Literature DB >> 8429556

Estimation and use of protein backbone angle probabilities.

H S Kang1, N A Kurochkina, B Lee.   

Abstract

A procedure is described for estimating the probabilities for the backbone phi-psi angles of a protein molecule from the data base of known protein structures. The procedure is basically an adaptation of a published secondary structure prediction scheme, applied to the phi-psi angle bins rather than to the secondary types. The phi-psi angle probabilities estimated this way include all effects of local sequence and are "context sensitive" in that the probabilities for a given residue type depend on its position along the sequence. These probabilities can be used to predict the three-dimensional structure of short polypeptides that are stabilized mainly by local interactions only and to predict the protein folding initiation sites, with moderate to good success rates in each case. They are also potentially useful for efficient sampling in a Monte Carlo scheme of protein tertiary structure prediction methods.

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Year:  1993        PMID: 8429556     DOI: 10.1006/jmbi.1993.1045

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


  17 in total

1.  Propensities, probabilities, and the Boltzmann hypothesis.

Authors:  David Shortle
Journal:  Protein Sci       Date:  2003-06       Impact factor: 6.725

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

Authors:  Xavier de la Cruz; E Gail Hutchinson; Adrian Shepherd; Janet M Thornton
Journal:  Proc Natl Acad Sci U S A       Date:  2002-08-12       Impact factor: 11.205

3.  Database-derived potentials dependent on protein size for in silico folding and design.

Authors:  Yves Dehouck; Dimitri Gilis; Marianne Rooman
Journal:  Biophys J       Date:  2004-07       Impact factor: 4.033

4.  Statistical coil model of the unfolded state: resolving the reconciliation problem.

Authors:  Abhishek K Jha; Andrés Colubri; Karl F Freed; Tobin R Sosnick
Journal:  Proc Natl Acad Sci U S A       Date:  2005-08-30       Impact factor: 11.205

5.  A new generation of statistical potentials for proteins.

Authors:  Y Dehouck; D Gilis; M Rooman
Journal:  Biophys J       Date:  2006-03-13       Impact factor: 4.033

6.  Improving the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins by guided-learning through a two-layer neural network.

Authors:  Eshel Faraggi; Bin Xue; Yaoqi Zhou
Journal:  Proteins       Date:  2009-03

7.  An entropy criterion to detect minimally frustrated intermediates in native proteins.

Authors:  M Compiani; P Fariselli; P L Martelli; R Casadio
Journal:  Proc Natl Acad Sci U S A       Date:  1998-08-04       Impact factor: 11.205

8.  Discriminating compact nonnative structures from the native structure of globular proteins.

Authors:  Y Wang; H Zhang; W Li; R A Scott
Journal:  Proc Natl Acad Sci U S A       Date:  1995-01-31       Impact factor: 11.205

9.  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

10.  Prediction of Protein Backbone Torsion Angles Using Deep Residual Inception Neural Networks.

Authors:  Chao Fang; Yi Shang; Dong Xu
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2018-03-12       Impact factor: 3.710

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