Caliandro Rocco, Carrozzini Benedetta, Cascarano Giovanni Luca, Comunale Giuliana, Giacovazzo Carmelo, Mazzone Annamaria
Istituto di Cristallografia, CNR, Via G. Amendola 122/O, 70126 Bari, Italy.
DiCEM, Università degli Studi della Basilicata, 75100 Matera, Italy.
Acta Crystallogr D Biol Crystallogr. 2014 Jul;70(Pt 7):1994-2006. doi: 10.1107/S139900471401013X. Epub 2014 Jun 29.
Phasing proteins at non-atomic resolution is still a challenge for any ab initio method. A variety of algorithms [Patterson deconvolution, superposition techniques, a cross-correlation function (C map), the VLD (vive la difference) approach, the FF function, a nonlinear iterative peak-clipping algorithm (SNIP) for defining the background of a map and the free lunch extrapolation method] have been combined to overcome the lack of experimental information at non-atomic resolution. The method has been applied to a large number of protein diffraction data sets with resolutions varying from atomic to 2.1 Å, with the condition that S or heavier atoms are present in the protein structure. The applications include the use of ARP/wARP to check the quality of the final electron-density maps in an objective way. The results show that resolution is still the maximum obstacle to protein phasing, but also suggest that the solution of protein structures at 2.1 Å resolution is a feasible, even if still an exceptional, task for the combined set of algorithms implemented in the phasing program. The approach described here is more efficient than the previously described procedures: e.g. the combined use of the algorithms mentioned above is frequently able to provide phases of sufficiently high quality to allow automatic model building. The method is implemented in the current version of SIR2014.
对于任何从头算方法来说,在非原子分辨率下确定蛋白质的相位仍然是一项挑战。多种算法(帕特森反卷积、叠加技术、互相关函数(C图)、VLD(万岁差异)方法、FF函数、用于定义图谱背景的非线性迭代峰裁剪算法(SNIP)以及免费午餐外推法)已被结合起来,以克服在非原子分辨率下实验信息的不足。该方法已应用于大量蛋白质衍射数据集,其分辨率从原子分辨率到2.1 Å不等,条件是蛋白质结构中存在S或更重的原子。应用包括使用ARP/wARP以客观的方式检查最终电子密度图的质量。结果表明,分辨率仍然是蛋白质相位确定的最大障碍,但也表明,对于相位确定程序中实现的组合算法集而言,以2.1 Å分辨率解析蛋白质结构是一项可行的任务,即使仍然是一项特殊的任务。这里描述的方法比先前描述的程序更有效:例如,上述算法的组合使用通常能够提供足够高质量的相位,以允许自动构建模型。该方法在SIR2014的当前版本中实现。