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促肾上腺皮质激素释放因子 1 拮抗剂的 3D-QSAR 研究及基于药效团的药物设计。

3D-QSAR study of corticotropin-releasing factor 1 antagonists and pharmacophore-based drug design.

机构信息

Tianjin Key Laboratory for Modern Drug Delivery & High-Efficiency, School of Pharmaceutical Science and Technology, Tianjin University, Nankai District, Tianjin, PR China.

出版信息

Neurochem Int. 2010 Jan;56(1):107-17. doi: 10.1016/j.neuint.2009.09.008. Epub 2009 Sep 24.

Abstract

Corticotropin-releasing factor (CRF) is a neuropeptide that falls into the broad spectrum of having neurotransmitter/neurohormonal/neuromodulator activities. The design and synthesis of low molecular weight non-peptide antagonists for the CRF receptors is a very important area of research as they can be employed in the treatment of a wide variety of disorders. To investigate the ligand-receptor binding mode and design novel CRF1 antagonists, both quantitative and qualitative 3D-QSAR analysis have been performed on a data set of CRF(1) antagonists by using HypoGen and HipHopRefine programs of Catalyst software. The training set of HypoGen study included twenty-five structurally diverse CRF(1) antagonists with Ki values ranging from 0.5 nM to 10 microM. The common feature-based 3D-QSAR study used eight highly potent CRF(1) antagonists and four poor antagonistic ligands to generate 3D-pharmacophore models with excluded volumes. The obtained 3D-pharmacophore models from each study served as queries for virtual screening with a 'focused compound library' for novel CRF(1) antagonist development. Pharmacophore models obtained for antagonist binding are useful for CRF related chemical biology and drug design. Strategies and methods employed in this paper are simple and practical for medicinal chemists in drug R&D.

摘要

促肾上腺皮质释放因子(CRF)是一种神经肽,具有广泛的神经递质/神经激素/神经调质活性。CRF 受体的低分子量非肽拮抗剂的设计和合成是一个非常重要的研究领域,因为它们可用于治疗多种疾病。为了研究配体-受体结合模式并设计新型 CRF1 拮抗剂,我们使用 Catalyst 软件的 HypoGen 和 HipHopRefine 程序对一组 CRF(1)拮抗剂进行了定量和定性的 3D-QSAR 分析。HypoGen 研究的训练集包括 25 种结构多样的 CRF(1)拮抗剂,Ki 值范围为 0.5 nM 至 10 μM。基于共有特征的 3D-QSAR 研究使用了 8 种高活性的 CRF(1)拮抗剂和 4 种拮抗作用差的配体,生成了具有排除体积的 3D 药效团模型。从每个研究中获得的 3D 药效团模型都用作虚拟筛选的查询,以开发新型 CRF(1)拮抗剂的“重点化合物库”。用于结合拮抗剂的药效团模型可用于 CRF 相关的化学生物学和药物设计。本文中使用的策略和方法对于药物研发中的药物化学家来说简单实用。

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