Using inferred residue contacts to distinguish between correct and incorrect protein models.
Using inferred residue contacts to distinguish between correct and incorrect protein models.
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DOI：
10.1093/bioinformatics/btn248
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发表时间：
2008-07-15
期刊：
影响因子：
--
通讯作者：
Eisenberg D
中科院分区：
文献类型：
--
作者：
Miller CS;Eisenberg D
动机：3D蛋白质结构的从头预测正在经历一个戏剧性的改进时期。通常，剩下的困难是从一组低能量候选者中选择最接近真实结构的模型。在多大程度上可以从多个序列比对的残基间接触预测，这是正交的信息，在大多数结构预测算法中使用，被用来确定那些模型最相似的天然蛋白质结构？结果：我们提出了一个贝叶斯推理过程，以确定在蛋白质结构中的空间上接近的残基对。该方法将多序列比对作为输入，并输出每个残基对的精确后验概率。我们利用最近的宏基因组测序项目创建一个测试集的1656个已知的蛋白质结构的大，多样性和信息丰富的多重序列比对。该方法推断空间上接近的残基对在这个测试集具有良好的准确性：排名靠前的预测达到平均准确度为38%（平均21倍的随机预测的改善）在交叉验证测试。值得注意的是，由一系列结构预测算法生成的预测3D模型的准确性与模型满足通过我们的方法推断的可能的残基接触的程度密切相关。这种相关性允许有信心地拒绝不正确的结构模型。可用性：该方法的实施可在www.example.com上免费获得联系方式：www.example.com补充信息：补充数据可在生物信息学在线获得。
Motivation: The de novo prediction of 3D protein structure is enjoying a period of dramatic improvements. Often, a remaining difficulty is to select the model closest to the true structure from a group of low-energy candidates. To what extent can inter-residue contact predictions from multiple sequence alignments, information which is orthogonal to that used in most structure prediction algorithms, be used to identify those models most similar to the native protein structure? Results: We present a Bayesian inference procedure to identify residue pairs that are spatially proximal in a protein structure. The method takes as input a multiple sequence alignment, and outputs an accurate posterior probability of proximity for each residue pair. We exploit a recent metagenomic sequencing project to create large, diverse and informative multiple sequence alignments for a test set of 1656 known protein structures. The method infers spatially proximal residue pairs in this test set with good accuracy: top-ranked predictions achieve an average accuracy of 38% (for an average 21-fold improvement over random predictions) in cross-validation tests. Notably, the accuracy of predicted 3D models generated by a range of structure prediction algorithms strongly correlates with how well the models satisfy probable residue contacts inferred via our method. This correlation allows for confident rejection of incorrect structural models. Availability: An implementation of the method is freely available at http://www.doe-mbi.ucla.edu/services Contact: david@mbi.ucla.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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