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首页> 外文期刊>Journal of Medicinal Chemistry >Nuclear Hormone Receptor Targeted Virtual Screening
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Nuclear Hormone Receptor Targeted Virtual Screening

机译:核激素受体靶向虚拟筛选

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摘要

Virtual library screening (VLS) is emerging as a valuable drug lead discovery tool. ICM-VLS implementation of this technology was evaluated on a benchmark set of nuclear hormone receptors (NRs), an important therapeutic target family. Over 5000 structurally diverse compounds, including 78 known NR ligands, were screened against 18 crystal structures and one computer model of 10 NR ligand binding domains in their active or inactive states. The results confirm the ability of the VLS method to generate highly focused subsets of the input chemical library, enriched 33- to 100-fold for all but one receptor studied. However, receptor flexibility remains to be fully addressed, and the choice of the specific conformation used for screening may determine the success of the exercise. We observe that for a particular ligand VLS can often identify the correct target within the receptor family, although the technology is unable to reliably discriminate between the closely related receptor isoforms. Additionally, our results suggest that VLS may be applied successfully without an experimental structure of the receptor by using a homology model. These data represent a realistic snapshot of the state-of-the-art of NR-targeted VLS and define the recent progress and the remaining limitations of the technology.
机译:虚拟图书馆筛选(VLS)逐渐成为一种有价值的药物线索发现工具。该技术的ICM-VLS实施情况是根据一组重要的治疗靶标家族核激素受体(NRs)进行评估的。针对18种晶体结构和10种处于活性或非活性状态的NR配体结合域的计算机模型,筛选了5000多种结构多样的化合物,包括78个已知的NR配体。结果证实了VLS方法能够生成输入化学文库的高度集中子集的能力,除了研究的一种受体外,其富集了33至100倍。然而,受体的柔韧性仍有待充分解决,用于筛选的特定构象的选择可能决定这项运动的成功。我们观察到,对于特定的配体,VLS通常可以识别受体家族中的正确靶标,尽管该技术无法可靠地区分紧密相关的受体同工型。此外,我们的结果表明,通过使用同源性模型,可以在没有受体的实验结构的情况下成功应用VLS。这些数据代表了以NR为目标的VLS的最新技术的真实快照,并定义了该技术的最新进展和剩余限制。

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