Toward better refinement of comparative models: Predicting loops in inexact environments
Toward better refinement of comparative models: Predicting loops in inexact environments
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DOI：
10.1002/prot.21990
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发表时间：
2008-08-15
影响因子：
2.9
通讯作者：
Jacobson, Matthew P.
中科院分区：
文献类型：
--
作者：
Sellers, Benjamin D.;Zhu, Kai;Jacobson, Matthew P.
在比较蛋白质模型中实现原子水平的准确性受到我们优化初始同源模型更接近天然状态的能力的限制。尽管付出了很大的努力，但开发广义改进方法方面的进展一直受到限制。相反，已经描述了可以准确地重建天然蛋白质结构中的环路构象的方法。我们假设同源模型中的循环完善要比晶体结构中的循环重建要困难得多，部分原因是循环周围的侧链，骨架和其他结构性不准确，会造成一个具有挑战性的抽样问题。如果没有同时完善相邻部分，就无法完善循环。在这项工作中，我们在人造但有用的测试集中挑出一个抽样问题，并检查循环改进精度如何受到周围侧链错误的影响。在80个高分辨率的晶体结构中，我们首先将6-12个残基环脱离晶体构象，并将所有蛋白质侧链置于非本地但低能构象中。即使是周围环境中这些相对较小的扰动，也使循环预测问题更具挑战性。使用先前发表的循环预测方法，对于6、8、10和12个残基环的组中值主链（N-C Alpha-C-O）RMSD分别为0.3/0.6/0.4/0.4/0.4/0.4/0.6 Angstrom，在天然结构上，并增加到1.1/增加到1.1/ 2.2/1.5/2.3在扰动的情况下备份。然后，我们增强了以前的循环预测方法，以同时优化环路周围的侧链的旋转状态。我们的结果表明，这种增强的环路预测方法可以在许多扰动的结构中恢复本机状态，而先前方法失败，6、8、10和12残留的RMSD的中位数RMSD扰动循环提高到0.4/0.8/0.8/1.1/1.2 Angstrom 。最后，我们重点介绍了盲试验中的三个比较模型，在该模型中，我们的新方法预测了与使用同源模板建模的首先建模的循环更接近天然构型，这一任务通常被认为很困难。尽管在完整的比较模型到高精度方面仍然存在许多挑战，但这项工作为实现了这一目标提供了有条理的一步。
Achieving atomic-level accuracy in comparative protein models is limited by our ability to refine the initial, homolog-derived model closer to the native state. Despite considerable effort, progress in developing a generalized refinement method has been limited. In contrast, methods have been described that can accurately reconstruct loop conformations in native protein structures. We hypothesize that loop refinement in homology models is much more difficult than loop reconstruction in crystal structures, in part, because side-chain, backbone, and other structural inaccuracies surrounding the loop create a challenging sampling problem; the loop cannot be refined without simultaneously refining adjacent portions. In this work, we single out one sampling issue in an artificial but useful test set and examine how loop refinement accuracy is affected by errors in surrounding side-chains. In 80 high-resolution crystal structures, we first perturbed 6-12 residue loops away from the crystal conformation, and placed all protein side chains in non-native but low energy conformations. Even these relatively small perturbations in the surroundings made the loop prediction problem much more challenging. Using a previously published loop prediction method, median backbone (N-C alpha-C-O) RMSD's for groups of 6, 8, 10, and 12 residue loops are 0.3/0.6/0.4/0.6 angstrom, respectively, on native structures and increase to 1.1/2.2/1.5/2.3 angstrom on the perturbed cases. We then augmented our previous loop prediction method to simultaneously optimize the rotamer states of side chains surrounding the loop. Our results show that this augmented loop prediction method can recover the native state in many perturbed structures where the previous method failed, the median RMSD's for the 6, 8, 10, and 12 residue perturbed loops improve to 0.4/0.8/1.1/1.2 angstrom. Finally, we highlight three comparative models from blind tests, in which our new method predicted loops closer to the native conformation than first modeled using the homolog template, a task generally understood to be difficult. Although many challenges remain in refining full comparative models to high accuracy, this work offers a methodical step toward that goal.