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Consensus scoring for enriching near-native structures from protein–protein docking decoys

机译:从蛋白质-蛋白质对接诱饵丰富近邻结构的共识评分

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摘要

The identification of near native protein-protein complexes among a set of decoys remains highly challenging. A strategy for improving the success rate of near native detection is to enrich near native docking decoys in a small number of top ranked decoys. Recently, we found that a combination of three scoring functions (energy, conservation, and interface propensity) can predict the location of binding interface regions with reasonable accuracy. Here, these three scoring functions are modified and combined into a consensus scoring function called ENDES for enriching near native docking decoys. We found that all individual scores result in enrichment for the majority of 28 targets in ZDOCK2.3 decoy set and the 22 targets in Benchmark 2.0. Among the three scores, the interface propensity score yields the highest enrichment in both sets of protein complexes. When these scores are combined into the ENDES consensus score, a significant increase in enrichment of near-native structures is found. For example, when 2000 dock decoys are reduced to 200 decoys by ENDES, the fraction of near-native structures in docking decoys increases by a factor of about six in average.
机译:在一组诱饵中鉴定近乎天然的蛋白质-蛋白质复合物仍然具有很高的挑战性。提高近本机检测成功率的策略是在少数排名靠前的诱饵中增加近本机对接诱饵。最近,我们发现三个评分功能(能量,守恒和界面倾向)的组合可以以合理的准确性预测结合界面区域的位置。在这里,这三个评分函数被修改并合并到一个称为ENDES的共识评分函数中,以丰富本机对接诱饵。我们发现,所有单独的分数都会导致ZDOCK2.3诱饵集中的大多数28个目标和Benchmark 2.0中的22个目标的富集。在这三个分数中,界面倾向分数在两组蛋白质复合物中均产生最高的富集。将这些分数合并为ENDES共识分数时,发现近自然结构的富集度显着增加。例如,当通过ENDES将2000个对接诱饵减少到200个诱饵时,对接诱饵中近自然结构的比例平均增加大约六倍。

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