Literature DB >> 9485510

Successful ab initio prediction of the tertiary structure of NK-lysin using multiple sequences and recognized supersecondary structural motifs.

D T Jones1.   

Abstract

A simple approach to protein tertiary structure prediction is described, based on the assembly of recognized supersecondary structural fragments taken from highly resolved protein structures by using a simulated annealing algorithm. The results of blind-testing this method on CASP2 target T0042 (pig NK-lysin) are presented. The predicted structure had a C alpha root-mean-square deviation of only 6.2 A from the experimental structure (and less than 5.0 A over the first 66 residues), and clearly had the correct fold when judged by using a number of objective measures. Despite the significant degree of success in this case, there is clearly much more development required before predictions with the accuracy of a good homology model can be made with this kind of approach.

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Year:  1997        PMID: 9485510     DOI: 10.1002/(sici)1097-0134(1997)1+<185::aid-prot24>3.3.co;2-t

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  22 in total

1.  Statistical potentials for fold assessment.

Authors:  Francisco Melo; Roberto Sánchez; Andrej Sali
Journal:  Protein Sci       Date:  2002-02       Impact factor: 6.725

2.  Alignment of protein sequences by their profiles.

Authors:  Marc A Marti-Renom; M S Madhusudhan; Andrej Sali
Journal:  Protein Sci       Date:  2004-04       Impact factor: 6.725

3.  Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis.

Authors:  Timothy Nugent; David T Jones
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-29       Impact factor: 11.205

4.  Multipass membrane protein structure prediction using Rosetta.

Authors:  Vladimir Yarov-Yarovoy; Jack Schonbrun; David Baker
Journal:  Proteins       Date:  2006-03-01

5.  Shaping up the protein folding funnel by local interaction: lesson from a structure prediction study.

Authors:  George Chikenji; Yoshimi Fujitsuka; Shoji Takada
Journal:  Proc Natl Acad Sci U S A       Date:  2006-02-17       Impact factor: 11.205

Review 6.  Towards genome-scale structure prediction for transmembrane proteins.

Authors:  Naama Hurwitz; Marialuisa Pellegrini-Calace; David T Jones
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-03-29       Impact factor: 6.237

7.  In silico chaperonin-like cycle helps folding of proteins for structure prediction.

Authors:  Tadaomi Furuta; Yoshimi Fujitsuka; George Chikenji; Shoji Takada
Journal:  Biophys J       Date:  2008-01-04       Impact factor: 4.033

Review 8.  Computational studies of membrane proteins: models and predictions for biological understanding.

Authors:  Jie Liang; Hammad Naveed; David Jimenez-Morales; Larisa Adamian; Meishan Lin
Journal:  Biochim Biophys Acta       Date:  2011-10-12

Review 9.  Chemical shift-based methods in NMR structure determination.

Authors:  Santrupti Nerli; Andrew C McShan; Nikolaos G Sgourakis
Journal:  Prog Nucl Magn Reson Spectrosc       Date:  2018-03-11       Impact factor: 9.795

10.  A geometric construction determines all permissible strand arrangements of sandwich proteins.

Authors:  A S Fokas; T S Papatheodorou; A E Kister; I M Gelfand
Journal:  Proc Natl Acad Sci U S A       Date:  2005-10-25       Impact factor: 11.205

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