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Title: A constraint-based assignment system for automating long side chain assignments in protein 2D NMR spectra

Abstract

The sequential assignment of protein 2D NMR data has been tackled by many automated and semi-automated systems. One area that these systems have not tackled is the searching of the TOCSY spectrum looking for cross peaks and chemical shift values for hydrogen nuclei that are at the end of long side chains. This paper describes our system for solving this problem using constraint logic programming and compares our constraint satisfaction algorithm to a standard backtracking version.

Authors:
; ;  [1]
  1. Univ. of Aberdeen (United Kingdom)
Publication Date:
Research Org.:
Stanford Univ., CA (United States)
OSTI Identifier:
401850
Report Number(s):
CONF-9507246-
TRN: 96:005602-0028
Resource Type:
Technical Report
Resource Relation:
Conference: Intelligent Systems for Molecular Biology (ISMB) conference, Cambridge (United Kingdom), 16-19 Jul 1995; Other Information: PBD: 1995; Related Information: Is Part Of ISMB-95 -- Third international conference on intelligent systems for molecular biology: Proceedings; Rawlings, C.; Clark, D.; Altman, R.; Hunter, L.; Lengauer, T.; Wodak, S. [eds.]; PB: 427 p.
Country of Publication:
United States
Language:
English
Subject:
55 BIOLOGY AND MEDICINE, BASIC STUDIES; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; 66 PHYSICS; PROTEIN STRUCTURE; NMR SPECTRA; CHEMICAL SHIFT; AUTOMATION; CHEMICAL BONDS; AMINO ACIDS

Citation Formats

Leishman, S., Gray, P., and Fothergill, J.E.. A constraint-based assignment system for automating long side chain assignments in protein 2D NMR spectra. United States: N. p., 1995. Web.
Leishman, S., Gray, P., & Fothergill, J.E.. A constraint-based assignment system for automating long side chain assignments in protein 2D NMR spectra. United States.
Leishman, S., Gray, P., and Fothergill, J.E.. 1995. "A constraint-based assignment system for automating long side chain assignments in protein 2D NMR spectra". United States. doi:.
@article{osti_401850,
title = {A constraint-based assignment system for automating long side chain assignments in protein 2D NMR spectra},
author = {Leishman, S. and Gray, P. and Fothergill, J.E.},
abstractNote = {The sequential assignment of protein 2D NMR data has been tackled by many automated and semi-automated systems. One area that these systems have not tackled is the searching of the TOCSY spectrum looking for cross peaks and chemical shift values for hydrogen nuclei that are at the end of long side chains. This paper describes our system for solving this problem using constraint logic programming and compares our constraint satisfaction algorithm to a standard backtracking version.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 1995,
month =
}

Technical Report:
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  • This paper considers the protein structure prediction problem for lattice and off-lattice protein folding models that explicitly represent side chains. Lattice models of proteins have proven extremely useful tools for reasoning about protein folding in unrestricted continuous space through analogy. This paper provides the first illustration of how rigorous algorithmic analyses of lattice models can lead to rigorous algorithmic analyses of off-lattice models. The authors consider two side chain models: a lattice model that generalizes the HP model (Dill 85) to explicitly represent side chains on the cubic lattice, and a new off-lattice model, the HP Tangent Spheres Side Chainmore » model (HP-TSSC), that generalizes this model further by representing the backbone and side chains of proteins with tangent spheres. They describe algorithms for both of these models with mathematically guaranteed error bounds. In particular, the authors describe a linear time performance guaranteed approximation algorithm for the HP side chain model that constructs conformations whose energy is better than 865 of optimal in a face centered cubic lattice, and they demonstrate how this provides a 70% performance guarantee for the HP-TSSC model. This is the first algorithm in the literature for off-lattice protein structure prediction that has a rigorous performance guarantee. The analysis of the HP-TSSC model builds off of the work of Dancik and Hannenhalli who have developed a 16/30 approximation algorithm for the HP model on the hexagonal close packed lattice. Further, the analysis provides a mathematical methodology for transferring performance guarantees on lattices to off-lattice models. These results partially answer the open question of Karplus et al. concerning the complexity of protein folding models that include side chains.« less
  • This paper is concerned with the handling of uncertain data about the applicability of constraints in protein topology prediction. It discusses the use of novel methods of representing and reasoning with uncertain data, and presents the results of some experiments in using these methods to build probabilistic models of constraint application. It thus builds on work by other authors in both constraint satisfaction and probabilistic reasoning.