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通过使用ABACUS方法的多规范蒙特卡罗搜索进行序列特异性共振归属。

Sequence specific resonance assignment via Multicanonical Monte Carlo search using an ABACUS approach.

作者信息

Lemak Alexander, Steren Carlos A, Arrowsmith Cheryl H, Llinás Miguel

机构信息

The Ontario Cancer Institute and Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada M5G 2M9.

出版信息

J Biomol NMR. 2008 May;41(1):29-41. doi: 10.1007/s10858-008-9238-2. Epub 2008 May 6.

Abstract

ABACUS [Grishaev et al. (2005) Proteins 61:36-43] is a novel protocol for automated protein structure determination via NMR. ABACUS starts from molecular fragments defined by unassigned J-coupled spin-systems and involves a Monte Carlo stochastic search in assignment space, probabilistic sequence selection, and assembly of fragments into structures that are used to guide the stochastic search. Here, we report further development of the two main algorithms that increase the flexibility and robustness of the method. Performance of the BACUS [Grishaev and Llinás (2004) J Biomol NMR 28:1-101] algorithm was significantly improved through use of sequential connectivities available from through-bond correlated 3D-NMR experiments, and a new set of likelihood probabilities derived from a database of 56 ultra high resolution X-ray structures. A Multicanonical Monte Carlo procedure, Fragment Monte Carlo (FMC), was developed for sequence-specific assignment of spin-systems. It relies on an enhanced assignment sampling and provides the uncertainty of assignments in a quantitative manner. The efficiency of the protocol was validated on data from four proteins of between 68-116 residues, yielding 100% accuracy in sequence specific assignment of backbone and side chain resonances.

摘要

ABACUS [格里沙耶夫等人(2005年),《蛋白质》61卷:36 - 43页]是一种通过核磁共振自动测定蛋白质结构的新方法。ABACUS从由未指定的J - 耦合自旋系统定义的分子片段开始,涉及在归属空间中的蒙特卡罗随机搜索、概率序列选择以及将片段组装成用于指导随机搜索的结构。在此,我们报告了两种主要算法的进一步发展,这些发展提高了该方法的灵活性和稳健性。通过使用来自键连相关三维核磁共振实验的顺序连接性以及从56个超高分辨率X射线结构数据库得出的一组新的似然概率,BACUS [格里沙耶夫和利尼亚斯(2004年),《生物分子核磁共振杂志》28卷:1 - 101页]算法的性能得到了显著提高。为自旋系统的序列特异性归属开发了一种多正则蒙特卡罗程序,即片段蒙特卡罗(FMC)。它依赖于增强的归属采样,并以定量方式提供归属的不确定性。该方法的效率在来自4种含有68 - 116个残基的蛋白质的数据上得到了验证,在主链和侧链共振的序列特异性归属方面产生了100%的准确率。

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