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新型抗抑郁药物的设计策略。

New design strategies for antidepressant drugs.

机构信息

Duquesne University, Center for Computational Sciences, Department of Chemistry and Biochemistry , 600 Forbes Ave, 308 Mellon Hall, Pittsburgh, PA 15282 , USA +1 412 396 4129 ; +1 412 396 5683 ;

出版信息

Expert Opin Drug Discov. 2013 Nov;8(11):1399-414. doi: 10.1517/17460441.2013.830102. Epub 2013 Aug 31.

Abstract

INTRODUCTION

In spite of research efforts spanning six decades, the most prominent antidepressant drugs to date still carry several adverse effects, often serious enough to warrant discontinuation of the drug. Molecular mechanisms of depression are now better understood such that some of the specific receptors responsible can be targeted for activation or inhibition. This advance, coupled with the recent availability of crystal structures of relevant drug targets or their homologs, has opened the door for new antidepressant therapeutic compounds.

AREAS COVERED

The authors review the evolution of monoamine-based antidepressant drugs, up to the selective serotonin reuptake inhibitors (SSRIs). The authors discuss classic and contemporary antidepressant drug design strategies, with a focus on virtual screening and fragment-based drug design methods. Furthermore, they discuss the recent advancements in the understanding of the serotonin transporter (SERT) structure/function relationship in the context of recognition of SSRIs and outline a strategy for the use of computational approaches in producing new SSRI lead compounds.

EXPERT OPINION

The authors suggest that given the long-awaited availability of credible three-dimensional structures for the SERT and related monoamine transporter proteins, cutting-edge computational methods should be the linchpin of future drug discovery efforts regarding monoamine-based antidepressant lead compounds. Because these transporter inhibitors cause a ubiquitous increase in extraneuronal neurotransmitter levels leading to side and adverse therapeutic effects, the drug discovery should extend to appropriate manipulation of the 'downstream' receptors affected by the neurotransmitter boost. Efficient use of new computational strategies will accelerate the drug discovery process and reduce its economic burden.

摘要

简介

尽管六十年的研究努力,迄今为止最突出的抗抑郁药物仍存在几种不良反应,严重到足以停止药物使用。抑郁症的分子机制现在理解得更好,以至于一些特定的受体可以被激活或抑制。这一进步,加上最近相关药物靶点或其同源物的晶体结构的可用性,为新的抗抑郁治疗化合物打开了大门。

涵盖领域

作者回顾了单胺类抗抑郁药物的发展,直至选择性 5-羟色胺再摄取抑制剂(SSRIs)。作者讨论了经典和当代抗抑郁药物设计策略,重点是虚拟筛选和基于片段的药物设计方法。此外,他们讨论了在理解 5-羟色胺转运蛋白(SERT)结构/功能关系方面的最新进展,以了解 SSRIs 的识别,并概述了在产生新的 SSRIs 先导化合物方面使用计算方法的策略。

专家意见

作者认为,鉴于 SERT 和相关单胺转运蛋白的可靠三维结构的长期期待已久的可用性,前沿的计算方法应该是未来单胺类抗抑郁先导化合物药物发现努力的关键。由于这些转运体抑制剂导致普遍增加了神经递质水平,导致副作用和不良治疗效果,因此药物发现应该扩展到对受神经递质促进影响的“下游”受体的适当操纵。新的计算策略的有效利用将加速药物发现过程并降低其经济负担。

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