药效团
抗抑郁药
效力
医学
药理学
萧条(经济学)
结合亲和力
计算生物学
神经科学
精神科
生物信息学
心理学
生物
受体
生物化学
内科学
体外
焦虑
经济
宏观经济学
作者
Kunal Singh,Rohit Bhatia,Bhupinder Kumar,Gurpreet Singh,Vikramdeep Monga
出处
期刊:Current Neuropharmacology
[Bentham Science]
日期:2022-07-01
卷期号:20 (7): 1329-1358
被引量:6
标识
DOI:10.2174/1570159x19666211102154311
摘要
: Depression is one of the major disorders of the central nervous system worldwide and causes disability and functional impairment. According to the World Health Organization, around 265 million people worldwide are affected by depression. Currently marketed antidepressant drugs take weeks or even months to show anticipated clinical efficacy but remain ineffective in treating suicidal thoughts and cognitive impairment. Due to the multifactorial complexity of the disease, single-target drugs do not always produce satisfactory results and lack the desired level of therapeutic efficacy. Recent literature reports have revealed improved therapeutic potential of multi-target directed ligands due to their synergistic potency and better safety. Medicinal chemists have gone to great extents to design multitarget ligands by generating structural hybrids of different key pharmacophores with improved binding affinities and potency towards different receptors or enzymes. This article has compiled the design strategies of recently published multi-target directed ligands as antidepressant agents. Their biological evaluation, structural-activity relationships, mechanistic and in silico studies have also been described. This article will prove to be highly useful for the researchers to design and develop multi-target ligands as antidepressants with high potency and therapeutic efficacy.
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