利用受体诱饵结合位点的新型虚拟筛选策略的评价。

Hershna Patel, Andreas Kukol
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引用次数: 0

摘要

虚拟筛选在生物医学研究中用于预测大量有机小分子与蛋白质受体靶点的结合亲和力。本报告展示了利用受体-诱饵策略提高基于受体的分子对接排名的一种新颖而直接的尝试的发展和评估。该策略包括在受体上定义一个诱饵结合位点,并根据诱饵结合位点屏幕调整真实结合位点虚拟屏幕的排名。结果表明,通过与Autodock Vina对接受体-诱饵位点,当考虑高达15%的诱饵位点等级列表时,所研究的15个受体靶标中有5个实现了改进的接收器算子特征富集(ROCE)。7个目标没有改善富集,而3个目标的ROCE降低。该策略能有效改善配体预测的程度取决于所研究的靶受体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Evaluation of a novel virtual screening strategy using receptor decoy binding sites.

Evaluation of a novel virtual screening strategy using receptor decoy binding sites.

Virtual screening is used in biomedical research to predict the binding affinity of a large set of small organic molecules to protein receptor targets. This report shows the development and evaluation of a novel yet straightforward attempt to improve this ranking in receptor-based molecular docking using a receptor-decoy strategy. This strategy includes defining a decoy binding site on the receptor and adjusting the ranking of the true binding-site virtual screen based on the decoy-site screen. The results show that by docking against a receptor-decoy site with Autodock Vina, improved Receiver Operator Characteristic Enrichment (ROCE) was achieved for 5 out of fifteen receptor targets investigated, when up to 15 % of a decoy site rank list was considered. No improved enrichment was seen for 7 targets, while for 3 targets the ROCE was reduced. The extent to which this strategy can effectively improve ligand prediction is dependent on the target receptor investigated.

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