Fundación Instituto Leloir, Buenos Aires, Argentina.
PLoS Comput Biol. 2010 Nov 4;6(11):e1000978. doi: 10.1371/journal.pcbi.1000978.
Identification of catalytic residues (CR) is essential for the characterization of enzyme function. CR are, in general, conserved and located in the functional site of a protein in order to attain their function. However, many non-catalytic residues are highly conserved and not all CR are conserved throughout a given protein family making identification of CR a challenging task. Here, we put forward the hypothesis that CR carry a particular signature defined by networks of close proximity residues with high mutual information (MI), and that this signature can be applied to distinguish functional from other non-functional conserved residues. Using a data set of 434 Pfam families included in the catalytic site atlas (CSA) database, we tested this hypothesis and demonstrated that MI can complement amino acid conservation scores to detect CR. The Kullback-Leibler (KL) conservation measurement was shown to significantly outperform both the Shannon entropy and maximal frequency measurements. Residues in the proximity of catalytic sites were shown to be rich in shared MI. A structural proximity MI average score (termed pMI) was demonstrated to be a strong predictor for CR, thus confirming the proposed hypothesis. A structural proximity conservation average score (termed pC) was also calculated and demonstrated to carry distinct information from pMI. A catalytic likeliness score (Cls), combining the KL, pC and pMI measures, was shown to lead to significantly improved prediction accuracy. At a specificity of 0.90, the Cls method was found to have a sensitivity of 0.816. In summary, we demonstrate that networks of residues with high MI provide a distinct signature on CR and propose that such a signature should be present in other classes of functional residues where the requirement to maintain a particular function places limitations on the diversification of the structural environment along the course of evolution.
鉴定催化残基(CR)对于表征酶功能至关重要。CR 通常是保守的,位于蛋白质的功能部位,以发挥其功能。然而,许多非催化残基高度保守,并非所有 CR 在给定的蛋白质家族中都是保守的,这使得 CR 的鉴定成为一项具有挑战性的任务。在这里,我们提出了一个假设,即 CR 携带由具有高互信息(MI)的近距离残基网络定义的特定特征,并且该特征可用于区分功能和其他非功能保守残基。我们使用包含在催化位点图谱(CSA)数据库中的 434 个 Pfam 家族的数据集来测试这一假设,并证明 MI 可以补充氨基酸保守评分来检测 CR。Kullback-Leibler(KL)守恒测量被证明明显优于 Shannon 熵和最大频率测量。催化部位附近的残基被证明富含共享 MI。结构接近 MI 平均得分(称为 pMI)被证明是 CR 的强有力预测因子,从而证实了所提出的假设。还计算了结构接近保守平均得分(称为 pC),并证明它与 pMI 具有不同的信息。将 KL、pC 和 pMI 措施结合起来的催化可能性得分(Cls)被证明可以显著提高预测准确性。在特异性为 0.90 时,Cls 方法的灵敏度为 0.816。总之,我们证明了具有高 MI 的残基网络为 CR 提供了独特的特征,并且提出这种特征应该存在于其他功能残基类别中,在这些类别中,维持特定功能的要求对结构环境在进化过程中的多样化施加了限制。