313 research outputs found
An Analytical Approach to the Protein Designability Problem
We present an analytical method for determining the designability of protein
structures. We apply our method to the case of two-dimensional lattice
structures, and give a systematic solution for the spectrum of any structure.
Using this spectrum, the designability of a structure can be estimated. We
outline a heirarchy of structures, from most to least designable, and show that
this heirarchy depends on the potential that is used.Comment: 16 pages 4 figure
Sequence correlations shape protein promiscuity
We predict analytically that diagonal correlations of amino acid positions
within protein sequences statistically enhance protein propensity for
nonspecific binding. We use the term 'promiscuity' to describe such nonspecific
binding. Diagonal correlations represent statistically significant repeats of
sequence patterns where amino acids of the same type are clustered together.
The predicted effect is qualitatively robust with respect to the form of the
microscopic interaction potentials and the average amino acid composition. Our
analytical results provide an explanation for the enhanced diagonal
correlations observed in hubs of eukaryotic organismal proteomes [J. Mol. Biol.
409, 439 (2011)]. We suggest experiments that will allow direct testing of the
predicted effect
Protein and DNA sequence determinants of thermophilic adaptation
Prokaryotes living at extreme environmental temperatures exhibit pronounced
signatures in the amino acid composition of their proteins and nucleotide
compositions of their genomes reflective of adaptation to their thermal
environments. However, despite significant efforts, the definitive answer of
what are the genomic and proteomic compositional determinants of Optimal Growth
Temperature of prokaryotic organisms remained elusive. Here the authors
performed a comprehensive analysis of amino acid and nucleotide compositional
signatures of thermophylic adaptation by exhaustively evaluating all
combinations of amino acids and nucleotides as possible determinants of Optimal
Growth Temperature for all prokaryotic organisms with fully sequences genomes..
The authors discovered that total concentration of seven amino acids in
proteomes, IVYWREL, serves as a universal proteomic predictor of Optimal Growth
Temperature in prokaryotes. Resolving the old-standing controversy the authors
determined that the variation in nucleotide composition (increase of purine
load, or A+G content with temperature) is largely a consequence of thermal
adaptation of proteins. However, the frequency with which A and G nucleotides
appear as nearest neighbors in genome sequences is strongly and independently
correlated with Optimal Growth Temperature. as a result of codon bias in
corresponding genomes. Together these results provide a complete picture of
proteomic and genomic determinants of thermophilic adaptation.Comment: in press PLoS Computational Biology; revised versio
Mapping of mutation-sensitive sites in protein-like chains
In this work we have studied, with the help of a simple on-lattice model, the
distribution pattern of sites sensitive to point mutations ('hot' sites) in
protein-like chains. It has been found that this pattern depends on the
regularity of the matrix that rules the interaction between different kinds of
residues. If the interaction matrix is dominated by the hydrophobic effect
(Miyazawa Jernigan like matrix), this distribution is very simple - all the
'hot' sites can be found at the positions with maximum number of closest
nearest neighbors (bulk).
If random or nonlinear corrections are added to such an interaction matrix
the distribution pattern changes. The rising of collective effects allows the
'hot' sites to be found in places with smaller number of nearest neighbors
(surface) while the general trend of the 'hot' sites to fall into a bulk part
of a conformation still holds.Comment: 15 pages, 6 figure
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