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未知的预测:CAPRI实验的启发性经验

Prediction of the unknown: inspiring experience with the CAPRI experiment.

作者信息

Ben-Zeev Efrat, Berchanski Alexander, Heifetz Alexander, Shapira Boaz, Eisenstein Miriam

机构信息

Department of Biological Chemistry, The Weizmann Institute of Science, Rehovot, Israel.

出版信息

Proteins. 2003 Jul 1;52(1):41-6. doi: 10.1002/prot.10392.

Abstract

We submitted predictions for all seven targets in the CAPRI experiment. For four targets, our submitted models included acceptable, medium accuracy predictions of the structures of the complexes, and for a fifth target we identified the location of the binding site of one of the molecules. We used a weighted-geometric docking algorithm in which contacts involving specified parts of the surfaces of either one or both molecules were up-weighted or down-weighted. The weights were based on available structural and biochemical data or on sequence analyses. The weighted-geometric docking proved very useful for five targets, improving the complementarity scores and the ranks of the nearly correct solutions, as well as their statistical significance. In addition, the weighted-geometric docking promoted formation of clusters of similar solutions, which include more accurate predictions.

摘要

我们提交了CAPRI实验中所有七个靶标的预测结果。对于四个靶标,我们提交的模型包含了对复合物结构可接受的、中等准确性的预测,对于第五个靶标,我们确定了其中一个分子结合位点的位置。我们使用了一种加权几何对接算法,其中涉及一个或两个分子表面特定部分的接触被加权上调或下调。权重基于可用的结构和生化数据或序列分析。加权几何对接被证明对五个靶标非常有用,提高了互补性得分、接近正确解决方案的排名及其统计显著性。此外,加权几何对接促进了相似解决方案簇的形成,其中包括更准确的预测。

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