首页> 外文期刊>Journal of Bioinformatics and Computational Biology >DEVELOPMENT OF AN AFFINITY EVALUATION AND PREDICTION SYSTEM BY USING THE SHAPE COMPLEMENTARITY CHARACTERISTIC BETWEEN PROTEINS
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DEVELOPMENT OF AN AFFINITY EVALUATION AND PREDICTION SYSTEM BY USING THE SHAPE COMPLEMENTARITY CHARACTERISTIC BETWEEN PROTEINS

机译:利用蛋白质之间的形状互补特征开发亲和力评估与预测系统

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摘要

A system was developed to evaluate and predict the interaction between protein pairs by using the widely used shape complementarity search method as the algorithm for docking simulations between the proteins This system, which we call the affinity evaluation and prediction (AEP) system, was used to evaluate the interaction between 20 protein pairs The system first executes a "round robin" shape complementarity search of the target protein group, and evaluates the interaction of the complex structures obtained by shape complementarity search These complex structures are selected by using a statistical procedure that we developed called "grouping". At a low prevalence of 5 0%, our AEP system predicted protein-protein interaction with 65.0% recall, 15 1% precision, 80 0% accuracy, and had an area under the curve (AUC) of 0 74, By optimizing the grouping process, our AEP system successfully predicted 13 protein pairs (among 20 pairs) that were biologically significant combinations Our ultimate goal is to construct an affinity database that will provide crucial information obtained using our AEP system to cell biologists and drug designers.
机译:通过使用广泛使用的形状互补性搜索方法作为蛋白质之间对接模拟的算法,开发了一种评估和预测蛋白质对之间相互作用的系统。该系统被称为亲和力评估和预测(AEP)系统,用于评估20个蛋白质对之间的相互作用系统首先对目标蛋白质组执行“循环”形状互补性搜索,并评估通过形状互补性搜索获得的复杂结构的相互作用。开发称为“分组”。在5 0%的低患病率下,我们的AEP系统通过65.0%的查全率,15 1%的准确性,80 0%的准确性预测蛋白质-蛋白质相互作用,并且通过优化分组具有0 74的曲线下面积(AUC)在这一过程中,我们的AEP系统成功地预测了13对蛋白质(其中20对是生物学上重要的组合)。我们的最终目标是构建一个亲和力数据库,该数据库将向细胞生物学家和药物设计人员提供使用AEP系统获得的重要信息。

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