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使用新软件CANDID和扭转角动力学算法DYANA进行自动NOE归属的蛋白质核磁共振结构测定。

Protein NMR structure determination with automated NOE assignment using the new software CANDID and the torsion angle dynamics algorithm DYANA.

作者信息

Herrmann Torsten, Güntert Peter, Wüthrich Kurt

机构信息

Institut für Molekularbiologie und Biophysik, Eidgenössische Technische Hochschule-Hönggerberg, CH-8093 Zürich, Switzerland.

出版信息

J Mol Biol. 2002 May 24;319(1):209-27. doi: 10.1016/s0022-2836(02)00241-3.

DOI:10.1016/s0022-2836(02)00241-3
PMID:12051947
Abstract

Combined automated NOE assignment and structure determination module (CANDID) is a new software for efficient NMR structure determination of proteins by automated assignment of the NOESY spectra. CANDID uses an iterative approach with multiple cycles of NOE cross-peak assignment and protein structure calculation using the fast DYANA torsion angle dynamics algorithm, so that the result from each CANDID cycle consists of exhaustive, possibly ambiguous NOE cross-peak assignments in all available spectra and a three-dimensional protein structure represented by a bundle of conformers. The input for the first CANDID cycle consists of the amino acid sequence, the chemical shift list from the sequence-specific resonance assignment, and listings of the cross-peak positions and volumes in one or several two, three or four-dimensional NOESY spectra. The input for the second and subsequent CANDID cycles contains the three-dimensional protein structure from the previous cycle, in addition to the complete input used for the first cycle. CANDID includes two new elements that make it robust with respect to the presence of artifacts in the input data, i.e. network-anchoring and constraint-combination, which have a key role in de novo protein structure determinations for the successful generation of the correct polypeptide fold by the first CANDID cycle. Network-anchoring makes use of the fact that any network of correct NOE cross-peak assignments forms a self-consistent set; the initial, chemical shift-based assignments for each individual NOE cross-peak are therefore weighted by the extent to which they can be embedded into the network formed by all other NOE cross-peak assignments. Constraint-combination reduces the deleterious impact of artifact NOE upper distance constraints in the input for a protein structure calculation by combining the assignments for two or several peaks into a single upper limit distance constraint, which lowers the probability that the presence of an artifact peak will influence the outcome of the structure calculation. CANDID test calculations were performed with NMR data sets of four proteins for which high-quality structures had previously been solved by interactive protocols, and they yielded comparable results to these reference structure determinations with regard to both the residual constraint violations, and the precision and accuracy of the atomic coordinates. The CANDID approach has further been validated by de novo NMR structure determinations of four additional proteins. The experience gained in these calculations shows that once nearly complete sequence-specific resonance assignments are available, the automated CANDID approach results in greatly enhanced efficiency of the NOESY spectral analysis. The fact that the correct fold is obtained in cycle 1 of a de novo structure calculation is the single most important advance achieved with CANDID, when compared with previously proposed automated NOESY assignment methods that do not use network-anchoring and constraint-combination.

摘要

组合式自动NOE归属与结构确定模块(CANDID)是一款新型软件,可通过自动归属NOESY谱图高效测定蛋白质的核磁共振(NMR)结构。CANDID采用迭代方法,通过使用快速DYANA扭转角动力学算法进行多个循环的NOE交叉峰归属和蛋白质结构计算,因此每个CANDID循环的结果包括所有可用谱图中详尽的、可能存在歧义的NOE交叉峰归属,以及由一组构象体表示的三维蛋白质结构。第一个CANDID循环的输入包括氨基酸序列、来自序列特异性共振归属的化学位移列表,以及一个或几个二维、三维或四维NOESY谱图中的交叉峰位置和体积列表。第二个及后续CANDID循环的输入除了包含第一个循环使用的完整输入外,还包含上一个循环的三维蛋白质结构。CANDID包含两个新元素,即网络锚定和约束组合,这使其在输入数据存在伪影的情况下仍具有稳健性,它们在从头蛋白质结构测定中起着关键作用,有助于第一个CANDID循环成功生成正确的多肽折叠。网络锚定利用了这样一个事实,即任何正确的NOE交叉峰归属网络都形成一个自洽集;因此,每个单独的NOE交叉峰基于化学位移的初始归属会根据它们能够嵌入由所有其他NOE交叉峰归属形成的网络的程度进行加权。约束组合通过将两个或多个峰的归属组合成一个单一的上限距离约束,减少了蛋白质结构计算输入中伪影NOE上限距离约束的有害影响,这降低了伪影峰的存在会影响结构计算结果的可能性。使用四种蛋白质的NMR数据集进行了CANDID测试计算,之前已通过交互式协议解析了这些蛋白质的高质量结构,在残余约束违反以及原子坐标的精度和准确性方面,CANDID测试计算得到的结果与这些参考结构测定结果相当。通过对另外四种蛋白质进行从头NMR结构测定,进一步验证了CANDID方法。这些计算中获得的经验表明,一旦获得几乎完整的序列特异性共振归属,自动CANDID方法会大大提高NOESY谱图分析的效率。与之前提出的不使用网络锚定和约束组合的自动NOESY归属方法相比,在从头结构计算的第1个循环中获得正确折叠是CANDID取得的最重要的进展。

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