APART Automated Pre-processing for NMR Assignments with Reduced Tedium.pdf

APART: Automated Pre-processing for NMR Assignments with Reduced Tedium Norma H. Pawley, Jason D. Gans and Ryszard Michalczyk* Los Alamos National Laboratory Bioscience Division MS G758 Los Alamos, New Mexico 87545 rmichalczyk@ *To whom correspondence should be addressed Bioinfor matics ? Oxford University Press 2004; all rights reserved. Bioinformatics Advance Access published September 23, 2004 2ABSTRACT Motivation: High-throughput NMR structure determination is a goal that will require progress on many fronts, one of which is rapid resonance assignment. An important rate-limiting step in the resonance assignment process is accurate identification of resonance peaks in NMR spectra. Peak-picking schemes range from incomplete (which lose essential assignment connectivities) to noisy (which obscure true connectivities with many false ones). We introduce an automated pre- assignment process that removes false peaks from noisy peak lists by requiring consensus between multiple NMR experiments and exploiting a priori information about NMR spectra. This process is designed to accept multiple input formats and generate multiple output formats, in an effort to be compatible with a variety of user preferences. Results: Automated pre-processing with APART rapidly identifies and removes false peaks from initial peak lists, reduces the burden of manual data entry, and documents and standardizes the peak filtering process. Successful pre-processing is demonstrated by the increased number of correct assignments obtained when data is submitted to an automated assignment program. Availability: APART is available from /NMR/APART.htm Supplementary Information: Manual pages with installation instructions, procedures and screen shots can also be found at /NMR/APART_Manual.pdf. Contact: npawley@ 3INTRODUCTION Three-dimensional protein structures can be obtained using Nuclear Magnetic Resonance spectroscopy; however, the process is generally time-consuming and expertise