FAST-Modelfree: A program for rapid automated analysis of solution NMR spin-relaxation data

被引:185
作者
Cole, R [1 ]
Loria, JP [1 ]
机构
[1] Yale Univ, Dept Chem, New Haven, CT 06511 USA
基金
美国国家科学基金会;
关键词
computer program; Modelfree; NMR spin-relaxation; protein dynamics;
D O I
10.1023/A:1023808801134
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Herein we describe the program FAST-Modelfree for the fully automated, high throughput analysis of NMR spin-relaxation data. This program interfaces with the program Modelfree 4.1 and provides an intuitive graphical user interface for configuration as well as complete standalone operation during the model selection and rotational diffusion parameter optimization processes. FAST-Modelfree is also capable of iteratively assigning models to each spin and optimizing the parameters that describe the diffusion tensor. Tests with the protein Ribonuclease A indicate that using this iterative approach even poor initial estimates of the diffusion tensor parameters will converge to the optimal value within a few iterations. In addition to improving the quality of the final fit, this represents a substantial timesaving compared to manual data analysis and minimizes the chance of human error. It is anticipated that this program will be particularly useful for the analysis and comparison of data collected under different conditions such as multiple temperatures and the presence and absence of ligands. Further, this program is intended to establish a more uniform protocol for NMR spin-relaxation data analysis, facilitating the comparison of results both between and within research laboratories. Results obtained with FAST-Modelfree are compared with previous literature results for the proteins Ribonuclease H, E. coli glutaredoxin-1 and the Ca2+-binding protein S100B. These proteins represent data sets collected at both single and multiple static magnetic fields and which required analysis with both isotropic and axially symmetric rotational diffusion tensors. In all cases results obtained with FAST-Modelfree compared favorably with the original literature results.
引用
收藏
页码:203 / 213
页数:11
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