Structure calculation, refinement and validation using CcpNmr Analysis.
Structure calculation, refinement and validation using CcpNmr Analysis.
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DOI：
10.1107/s1399004714026662
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发表时间：
2015-01-01
期刊：
影响因子：
--
通讯作者：
Vuister GW
中科院分区：
文献类型：
--
作者：
Skinner SP;Goult BT;Fogh RH;Boucher W;Stevens TJ;Laue ED;Vuister GW
本文介绍了用于生物大分子的核磁共振化学位移归属和结构测定的CcpNmr分析程序的工作。CcpNmr分析为生物大分子的核磁共振化学位移归属和结构确定提供了一条流水线。此外，它还包括分析许多附加实验的工具，这些实验使核磁共振成为研究复杂生物学问题的关键技术。这份报告描述了CcpNmr分析如何将核磁共振结构确定过程中的所有任务无缝地联系在一起。它详细介绍了每个阶段，从产生核磁共振限制条件[距离、二面体、氢键和残余偶极耦合(RDC)]，将这些限制条件导出，然后从结构计算软件(如程序CyANA或ARIA)重新导入，以及分析和验证结构计算获得的结果，最终将完成的赋值和精炼的结构系综简化地沉积到PDBe储存库中。直到最近，通过核磁共振确定溶液结构一直是一项相当费力的任务，需要多个阶段和程序。然而，随着这里描述的对CcpNmr分析的新增强，这个过程现在更加直观和高效，而且不太容易出错。
This report describes the working of the program CcpNmr Analysis for both NMR chemical shift assignment and structure determination of biological macromolecules. CcpNmr Analysis provides a streamlined pipeline for both NMR chemical shift assignment and structure determination of biological macromolecules. In addition, it encompasses tools to analyse the many additional experiments that make NMR such a pivotal technique for research into complex biological questions. This report describes how CcpNmr Analysis can seamlessly link together all of the tasks in the NMR structure-determination process. It details each of the stages from generating NMR restraints [distance, dihedral, hydrogen bonds and residual dipolar couplings (RDCs)], exporting these to and subsequently re-importing them from structure-calculation software (such as the programs CYANA or ARIA) and analysing and validating the results obtained from the structure calculation to, ultimately, the streamlined deposition of the completed assignments and the refined ensemble of structures into the PDBe repository. Until recently, such solution-structure determination by NMR has been quite a laborious task, requiring multiple stages and programs. However, with the new enhancements to CcpNmr Analysis described here, this process is now much more intuitive and efficient and less error-prone.
影响因子：
2.7
作者：
Penkett CJ;van Ginkel G;Velankar S;Swaminathan J;Ulrich EL;Mading S;Stevens TJ;Fogh RH;Gutmanas A;Kleywegt GJ;Henrick K;Vranken WF
通讯作者：
Vranken WF