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首页> 外文期刊>Journal of Biomolecular NMR >Improved reliability, accuracy and quality in automated NMR structure calculation with ARIA
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Improved reliability, accuracy and quality in automated NMR structure calculation with ARIA

机译：利用咏叹调提高自动化NMR结构计算中的可靠性，准确性和质量

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In biological NMR, assignment of NOE crosspeaks 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.
机译：在生物NMR中，NEE交叉斑块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是一种自动化方法，以迭代程序以伴随方式执行NOE分配和结构计算。距离约束电位的对数谐波形状和距离限制的贝叶斯加权，最近在aria引入，显着提高了确定的结构的质量和准确性。在本文中，我们提出了两种修改ARIA协议：（1）与贝叶斯加权的对数谐波电位的语境中的调整氢半导体一起软化力场的软化，（2）根据结构的拟合自动调整在选择的违规公差中，基于结构对输入数据集的拟合。新的ARIA协议在来自CASD-NMR倡议的一组八种蛋白质目标上进行了微调。结果，解决了一些目标之前观察到的收敛问题，并且所获得的结构表现出更好的质量。此外，新的ARIA协议以盲目的方式应用于十个新的Casd-NMR目标的结构计算，即，不知道实际解决方案。尽管对目标的一半是必要的参数和未精确的NOE峰值列表的优化，但ARIA始终如一，可靠地确定所有情况的非常精确和高度准确的结构。在综合结构生物学的背景下，使用越来越多的实验方法，用于产生距离大分子的3D结构的距离数据，强调成功利用模糊和嘈杂的距离数据的方法的重要性。

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