Literature DB >> 10048329

Pair potentials for protein folding: choice of reference states and sensitivity of predicted native states to variations in the interaction schemes.

M R Betancourt1, D Thirumalai.   

Abstract

We examine the similarities and differences between two widely used knowledge-based potentials, which are expressed as contact matrices (consisting of 210 elements) that gives a scale for interaction energies between the naturally occurring amino acid residues. These are the Miyazawa-Jernigan contact interaction matrix M and the potential matrix S derived by Skolnick J et al., 1997, Protein Sci 6:676-688. Although the correlation between the two matrices is good, there is a relatively large dispersion between the elements. We show that when Thr is chosen as a reference solvent within the Miyazawa and Jernigan scheme, the dispersion between the M and S matrices is reduced. The resulting interaction matrix B gives hydrophobicities that are in very good agreement with experiment. The small dispersion between the S and B matrices, which arises due to differing reference states, is shown to have dramatic effect on the predicted native states of lattice models of proteins. These findings and other arguments are used to suggest that for reliable predictions of protein structures, pairwise additive potentials are not sufficient. We also establish that optimized protein sequences can tolerate relatively large random errors in the pair potentials. We conjecture that three body interaction may be needed to predict the folds of proteins in a reliable manner.

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Year:  1999        PMID: 10048329      PMCID: PMC2144252          DOI: 10.1110/ps.8.2.361

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


  20 in total

1.  Medium- and long-range interaction parameters between amino acids for predicting three-dimensional structures of proteins.

Authors:  S Tanaka; H A Scheraga
Journal:  Macromolecules       Date:  1976 Nov-Dec       Impact factor: 5.985

2.  How do potentials derived from structural databases relate to "true" potentials?

Authors:  L Zhang; J Skolnick
Journal:  Protein Sci       Date:  1998-01       Impact factor: 6.725

Review 3.  Structure-derived potentials and protein simulations.

Authors:  R L Jernigan; I Bahar
Journal:  Curr Opin Struct Biol       Date:  1996-04       Impact factor: 6.809

Review 4.  Knowledge-based potentials for protein folding: what can we learn from known protein structures?

Authors:  A Godzik
Journal:  Structure       Date:  1996-04-15       Impact factor: 5.006

5.  Derivation and testing of pair potentials for protein folding. When is the quasichemical approximation correct?

Authors:  J Skolnick; L Jaroszewski; A Kolinski; A Godzik
Journal:  Protein Sci       Date:  1997-03       Impact factor: 6.725

6.  Hydrophilicity of polar amino acid side-chains is markedly reduced by flanking peptide bonds.

Authors:  M A Roseman
Journal:  J Mol Biol       Date:  1988-04-05       Impact factor: 5.469

7.  Statistical potentials extracted from protein structures: how accurate are they?

Authors:  P D Thomas; K A Dill
Journal:  J Mol Biol       Date:  1996-03-29       Impact factor: 5.469

8.  Why do protein architectures have Boltzmann-like statistics?

Authors:  A V Finkelstein; A M Gutin
Journal:  Proteins       Date:  1995-10

9.  Reduced representation model of protein structure prediction: statistical potential and genetic algorithms.

Authors:  S Sun
Journal:  Protein Sci       Date:  1993-05       Impact factor: 6.725

10.  Origins of structure in globular proteins.

Authors:  H S Chan; K A Dill
Journal:  Proc Natl Acad Sci U S A       Date:  1990-08       Impact factor: 11.205

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  101 in total

1.  A statistical mechanical method to optimize energy functions for protein folding.

Authors:  U Bastolla; M Vendruscolo; E W Knapp
Journal:  Proc Natl Acad Sci U S A       Date:  2000-04-11       Impact factor: 11.205

2.  Scoring functions in protein folding and design.

Authors:  R I Dima; J R Banavar; A Maritan
Journal:  Protein Sci       Date:  2000-04       Impact factor: 6.725

3.  Analysis of knowledge-based protein-ligand potentials using a self-consistent method.

Authors:  J Shimada; A V Ishchenko; E I Shakhnovich
Journal:  Protein Sci       Date:  2000-04       Impact factor: 6.725

4.  Native topology determines force-induced unfolding pathways in globular proteins.

Authors:  D K Klimov; D Thirumalai
Journal:  Proc Natl Acad Sci U S A       Date:  2000-06-20       Impact factor: 11.205

5.  Structure-based prediction of binding peptides to MHC class I molecules: application to a broad range of MHC alleles.

Authors:  O Schueler-Furman; Y Altuvia; A Sette; H Margalit
Journal:  Protein Sci       Date:  2000-09       Impact factor: 6.725

6.  Statistical potentials for fold assessment.

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

7.  Discrimination of native protein structures using atom-atom contact scoring.

Authors:  Brendan J McConkey; Vladimir Sobolev; Marvin Edelman
Journal:  Proc Natl Acad Sci U S A       Date:  2003-03-11       Impact factor: 11.205

8.  An accurate, residue-level, pair potential of mean force for folding and binding based on the distance-scaled, ideal-gas reference state.

Authors:  Chi Zhang; Song Liu; Hongyi Zhou; Yaoqi Zhou
Journal:  Protein Sci       Date:  2004-02       Impact factor: 6.725

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

Authors:  Boris Fain; Yu Xia; Michael Levitt
Journal:  Protein Sci       Date:  2002-08       Impact factor: 6.725

10.  Proteomics in Vaccinology and Immunobiology: An Informatics Perspective of the Immunone.

Authors:  Irini A. Doytchinova; Paul Taylor; Darren R. Flower
Journal:  J Biomed Biotechnol       Date:  2003
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