Literature DB >> 10329175

Prediction of protein tertiary structure to low resolution: performance for a large and structurally diverse test set.

V A Eyrich1, D M Standley, R A Friesner.   

Abstract

We report the tertiary structure predictions for 95 proteins ranging in size from 17 to 160 residues starting from known secondary structure. Predictions are obtained from global minimization of an empirical potential function followed by the application of a refined atomic overlap potential. The minimization strategy employed represents a variant of the Monte Carlo plus minimization scheme of Li and Scheraga applied to a reduced model of the protein chain. For all of the cases except beta-proteins larger than 75 residues, a native-like structure, usually 4-6 A root-mean-square deviation from the native, is located. For beta-proteins larger than 75 residues, the energy gap between native-like structures and the lowest energy structures produced in the simulation is large, so that low RMSD structures are not generated starting from an unfolded state. This is attributed to the lack of an explicit hydrogen bond term in the potential function, which we hypothesize is necessary to stabilize large assemblies of beta-strands. Copyright 1999 Academic Press.

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Year:  1999        PMID: 10329175     DOI: 10.1006/jmbi.1999.2702

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  13 in total

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2.  Packing helices in proteins by global optimization of a potential energy function.

Authors:  Marian Nanias; Maurizio Chinchio; Jarosław Pillardy; Daniel R Ripoll; Harold A Scheraga
Journal:  Proc Natl Acad Sci U S A       Date:  2003-02-05       Impact factor: 11.205

3.  Toward predicting protein topology: an approach to identifying beta hairpins.

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Journal:  Proc Natl Acad Sci U S A       Date:  2002-08-12       Impact factor: 11.205

4.  ASTRO-FOLD: a combinatorial and global optimization framework for Ab initio prediction of three-dimensional structures of proteins from the amino acid sequence.

Authors:  J L Klepeis; C A Floudas
Journal:  Biophys J       Date:  2003-10       Impact factor: 4.033

5.  An automatic method for predicting transmembrane protein structures using cryo-EM and evolutionary data.

Authors:  Sarel J Fleishman; Susan Harrington; Richard A Friesner; Barry Honig; Nir Ben-Tal
Journal:  Biophys J       Date:  2004-08-31       Impact factor: 4.033

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Journal:  Polymer (Guildf)       Date:  2005-05-26       Impact factor: 4.430

7.  A reexamination of correlations of amino acids with particular secondary structures.

Authors:  Sasa N Malkov; Miodrag V Zivković; Milos V Beljanski; Srdan D Stojanović; Snezana D Zarić
Journal:  Protein J       Date:  2009-02       Impact factor: 2.371

8.  A reexamination of the propensities of amino acids towards a particular secondary structure: classification of amino acids based on their chemical structure.

Authors:  Sasa N Malkov; Miodrag V Zivković; Milos V Beljanski; Michael B Hall; Snezana D Zarić
Journal:  J Mol Model       Date:  2008-05-27       Impact factor: 1.810

9.  Application of data mining tools for classification of protein structural class from residue based averaged NMR chemical shifts.

Authors:  Arun V Kumar; Rehana F M Ali; Yu Cao; V V Krishnan
Journal:  Biochim Biophys Acta       Date:  2015-03-07

10.  Predicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure prediction.

Authors:  Eshel Faraggi; Yuedong Yang; Shesheng Zhang; Yaoqi Zhou
Journal:  Structure       Date:  2009-11-11       Impact factor: 5.006

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