![]() This paper develops, analyzes and applies a novel algorithm for the identification of polytopes representing consistent patterns of edges in a corrupted NOESY graph. The key algorithmic challenge is to be able to uncover these patterns even when they are obscured by significant noise. for alpha-helices and beta-sheets) within a graph and by mapping the vertices to the primary sequence. An assignment is derived by identifying consistent patterns of edges (e.g. Due to experimental ambiguity, several incorrect edges can be hypothesized for each spectral peak. In the contact-based approach, spectral data are represented in a graph with vertices for putative residues (of unknown relation to the primary sequence) and edges for hypothesized NOESY interactions, such that observed spectral peaks could be explained if the residues were 'close enough'. A minimalist approach to assignment, which we call 'contact-based', seeks to dramatically reduce experimental time and expense by replacing the standard suite of through-bond experiments with the through-space (nuclear Overhauser enhancement spectroscopy, NOESY) experiment. Kamisetty, Hetunandan Bailey-Kellogg, Chris Pandurangan, Gopalīackbone resonance assignment is a critical bottleneck in studies of protein structure, dynamics and interactions by nuclear magnetic resonance ( NMR) spectroscopy. The final structures computed using the NOE distance restraints assigned by NASCA have backbone RMSD 0Īn efficient randomized algorithm for contact-based NMR backbone resonance assignment. Tests on five proteins show that NASCA assigns resonances for more than 90% of side-chain protons, and achieves about 80% correct assignments. These side-chain resonance assignments are then used to resolve the NOE assignment ambiguity and compute high-resolution protein structures. Then an A* search algorithm is employed to find a set of optimal side-chain resonance assignments that best fit the NMR data. The complexity of the combinatorial search is reduced by using a dead-end elimination (DEE) algorithm, which prunes side-chain resonance assignments that are provably not part of the optimal solution. The MRF captures the contact map information of the protein derived from NOESY spectra, exploits the backbone structural information determined by RDCs, and considers all possible side-chain rotamers. After casting the assignment problem into a Markov Random Field (MRF), NASCA extends and applies combinatorial protein design algorithms to compute optimal assignments that best interpret the NMR data. To overcome this deficiency, we present a novel algorithm, called NASCA (NOE Assignment and Side-Chain Assignment), to automate both side-chain resonance and NOE assignments and to perform high-resolution protein structure determination in the absence of any explicit through-bond experiment to facilitate side-chain resonance assignment, such as HCCH-TOCSY. Unfortunately, these TOCSY experiments perform poorly on large proteins. Most NOE assignment algorithms require nearly complete side-chain resonance assignments from a series of through-bond experiments such as HCCH-TOCSY or HCCCONH. Compared to the well-studied backbone resonance assignment problem, automated side-chain resonance and NOE assignments are relatively less explored. One bottleneck in NMR structure determination lies in the laborious and time-consuming process of side-chain resonance and NOE assignments. Zeng, Jianyang Zhou, Pei Donald, Bruce Randall Protein Side-Chain Resonance Assignment and NOE Assignment Using RDC-Defined Backbones without TOCSY Data3
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