Optimus peak: automatic peak information extraction from 2D and 3D solution and solid state spectra using evolutionary algorithms

IF 1.9 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Rachel E. Brown, Allan R. Willms, Steffen P. Graether
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引用次数: 0

Abstract

Peak information extraction is an important step for all types of protein NMR experiments, from structure determination to titration experiments. In most cases, extraction of peak information, or peak-picking, is done semi-automatically or manually, relying on the spectroscopist’s expertise to guard against errors in the algorithm. Optimus Peak is designed for fully automatic peak-picking in multi-dimensional protein NMR spectra for both solid-state and solution NMR. The program shows a low false positive rate, due to its more robust evolutionary algorithm-based fitting. The program is also designed to fit together with other programs by being implemented as a terminal based command line program. Optimus Peak was tested using both solid-state and solution NMR experiments, for both 2D and 3D experiments, using 67 spectra from 12 different proteins, consisting of 26 different types of NMR experiments.

Abstract Image

Optimus峰:利用进化算法从二维和三维溶液和固态光谱中自动提取峰信息。
峰信息提取是各种类型的蛋白质核磁共振实验的重要步骤,从结构测定到滴定实验。在大多数情况下,峰信息的提取或峰拾取是半自动或手动完成的,依靠光谱学家的专业知识来防止算法中的错误。Optimus Peak专为固态和溶液核磁共振的多维蛋白质NMR光谱全自动选峰而设计。该程序显示出较低的假阳性率,由于其更强大的进化算法为基础的拟合。通过作为基于终端的命令行程序来实现,该程序也被设计成与其他程序相结合。Optimus Peak采用固态和溶液核磁共振实验,二维和三维实验,使用来自12种不同蛋白质的67个光谱,包括26种不同类型的核磁共振实验。
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来源期刊
Journal of Biomolecular NMR
Journal of Biomolecular NMR 生物-光谱学
CiteScore
6.00
自引率
3.70%
发文量
19
审稿时长
6-12 weeks
期刊介绍: The Journal of Biomolecular NMR provides a forum for publishing research on technical developments and innovative applications of nuclear magnetic resonance spectroscopy for the study of structure and dynamic properties of biopolymers in solution, liquid crystals, solids and mixed environments, e.g., attached to membranes. This may include: Three-dimensional structure determination of biological macromolecules (polypeptides/proteins, DNA, RNA, oligosaccharides) by NMR. New NMR techniques for studies of biological macromolecules. Novel approaches to computer-aided automated analysis of multidimensional NMR spectra. Computational methods for the structural interpretation of NMR data, including structure refinement. Comparisons of structures determined by NMR with those obtained by other methods, e.g. by diffraction techniques with protein single crystals. New techniques of sample preparation for NMR experiments (biosynthetic and chemical methods for isotope labeling, preparation of nutrients for biosynthetic isotope labeling, etc.). An NMR characterization of the products must be included.
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