Understanding the Polypharmacological Profiles of Triple Reuptake Inhibitors by Molecular Simulation

医学 药理学
作者
Gao Tu,Tingting Fu,Fengyuan Yang,H. J. Yang,Zhao Zhang,Xiaojun Yao,Weiwei Xue,Feng Zhu
出处
期刊:ACS Chemical Neuroscience [American Chemical Society]
卷期号:12 (11): 2013-2026 被引量:20
标识
DOI:10.1021/acschemneuro.1c00127
摘要

The triple reuptake inhibitors (TRIs) class is a class of effective inhibitors of human monoamine transporters (hMATs), which includes dopamine, norepinephrine, and serotonin transporters (hDATs, hNETs, and hSERTs). Due to the high degree of structural homology of the binding sites of those transporters, it is a great challenge to design potent TRIs with fine-tuned binding profiles. The molecular determinants responsible for the binding selectivity of TRIs to hDATs, hNETs, and hSERTs remain elusive. In this study, the solved X-ray crystallographic structure of hSERT in complex with escitalopram was used as a basis for modeling nine complexes of three representative TRIs (SEP225289, NS2359, and EB1020) bound to their corresponding targets. Molecular dynamics (MD) and effective post-trajectory analysis were performed to estimate the drug binding free energies and characterize the selective profiles of each TRI to hMATs. The common binding mode of studied TRIs to hMATs was revealed by hierarchical clustering analysis of the per-residue energy. Furthermore, the combined protein-ligand interaction fingerprint and residue energy contribution analysis indicated that several conserved and nonconserved "Warm Spots" such as S149, V328, and M427 in hDAT, F317, F323, and V325 in hNET and F335, F341, and V343 in hSERT were responsible for the TRI-binding selectivity. These findings provided important information for rational design of a single drug with better polypharmacological profiles through modulating multiple targets.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
木子完成签到,获得积分10
1秒前
1秒前
通行证发布了新的文献求助10
1秒前
2秒前
3秒前
devilito完成签到,获得积分10
3秒前
Memory_H完成签到,获得积分10
3秒前
成就含玉完成签到,获得积分10
3秒前
cck1ckass完成签到,获得积分20
4秒前
Lucas应助快乐的小懒虫采纳,获得10
4秒前
清脆的梦寒完成签到,获得积分10
4秒前
健壮尔丝发布了新的文献求助10
4秒前
俏皮道之完成签到,获得积分10
4秒前
jxwxxxx发布了新的文献求助10
4秒前
顾矜应助猹c采纳,获得10
5秒前
6秒前
ding应助devilito采纳,获得10
6秒前
小二郎应助Memory_H采纳,获得10
7秒前
积极聋五发布了新的文献求助10
7秒前
ricardo发布了新的文献求助10
8秒前
隐形曼青应助科研通管家采纳,获得10
8秒前
现代的白桃完成签到,获得积分10
8秒前
8秒前
Lucas应助科研通管家采纳,获得10
8秒前
共享精神应助科研通管家采纳,获得10
8秒前
8秒前
HYC完成签到,获得积分10
8秒前
8秒前
CR7应助科研通管家采纳,获得20
8秒前
NexusExplorer应助科研通管家采纳,获得10
8秒前
天天快乐应助科研通管家采纳,获得10
8秒前
Akim应助科研通管家采纳,获得10
8秒前
搜集达人应助科研通管家采纳,获得10
8秒前
隐形曼青应助科研通管家采纳,获得10
8秒前
李健应助科研通管家采纳,获得10
8秒前
牧万万应助科研通管家采纳,获得10
8秒前
8秒前
9秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Introduction to Helicopter and Tiltrotor Flight Simulation, Second Edition 2500
卤化钙钛矿人工突触的研究 2000
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6502097
求助须知:如何正确求助?哪些是违规求助? 8296804
关于积分的说明 17707392
捐赠科研通 5599737
什么是DOI,文献DOI怎么找? 2918929
邀请新用户注册赠送积分活动 1896109
关于科研通互助平台的介绍 1757419