Literature DB >> 7663143

Graph-theoretical assignment of secondary structure in multidimensional protein NMR spectra: application to the lac repressor headpiece.

E C van Geerestein-Ujah1, M Slijper, R Boelens, R Kaptein.   

Abstract

A novel procedure is presented for the automatic identification of secondary structures in proteins from their corresponding NOE data. The method uses a branch of mathematics known as graph theory to identify prescribed NOE connectivity patterns characteristic of the regular secondary structures. Resonance assignment is achieved by connecting these patterns of secondary structure together, thereby matching the connected spin systems to specific segments of the protein sequence. The method known as SERENDIPITY refers to a set of routines developed in a modular fashion, where each program has one or several well-defined tasks. NOE templates for several secondary structure motifs have been developed and the method has been successfully applied to data obtained from NOESY-type spectra. The present report describes the application of the SERENDIPITY protocol to a 3D NOESY-HMQC spectrum of the 15N-labelled lac repressor headpiece protein. The application demonstrates that, under favourable conditions, fully automated identification of secondary structures and semi-automated assignment are feasible.

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Year:  1995        PMID: 7663143     DOI: 10.1007/bf00417493

Source DB:  PubMed          Journal:  J Biomol NMR        ISSN: 0925-2738            Impact factor:   2.835


  24 in total

1.  Implementation of the main chain directed assignment strategy. Computer assisted approach.

Authors:  S J Nelson; D M Schneider; A J Wand
Journal:  Biophys J       Date:  1991-05       Impact factor: 4.033

2.  A computer-based protocol for semiautomated assignments and 3D structure determination of proteins.

Authors:  R P Meadows; E T Olejniczak; S W Fesik
Journal:  J Biomol NMR       Date:  1994-01       Impact factor: 2.835

3.  Upperbound procedures for the identification of similar three-dimensional chemical structures.

Authors:  A T Brint; P Willett
Journal:  J Comput Aided Mol Des       Date:  1989-01       Impact factor: 3.686

4.  Identification of tertiary structure resemblance in proteins using a maximal common subgraph isomorphism algorithm.

Authors:  H M Grindley; P J Artymiuk; D W Rice; P Willett
Journal:  J Mol Biol       Date:  1993-02-05       Impact factor: 5.469

Review 5.  Multidimensional heteronuclear nuclear magnetic resonance of proteins.

Authors:  G M Clore; A M Gronenborn
Journal:  Methods Enzymol       Date:  1994       Impact factor: 1.600

6.  Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features.

Authors:  W Kabsch; C Sander
Journal:  Biopolymers       Date:  1983-12       Impact factor: 2.505

7.  Use of fuzzy mathematics for complete automated assignment of peptide 1H 2D NMR spectra.

Authors:  J Xu; S K Straus; B C Sanctuary; L Trimble
Journal:  J Magn Reson B       Date:  1994-01

8.  A protein structure from nuclear magnetic resonance data. lac repressor headpiece.

Authors:  R Kaptein; E R Zuiderweg; R M Scheek; R Boelens; W F van Gunsteren
Journal:  J Mol Biol       Date:  1985-03-05       Impact factor: 5.469

Review 9.  The anatomy and taxonomy of protein structure.

Authors:  J S Richardson
Journal:  Adv Protein Chem       Date:  1981

10.  A novel approach for sequential assignment of 1H, 13C, and 15N spectra of proteins: heteronuclear triple-resonance three-dimensional NMR spectroscopy. Application to calmodulin.

Authors:  M Ikura; L E Kay; A Bax
Journal:  Biochemistry       Date:  1990-05-15       Impact factor: 3.162

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  2 in total

1.  Network representation of protein interactions: Theory of graph description and analysis.

Authors:  Dennis Kurzbach
Journal:  Protein Sci       Date:  2016-06-19       Impact factor: 6.725

2.  Maximal clique method for the automated analysis of NMR TOCSY spectra of complex mixtures.

Authors:  Da-Wei Li; Cheng Wang; Rafael Brüschweiler
Journal:  J Biomol NMR       Date:  2017-06-01       Impact factor: 2.835

  2 in total

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