Towards Fully Automated Structure-Based NMR Resonance Assignment of 15N-Labeled Proteins From Automatically Picked Peaks

摘要

Abstract In NMR resonance assignment, an indispensable step in NMR protein studies, manually processed peaks from both N-labeled and C-labeled spectra are typically used as inputs. However, the use of homologous structures can allow one to use only N-labeled NMR data and avoid the added expense of using C-labeled data. We propose a novel integer programming framework for structure-based backbone resonance assignment using N-labeled data. The core consists of a pair of integer programming models: one for spin system forming and amino acid typing, and the other for backbone resonance assignment. The goal is to perform the assignment directly from spectra without any manual intervention via automatically picked peaks, which are much noisier than manually picked peaks, so methods must be error-tolerant. In the case of semi-automated/manually processed peak data, we compare our system with the Xiong-Pandurangan-Bailey-Kellogg's contact replacement (CR) method, which is the most error-tolerant method for struct..." /> rel="meta" type="application/atom+xml" href="http://dx.doi.org/10.1089%2Fcmb.2010.0251" /> rel="meta" type="application/rdf+json" href="http://dx.doi.org/10.1089%2Fcmb.2010.0251" /> rel="meta" type="application/unixref+xml" href="http://dx.doi.org/10.1089%2Fcmb.2010.0251" /> 展开▼