Evaluation of the utility of homology models in high throughput docking
Evaluation of the utility of homology models in high throughput docking
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DOI：
10.1007/s00894-007-0207-6
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发表时间：
2007-08-01
影响因子：
2.2
通讯作者：
Jacoby, Edgar
中科院分区：
文献类型：
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作者：
Ferrara, Philippe;Jacoby, Edgar
高通量对接 (HTD) 通常用于化合物库的计算机筛选，目的是在药物发现计划中寻找新的先导化合物。在缺乏实验确定的结构的情况下，可以使用同源模型来代替。在这里，我们通过将 300,000 种预期的无活性化合物以及 642 种已知活性物质对接至通过同源模型构建的胰岛素样生长因子 1 受体 (IGF-1R) 激酶的结合位点，对 HTD 中的同源模型的实用性进行了评估。选择二十一种不同的模板，并将同源模型获得的富集曲线与三种IGF-1R晶体结构获得的富集曲线进行比较。结果显示，富集范围很广，从随机到三种 IGF-1R 晶体结构中的两种。然而，如果我们将筛选数据库的 2% 获得的富集视为性能标准，则最佳晶体结构优于最佳同源模型。令人惊讶的是，模板与靶标的序列同一性并不是预测同源模型获得的富集的良好描述符。产生最差富集的三个同源模型具有最小的结合位点体积。根据我们的结果，我们建议通过同源模型进行集成对接来执行 HTD。
High throughput docking (HTD) is routinely used for in silico screening of compound libraries with the aim to find novel leads in a drug discovery program. In the absence of an experimentally determined structure, a homology model can be used instead. Here we present an assessment of the utility of homology models in HTD by docking 300,000 anticipated inactive compounds along with 642 known actives into the binding site of the insulin-like growth factor 1 receptor (IGF-1R) kinase constructed by homology modeling. Twenty-one different templates were selected and the enrichment curves obtained by the homology models were compared to those obtained by three IGF-1R crystal structures. The results show a wide range of enrichments from random to as good as two of the three IGF-1R crystal structures. Nevertheless, if we consider the enrichment obtained at 2% of the database screened as a performance criterion, the best crystal structure outperforms the best homology model. Surprisingly, the sequence identity of the template to the target is not a good descriptor to predict the enrichment obtained by a homology model. The three homology models that yield the worst enrichment have the smallest binding-site volume. Based on our results, we propose ensemble docking to perform HTD with homology models.