Pairwise contact energy statistical potentials can help to find probability of point mutations

Abstract

To adopt a particular fold, a protein requires several interactions between its amino acid residues. The energetic contribution of these residue-residue interactions can be approximated by extracting statistical potentials from known high resolution structures. Several methods based on statistical potentials extracted from unrelated proteins are found to make a better prediction of probability of point mutations. We postulate that the statistical potentials extracted from known structures of similar folds with varying sequence identity can be a powerful tool to examine probability of point mutation. By keeping this in mind, we have derived pairwise residue and atomic contact energy potentials for the different functional families that adopt the (α/β) TIM-Barrel fold. We carried out computational point mutations at various conserved residue positions in yeast Triose phosphate isomerase enzyme for which experimental results are already reported. We have also performed molecular dynamics simulations on a subset of point mutants to make a comparative study. The difference in pairwise residue and atomic contact energy of wildtype and various point mutations reveals probability of mutations at a particular position. Interestingly, we found that our computational prediction agrees with the experimental studies of Silverman et al. (Proc Natl Acad Sci 2001;98:3092-3097) and perform better prediction than i and Cologne University Protein Stability Analysis Tool. The present work thus suggests deriving pairwise contact energy potentials and molecular dynamics simulations of functionally important folds could help us to predict probability of point mutations which may ultimately reduce the time and cost of mutation experiments. Proteins 2016; 85:54-64. © 2016 Wiley Periodicals, Inc.

On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective

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Comparative Analysis of Inter Residue Contact Energy Potentials With Surrounding Hydrophobicity Model

“…As early as 1978, Manavalan and Ponnuswamy explored the hydrophobic environment of amino acid residues in globular proteins based on inter residue interactions which is termed as surrounding hydrophobicity model [8]. Later in 1990's, different statistical or empirical potentials based on inter residue interactions have been defined and their ability in discriminating the native structure from non-native ones has been explored for different proteins [9][10][11][12][13][14]. These statistical potentials use twenty amino acid alphabets and assume the energy contribution for a given residue pair regardless of its local environment.…”