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首页> 外文期刊>Journal of Molecular Biology >ProMate: A Structure Based Prediction Program to Identify the Location of Protein-Protein Binding Sites.
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ProMate: A Structure Based Prediction Program to Identify the Location of Protein-Protein Binding Sites.

机译：ProMate：一种基于结构的预测程序，用于识别蛋白质-蛋白质结合位点的位置。

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Is the whole protein surface available for interaction with other proteins, or are specific sites pre-assigned according to their biophysical and structural character? And if so, is it possible to predict the location of the binding site from the surface properties? These questions are answered quantitatively by probing the surfaces of proteins using spheres of radius of 10A on a database (DB) of 57 unique, non-homologous proteins involved in heteromeric, transient protein-protein interactions for which the structures of both the unbound and bound states were determined. In structural terms, we found the binding site to have a preference for beta-sheets and for relatively long non-structured chains, but not for alpha-helices. Chemically, aromatic side-chains show a clear preference for binding sites. While the hydrophobic and polar content of the interface is similar to the rest of the surface, hydrophobic and polar residues tend to cluster in interfaces. In the crystal, the binding site has more boundwater molecules surrounding it, and a lower B-factor already in the unbound protein. The same biophysical properties were found to hold for the unbound and bound DBs. All the significant interface properties were combined into ProMate, an interface prediction program. This was followed by an optimization step to choose the best combination of properties, as many of them are correlated. During optimization and prediction, the tested proteins were not used for data collection, to avoid over-fitting. The prediction algorithm is fully automated, and is used to predict the location of potential binding sites on unbound proteins with known structures. The algorithm is able to successfully predict the location of the interface for about 70% of the proteins. The success rate of the predictor was equal whether applied on the unbound DB or on the disjoint bound DB. A prediction is assumed correct if over half of the predicted continuous interface patch is indeed interface. The ability to predict the location of protein-protein interfaces has far reaching implications both towards our understanding of specificity and kinetics of binding, as well as in assisting in the analysis of the proteome.
机译：整个蛋白质表面是否可与其他蛋白质相互作用，或者根据其生物物理和结构特征预先指定了特定位点？如果是这样，是否可以根据表面性质预测结合位点的位置？通过在10个半径为球形的蛋白质表面上探查蛋白质表面，定量地回答了这些问题，该数据库包含57个独特，非同源蛋白质，涉及异源，瞬时蛋白质-蛋白质相互作用，其中未结合和结合的结构均如此确定状态。在结构上，我们发现结合位点对β-折叠和相对长的非结构化链有偏好，但对α-螺旋则没有偏好。化学上，芳族侧链显示出明显优先的结合位点。尽管界面的疏水性和极性含量与表面的其余部分相似，但疏水性和极性残基倾向于聚集在界面中。在晶体中，结合位点周围有更多的结合水分子，而未结合的蛋白质中已经有较低的B因子。发现相同的生物物理性质适用于未结合和结合的DB。所有重要的接口属性都组合到接口预测程序ProMate中。接下来是优化步骤，以选择最佳的属性组合，因为许多属性是相关的。在优化和预测过程中，测试的蛋白质不用于数据收集，以避免过度拟合。该预测算法是完全自动化的，并且用于预测具有已知结构的未结合蛋白上潜在结合位点的位置。该算法能够成功预测约70％的蛋白质的界面位置。无论应用于未绑定DB还是不相交绑定DB，预测器的成功率均相等。如果超过一半的预测连续界面补丁确实是界面，则认为该预测是正确的。预测蛋白质-蛋白质界面位置的能力对我们对结合的特异性和动力学的理解，以及对蛋白质组分析的协助具有深远的意义。

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