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首页> 外文期刊>IUCrJ >Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds
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Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds

机译：通过进化协方差预测的残基接触将从头算分子替换的应用扩展到更大和更具挑战性的蛋白质折叠

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For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions (`decoys'), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue–residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing.
机译：对于许多蛋白质家族而言，大量的新序列信息以及新的统计协议现在允许仅从序列信息中准确预测接触残基。这提供了更准确的从头开始（基于非同源性）结构预测的可能性。此类模型可通过分子置换（MR）用于结构求解，其中目标折叠是新颖的，或仅与已知结构有很远的关联。在这里，AMPLE是一种从头算结构预测（“诱饵”）组装搜索模型集合的MR管道，用于评估接触辅助的头算模型对晶体学家的价值。结果表明，进化协方差派生的残基-残基接触预测可提高从头算模型的质量，因此，使用从其衍生的搜索模型提高MR的成功率。对于包含β结构的靶标，通过使用β链接触过滤方案，诱饵质量和MR性能会进一步提高。这样的接触引导诱饵从21种尝试的蛋白质靶标中获得14种结构解，而简单的Rosetta诱饵则为9种。先前遇到的限制已在两个关键方面被取代。首先，解决了多达221个残基的更大目标，该目标远大于先前基准的120个残基的阈值。其次，接触引导诱饵显着提高了富含β-折叠的蛋白质的成功率。总体而言，接触引导诱饵的性能提高表明，MR现在可用于比以前容易处理的蛋白靶标范围更广的靶标，并指出最近测序方面的显着进展可直接为结构生物学带来好处。

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