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Analysis of structure-based virtual screening studies and characterization of identified active compounds

机译:基于结构的虚拟筛选研究分析和鉴定的活性化合物的表征

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Structure-based virtual screening makes explicit or implicit use of 3D target structure information to detect novel active compounds. Results of nearly 300 currently available original applications have been analyzed to characterize the state-of-the-art in this field. Compound selection from docking calculations is much influenced by subjective criteria. Although submicromolar compounds are identified, the majority of docking hits are only weakly potent. However, only a small percentage of docking hits can be reproduced by ligand-based methods. When docking calculations identify potent hits, they often originate from specialized compound sources (e.g., pharmaceutical compound decks or target-focused libraries) and also display a notable bias towards kinase targets. Structure-based virtual screening is the dominant approach to computational hit identification. Docking calculations frequently identify active compounds. Limited accuracy of compound scoring and ranking currently presents a major caveat of the approach that is often compensated for by chemical intuition and knowledge.
机译:基于结构的虚拟筛选可显式或隐式使用3D目标结构信息来检测新型活性化合物。分析了近300种当前可用的原始应用程序的结果,以表征该领域的最新技术。对接计算中的化合物选择受主观标准的影响很大。尽管已鉴定出亚微摩尔化合物,但大多数对接命中的作用都较弱。但是,基于配体的方法只能复制一小部分的对接命中。当对接计算确定有效命中时,它们通常来自专门的化合物来源(例如,药物化合物套组或针对靶标的文库),并且对激酶靶标也表现出明显的偏倚。基于结构的虚拟筛选是计算命中识别的主要方法。对接计算经常确定活性化合物。目前,化合物评分和排名的准确性有限,这给该方法带来了很大的警告,通常需要通过化学直觉和知识来弥补。

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