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Improved reliability accuracy and quality in automated NMR structure calculation with ARIA

机译:使用ARIA提高了自动NMR结构计算的可靠性准确性和质量

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摘要

In biological NMR, assignment of NOE cross-peaks and calculation of atomic conformations are critical steps in the determination of reliable high-resolution structures. ARIA is an automated approach that performs NOE assignment and structure calculation in a concomitant manner in an iterative procedure. The log-harmonic shape for distance restraint potential and the Bayesian weighting of distance restraints, recently introduced in ARIA, were shown to significantly improve the quality and the accuracy of determined structures. In this paper, we propose two modifications of the ARIA protocol: (1) the softening of the force field together with adapted hydrogen radii, which is meaningful in the context of the log-harmonic potential with Bayesian weighting, (2) a procedure that automatically adjusts the violation tolerance used in the selection of active restraints, based on the fitting of the structure to the input data sets. The new ARIA protocols were fine-tuned on a set of eight protein targets from the CASD–NMR initiative. As a result, the convergence problems previously observed for some targets was resolved and the obtained structures exhibited better quality. In addition, the new ARIA protocols were applied for the structure calculation of ten new CASD–NMR targets in a blind fashion, i.e. without knowing the actual solution. Even though optimisation of parameters and pre-filtering of unrefined NOE peak lists were necessary for half of the targets, ARIA consistently and reliably determined very precise and highly accurate structures for all cases. In the context of integrative structural biology, an increasing number of experimental methods are used that produce distance data for the determination of 3D structures of macromolecules, stressing the importance of methods that successfully make use of ambiguous and noisy distance data.Electronic supplementary materialThe online version of this article (doi:10.1007/s10858-015-9928-5) contains supplementary material, which is available to authorized users.
机译:在生物NMR中,NOE交叉峰的分配和原子构象的计算是确定可靠的高分辨率结构的关键步骤。 ARIA是一种自动化的方法,可以在迭代过程中同时进行NOE分配和结构计算。最近在ARIA中引入的对距离约束电位的对数谐波形状和距离约束的贝叶斯加权可以显着提高所确定结构的质量和准确性。在本文中,我们提出了ARIA协议的两个修改:(1)力场的软化以及合适的氢半径,这在使用贝叶斯加权的对数谐波势的背景下是有意义的,(2)根据结构对输入数据集的拟合,自动调整在选择主动约束时使用的违反容限。新的ARIA方案在CASD-NMR计划的一组八个蛋白质靶标上进行了微调。结果,解决了先前针对某些目标观察到的收敛问题,并且所获得的结构表现出更好的质量。此外,新的ARIA协议被盲目地用于十个新CASD-NMR靶的结构计算,即不知道实际的解决方案。尽管对于一半的目标来说,参数优化和未精炼的NOE峰列表的预过滤是必要的,但ARIA始终如一地可靠地确定了所有情况下非常精确和高度准确的结构。在整合结构生物学的背景下,越来越多的实验方法被用于产生距离数据来确定大分子的3D结构,从而强调了成功利用模糊和嘈杂的距离数据的方法的重要性。本文的文章(doi:10.1007 / s10858-015-9928-5)包含补充材料,授权用户可以使用。

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