Literature DB >> 12142455

Design of an optimal Chebyshev-expanded discrimination function for globular proteins.

Boris Fain1, Yu Xia, Michael Levitt.   

Abstract

We describe the construction of a scoring function designed to model the free energy of protein folding. An optimization technique is used to determine the best functional forms of the hydrophobic, residue-residue and hydrogen-bonding components of the potential. The scoring function is expanded by use of Chebyshev polynomials, the coefficients of which are determined by minimizing the score, in units of standard deviation, of native structures in the ensembles of alternate decoy conformations. The derived effective potential is then tested on decoy sets used conventionally in such studies. Using our scoring function, we achieve a high level of discrimination between correct and incorrect folds. In addition, our method is able to represent functions of arbitrary shape with fewer parameters than the usual histogram potentials of similar resolution. Finally, our representation can be combined easily with many optimization methods, because the total energy is a linear function of the parameters. Our results show that the techniques of Z-score optimization and Chebyshev expansion work well.

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Year:  2002        PMID: 12142455      PMCID: PMC2373672          DOI: 10.1110/ps.0200702

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  42 in total

1.  The ASTRAL compendium for protein structure and sequence analysis.

Authors:  S E Brenner; P Koehl; M Levitt
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  Protein tertiary structure recognition using optimized Hamiltonians with local interactions.

Authors:  R A Goldstein; Z A Luthey-Schulten; P G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  1992-10-01       Impact factor: 11.205

3.  Contact potential that recognizes the correct folding of globular proteins.

Authors:  V N Maiorov; G M Crippen
Journal:  J Mol Biol       Date:  1992-10-05       Impact factor: 5.469

4.  A lattice model for protein structure prediction at low resolution.

Authors:  D A Hinds; M Levitt
Journal:  Proc Natl Acad Sci U S A       Date:  1992-04-01       Impact factor: 11.205

5.  A new approach to protein fold recognition.

Authors:  D T Jones; W R Taylor; J M Thornton
Journal:  Nature       Date:  1992-07-02       Impact factor: 49.962

6.  Accurate modeling of protein conformation by automatic segment matching.

Authors:  M Levitt
Journal:  J Mol Biol       Date:  1992-07-20       Impact factor: 5.469

7.  SCOP: a structural classification of proteins database for the investigation of sequences and structures.

Authors:  A G Murzin; S E Brenner; T Hubbard; C Chothia
Journal:  J Mol Biol       Date:  1995-04-07       Impact factor: 5.469

8.  An improved pair potential to recognize native protein folds.

Authors:  A Bauer; A Beyer
Journal:  Proteins       Date:  1994-03

9.  An empirical energy function for threading protein sequence through the folding motif.

Authors:  S H Bryant; C E Lawrence
Journal:  Proteins       Date:  1993-05

10.  Prediction of protein structure by evaluation of sequence-structure fitness. Aligning sequences to contact profiles derived from three-dimensional structures.

Authors:  C Ouzounis; C Sander; M Scharf; R Schneider
Journal:  J Mol Biol       Date:  1993-08-05       Impact factor: 5.469

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  5 in total

1.  Can correct protein models be identified?

Authors:  Björn Wallner; Arne Elofsson
Journal:  Protein Sci       Date:  2003-05       Impact factor: 6.725

2.  Funnel sculpting for in silico assembly of secondary structure elements of proteins.

Authors:  Boris Fain; Michael Levitt
Journal:  Proc Natl Acad Sci U S A       Date:  2003-08-18       Impact factor: 11.205

3.  Mimicking the action of folding chaperones in molecular dynamics simulations: Application to the refinement of homology-based protein structures.

Authors:  Hao Fan; Alan E Mark
Journal:  Protein Sci       Date:  2004-03-09       Impact factor: 6.725

4.  Validation of protein models by a neural network approach.

Authors:  Paolo Mereghetti; Maria Luisa Ganadu; Elena Papaleo; Piercarlo Fantucci; Luca De Gioia
Journal:  BMC Bioinformatics       Date:  2008-01-29       Impact factor: 3.169

5.  Improved protein structure selection using decoy-dependent discriminatory functions.

Authors:  Kai Wang; Boris Fain; Michael Levitt; Ram Samudrala
Journal:  BMC Struct Biol       Date:  2004-06-18
  5 in total

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