College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Phys Chem Chem Phys. 2018 Nov 28;20(46):29513-29527. doi: 10.1039/c8cp06232c.
Human norepinephrine and serotonin transporters (hNET and hSERT) are closely related monoamine transporters (MATs) that regulate neurotransmitter signaling in neurons and are primary targets for a wide range of therapeutic drugs used in the treatment of mood disorders. The subtle modifications of an escitalopram scaffold exhibit distinct selective inhibition profiles of hNET and hSERT. However, the structural details of escitalopram scaffold binding to hSERT and (or) hNET are poorly understood and still remain a great challenge. In this work, on the basis of more recently solved X-ray crystallographic structure of hSERT in complex with escitalopram, 3 μs long all-atom MD simulations and binding free energy calculations via MM/GB(PB)SA, thermodynamic integration (TI) and MM/3D-RISM methods were performed to reproduce experimental free energies. And both MM/GBSA and TI have a high correlation coefficient (R2 = 0.95 and 0.96, respectively) between the relative binding free energies of the calculated and experimental values. Furthermore, MM/GBSA per-residue energy decomposition, molecular interaction fingerprints and thermodynamics-structure relationship analysis were employed to investigate and characterize the selectivity of the escitalopram scaffold with three modifications (escitalopram, ligand10 and talopram) to hNET and hSERT. As a result, 4 warm spots (A73, Y151, A477 and I481) in hNET and 4 warm spots (A96, A173, T439 and L443) in hSERT were thus discovered to exert a pronounced effect on the selective inhibition of hNET and hSERT by the studied ligands. These simulation results would provide great insight into the design of inhibitors with the desired selectivity to hNET and hSERT, thus further promoting the research of more efficacious antidepressants.
人去甲肾上腺素和 5-羟色胺转运体（hNET 和 hSERT）是密切相关的单胺转运体（MATs），它们调节神经元中的神经递质信号传递，是广泛用于治疗情绪障碍的治疗药物的主要靶点。依地普仑骨架的细微修饰表现出对 hNET 和 hSERT 的独特选择性抑制特征。然而，依地普仑骨架与 hSERT 和（或）hNET 结合的结构细节知之甚少，仍然是一个巨大的挑战。在这项工作中，基于最近解决的 hSERT 与依地普仑复合物的 X 射线晶体结构，进行了 3 μs 长的全原子 MD 模拟和通过 MM/GB(PB)SA、热力学积分（TI）和 MM/3D-RISM 方法计算的结合自由能，以重现实验自由能。并且 MM/GBSA 和 TI 之间都具有计算值和实验值之间相对结合自由能的高相关系数（R2 分别为 0.95 和 0.96）。此外，采用 MM/GBSA 逐残基能量分解、分子相互作用指纹和热力学-结构关系分析，研究并表征了依地普仑骨架与三种修饰物（依地普仑、配体 10 和他普仑）对 hNET 和 hSERT 的选择性。结果，发现 hNET 中的 4 个热点（A73、Y151、A477 和 I481）和 hSERT 中的 4 个热点（A96、A173、T439 和 L443）对研究配体对 hNET 和 hSERT 的选择性抑制具有显著影响。这些模拟结果将为设计对 hNET 和 hSERT 具有所需选择性的抑制剂提供重要见解，从而进一步推动更有效的抗抑郁药的研究。
