title: 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)8TIM-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 iMutantand 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.
authors.affiliation: Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Guindy Campus, Chennai, Tamilnadu, 600 025, India.
authors.forename: K M
authors.initials: KM
authors.lastname: Saravanan
authors.affiliation: Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tirchirappalli, Tamilnadu, 620 024, India.
authors.forename: S
authors.initials: S
authors.lastname: Suvaithenamudhan
authors.affiliation: Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tirchirappalli, Tamilnadu, 620 024, India.
authors.forename: S
authors.initials: S
authors.lastname: Parthasarathy
authors.affiliation: Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tirchirappalli, Tamilnadu, 620 024, India.
authors.forename: S
authors.initials: S
authors.lastname: Selvaraj
mesh_terms: D000595:Amino Acid Sequence; D005656:Fungal Proteins / Q000737:chemistry* / Q000235:genetics; D015233:Models, Statistical; D056004:Molecular Dynamics Simulation; D017354:Point Mutation; D000072756:Protein Conformation, alpha-Helical; D000072757:Protein Conformation, beta-Strand; D017510:Protein Folding; D054730:Protein Interaction Domains and Motifs; D012441:Saccharomyces cerevisiae / Q000737:chemistry / Q000201:enzymology; D013816:Thermodynamics; D014305:Triose-Phosphate Isomerase / Q000737:chemistry* / Q000235:genetics
chemical_list: D005656:Fungal Proteins; D014305:Triose-Phosphate Isomerase
keywords: TIM-Barrell fold; molecular dynamics simulation; pairwise residue contact energy; point mutations; protein folding