Neuvirth Hani, Raz Ran, Schreiber Gideon
Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100 Israel.
J Mol Biol. 2004 Apr 16;338(1):181-99. doi: 10.1016/j.jmb.2004.02.040.
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 10 A 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 bound water 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.
整个蛋白质表面都可用于与其他蛋白质相互作用，还是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，是否有可能从表面性质预测结合位点的位置？通过在一个包含57种独特的、非同源蛋白质的数据库（DB）上使用半径为10埃的球体探测蛋白质表面，定量回答了这些问题。这些蛋白质参与异源三聚体、瞬时蛋白质-蛋白质相互作用，且已确定了未结合状态和结合状态的结构。从结构角度来看，我们发现结合位点偏好β-折叠和相对较长的无结构链，但不偏好α-螺旋。从化学角度来看，芳香族侧链对结合位点表现出明显的偏好。虽然界面的疏水和极性含量与表面的其他部分相似，但疏水和极性残基倾向于在界面处聚集。在晶体中，结合位点周围有更多的结合水分子，并且未结合蛋白质中的B因子已经较低。未结合和结合的数据库都具有相同的生物物理性质。所有重要的界面性质都被整合到ProMate，一个界面预测程序中。接下来是一个优化步骤，以选择最佳的性质组合，因为其中许多性质是相关的。在优化和预测过程中，测试蛋白质不用于数据收集，以避免过度拟合。预测算法是完全自动化的，用于预测具有已知结构的未结合蛋白质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。无论应用于未结合的数据库还是不相交的结合数据库，预测器的成功率都是相等的。如果预测的连续界面补丁超过一半确实是界面，则认为预测是正确的。预测蛋白质-蛋白质界面位置的能力对于我们理解结合的特异性和动力学以及辅助蛋白质组分析都具有深远的意义。
