Related Experiment Videos
APART: automated preprocessing for NMR assignments with reduced tedium
Norma H Pawley1, Jason D Gans, Ryszard Michalczyk
1Los Alamos National Laboratory, Bioscience Division MS G758, Los Alamos, NM 87545, USA. npawley@lanl.gov
Bioinformatics (Oxford, England)
|September 25, 2004
Summary
Automated peak picking in NMR spectra uses APART to remove false positives by cross-referencing multiple experiments. This improves resonance assignment accuracy for high-throughput structure determination.
Area of Science:
- Biophysics
- Structural Biology
- Nuclear Magnetic Resonance (NMR) Spectroscopy
Background:
- High-throughput NMR structure determination requires efficient resonance assignment.
- Accurate peak identification in NMR spectra is a critical bottleneck.
- Existing peak-picking methods are either incomplete or introduce noise, hindering assignment.
Purpose of the Study:
- To introduce an automated preassignment process to improve NMR resonance assignment.
- To develop a method for removing false peaks from noisy peak lists.
- To enhance compatibility with diverse user preferences and data formats.
Main Methods:
- Developed APART, an automated preassignment process.
- Implemented consensus-building across multiple NMR experiments.
- Incorporated a priori information about NMR spectra for peak validation.
- Designed for flexible input and output format compatibility.
Main Results:
- APART effectively identifies and removes false peaks from initial lists.
- The process reduces manual data entry and standardizes peak filtering.
- Successful preprocessing led to a higher number of correct assignments when using automated assignment programs.
Conclusions:
- Automated preprocessing with APART significantly enhances NMR resonance assignment accuracy.
- APART streamlines the data analysis pipeline for structural biology.
- This method facilitates progress towards high-throughput NMR structure determination.