Literature DB >> 15688450

Inferring ideal amino acid interaction forms from statistical protein contact potentials.

Piotr Pokarowski1, Andrzej Kloczkowski, Robert L Jernigan, Neha S Kothari, Maria Pokarowska, Andrzej Kolinski.   

Abstract

We have analyzed 29 different published matrices of protein pairwise contact potentials (CPs) between amino acids derived from different sets of proteins, either crystallographic structures taken from the Protein Data Bank (PDB) or computer-generated decoys. Each of the CPs is similar to 1 of the 2 matrices derived in the work of Miyazawa and Jernigan (Proteins 1999;34:49-68). The CP matrices of the first class can be approximated with a correlation of order 0.9 by the formula e(ij) = h(i) + h(j), 1 <or= i, j <or= 20, where the residue-type dependent factor h is highly correlated with the frequency of occurrence of a given amino acid type inside proteins. Electrostatic interactions for the potentials of this class are almost negligible. In the potentials belonging to this class, the major contribution to the potentials is the one-body transfer energy of the amino acid from water to the protein environment. Potentials belonging to the second class can be approximated with a correlation of 0.9 by the formula e(ij) = c(0) - h(i)h(j) + q(i)q(j), where c(0) is a constant, h is highly correlated with the Kyte-Doolittle hydrophobicity scale, and a new, less dominant, residue-type dependent factor q is correlated ( approximately 0.9) with amino acid isoelectric points pI. Including electrostatic interactions significantly improves the approximation for this class of potentials. While, the high correlation between potentials of the first class and the hydrophobic transfer energies is well known, the fact that this approximation can work well also for the second class of potentials is a new finding. We interpret potentials of this class as representing energies of contact of amino acid pairs within an average protein environment. (c) 2005 Wiley-Liss, Inc.

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Year:  2005        PMID: 15688450      PMCID: PMC4417612          DOI: 10.1002/prot.20380

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


  49 in total

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  21 in total

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10.  Residue contact-count potentials are as effective as residue-residue contact-type potentials for ranking protein decoys.

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