives as Anti-Cancer Agents

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