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Phys Chem Chem Phys. 2016 Jan 28;18(4):3260-71. doi: 10.1039/c5cp05771j.

Identification of the inhibitory mechanism of FDA approved selective serotonin reuptake inhibitors: an insight from molecular dynamics simulation study.

Author information

Innovative Drug Research and Bioinformatics Group, Innovative Drug Research Centre and College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 401331, China.
State Key Laboratory of Applied Organic Chemistry and Department of Chemistry, Lanzhou University, Lanzhou 730000, China.
Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore 117543, Singapore.
College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300071, China.


Antidepressants selectively inhibiting serotonin reuptake (SSRIs) represent a highly effective drug class, and novel therapeutic strategies were proposed to improve SSRIs' drug efficacy. The knowledge of the inhibitory mechanism of FDA approved SSRIs could provide great insights and act as important starting points to discover privileged drug scaffolds with improved efficacy. However, the structure of human serotonin transporter (hSERT) is yet to be determined and the inhibitory mechanism underlying SSRIs still needs to be further explored. In this study, the inhibitory mechanism of 4 approved SSRIs treating major depression (fluoxetine, sertraline, paroxetine and escitalopram) was identified by integrating multiple computational methods. Firstly, a recently published template with high sequence identity was adopted for the first time to generate hSERT's homology model. Then, docking poses of 4 SSRIs were used as the initial conformation for molecular dynamics (MD) simulation followed by MM/GBSA binding free energy calculation and per-residue free energy decomposition. Finally, the binding mode shared by the 4 studied SSRIs was identified by hierarchically clustering per-residue free energies. The identified binding mode was composed of collective interactions between 3 chemical groups in SSRIs and 11 hot spot residues in hSERT. 6 out of these 11 were validated by previous mutagenesis studies or pharmacophore models, and the remaining 5 (Ala169, Ala173, Thr439, Gly442 and Leu443) found in this work were not yet been identified as common determinants of all the 4 studied SSRIs in binding hSERT. Moreover, changes in SSRIs' binding induced by mutation on hot spot residues were further explored, and 3 mechanisms underlining their drug sensitivity were summarized. In summary, the identified binding mode provided important insights into the inhibitory mechanism of approved SSRIs treating major depression, which could be further utilized as a framework for assessing and discovering novel lead scaffolds.

[Indexed for MEDLINE]

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