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Venn-Abers predictors for improved compound iterative screening in drug discovery

机译:Venn-abers预测因素,用于改善药物发现中的复合迭代筛选

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Iterative screening, where selected hits from a given round of screening are used to enrich a compound activity prediction model for the next iteration, enables more efficient screening campaigns. The portion of the compound library that should be screened in each iteration is often arbitrarily decided. This is because no accurate information between screening size and the number of hits to be retrieved exists. In this article, a novel method based on Venn-Abers predictors was used to determine the optimal number of compounds to be screened in order to get a desired number of hits. We found that Venn-Abers predictors provide accurate information to support a reliable and flexible decision about the portion size of the compound library that should be screened in each iteration. In addition, the method exhibited great ability in producing an enriched subset in terms of hits and their diversity.
机译:迭代筛选,其中来自给定圆形筛选的所选命中用于丰富化合物活性预测模型,用于下一步迭代,使得更有效的筛选活动。应该在每次迭代中筛选的复合文库的部分通常是任意决定的。这是因为没有准确的筛选大小与要检索的命中次数之间的信息。在本文中,使用基于Venn-abers预测器的新方法来确定要筛选的最佳化合物,以获得所需的次数。我们发现Venn-abers预测器提供准确的信息,以支持关于在每次迭代中应筛选的复合库的部分尺寸的可靠和灵活的决定。此外,该方法表现出在击中和其多样性方面产生丰富的子集的能力。

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