scholarly journals Local Packing Density Is the Main Structural Determinant of the Rate of Protein Sequence Evolution at Site Level

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
So-Wei Yeh ◽  
Tsun-Tsao Huang ◽  
Jen-Wei Liu ◽  
Sung-Huan Yu ◽  
Chien-Hua Shih ◽  
...  
Keyword(s):  
Packing Density ◽  
Protein Sequence ◽  
Solvent Accessibility ◽  
Sequence Evolution ◽  
Relative Solvent Accessibility ◽  
Sequence Variability ◽  
Substitution Rates ◽  
Contact Number ◽  
Local Packing Density ◽  
Structural Determinant

Functional and biophysical constraints result in site-dependent patterns of protein sequence variability. It is commonly assumed that the key structural determinant of site-specific rates of evolution is the Relative Solvent Accessibility (RSA). However, a recent study found that amino acid substitution rates correlate better with two Local Packing Density (LPD) measures, the Weighted Contact Number (WCN) and the Contact Number (CN), than with RSA. This work aims at a more thorough assessment. To this end, in addition to substitution rates, we considered four other sequence variability scores, four measures of solvent accessibility (SA), and other CN measures. We compared all properties for each protein of a structurally and functionally diverse representative dataset of monomeric enzymes. We show that the best sequence variability measures take into account phylogenetic tree topology. More importantly, we show that both LPD measures (WCN and CN) correlate better than all of the SA measures, regardless of the sequence variability score used. Moreover, the independent contribution of the best LPD measure is approximately four times larger than that of the best SA measure. This study strongly supports the conclusion that a site’s packing density rather than its solvent accessibility is the main structural determinant of its rate of evolution.

scholarly journals Dissecting the roles of local packing density and longer-range effects in protein sequence evolution

2015 ◽  
Author(s):  
Amir Shahmoradi ◽  
Claus O Wilke
Keyword(s):  
Packing Density ◽  
Solvent Accessibility ◽  
Voronoi Cell ◽  
Sequence Evolution ◽  
Relative Importance ◽  
Site Specific ◽  
Contact Number ◽  
Evolutionary Variation ◽  
Local Packing Density ◽  
Protein Sequence Evolution

What are the structural determinants of protein sequence evolution? A number of site-specific structural characteristics have been proposed, most of which are broadly related to either the density of contacts or the solvent accessibility of individual residues. Most importantly, there has been disagreement in the literature over the relative importance of solvent accessibility and local packing density for explaining site-specific sequence variability in proteins. We show here that this discussion has been confounded by the definition of local packing density. The most commonly used measures of local packing, such as the contact number and the weighted contact number, represent by definition the combined effects of local packing density and longer-range effects. As an alternative, we here propose a truly local measure of packing density around a single residue, based on the Voronoi cell volume. We show that the Voronoi cell volume, when calculated relative to the geometric center of amino-acid side chains, behaves nearly identically to the relative solvent accessibility, and both can explain, on average, approximately 34\% of the site-specific variation in evolutionary rate in a data set of 209 enzymes. An additional 10\% of variation can be explained by non-local effects that are captured in the weighted contact number. Consequently, evolutionary variation at a site is determined by the combined action of the immediate amino-acid neighbors of that site and of effects mediated by more distant amino acids. We conclude that instead of contrasting solvent accessibility and local packing density, future research should emphasize the relative importance of immediate contacts and longer-range effects on evolutionary variation.

scholarly journals Protein evolution is structure dependent and non-homogeneous across the tree of life

2020 ◽  
Author(s):  
Akanksha Pandey ◽  
Edward L. Braun
Keyword(s):  
Mixture Models ◽  
Protein Evolution ◽  
Protein Sequence ◽  
Solvent Accessibility ◽  
Tree Of Life ◽  
Supplementary Information ◽  
Amino Acid Side Chain ◽  
Sequence Evolution ◽  
Relative Solvent Accessibility ◽  
Protein Sequence Evolution

AbstractMotivationProtein sequence evolution is a complex process that varies among-sites within proteins and across the tree of life. Comparisons of evolutionary rate matrices for specific taxa (‘clade-specific models’) have the potential to reveal this variation and provide information about the underlying reasons for those changes. To study changes in patterns of protein sequence evolution we estimated and compared clade-specific models in a way that acknowledged variation within proteins due to structure.ResultsClade-specific model fit was able to correctly classify proteins from four specific groups (vertebrates, plants, oomycetes, and yeasts) more than 70% of the time. This was true whether we used mixture models that incorporate relative solvent accessibility or simple models that treat sites as homogeneous. Thus, protein evolution is non-homogeneous over the tree of life. However, a small number of dimensions could explain the differences among models (for mixture models ~50% of the variance reflected relative solvent accessibility and ~25% reflected clade). Relaxed purifying selection in taxa with lower long-term effective population sizes appears to explain much of the among clade variance. Relaxed selection on solvent-exposed sites was correlated with changes in amino acid side-chain volume; other differences among models were more complex. Beyond the information they reveal about protein evolution, our clade-specific models also represent tools for phylogenomic inference.AvailabilityModel files are available from https://github.com/ebraun68/[email protected] informationSupplementary data are appended to this preprint.

scholarly journals Improved computational methods of protein sequence alignment, model selection and tertiary structure prediction

2013 ◽  
Author(s):  
◽  
Xin Deng
Keyword(s):  
Protein Structure ◽  
Secondary Structure ◽  
Model Selection ◽  
Sequence Alignment ◽  
Protein Sequence ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Solvent Accessibility ◽  
Relative Solvent Accessibility ◽  
Tertiary Structure Prediction

Protein sequence and profile alignment has been used essentially in most bioinformatics tasks such as protein structure modeling, function prediction, and phylogenetic analysis. We designed a new algorithm MSACompro to incorporate predicted secondary structure, relative solvent accessibility, and residue-residue contact information into multiple protein sequence alignment. Our experiments showed that it improved multiple sequence alignment accuracy over most existing methods without using the structural information and performed comparably to the method using structural features and additional homologous sequences by slightly lower scores. We also developed HHpacom, a new profile-profile pairwise alignment by integrating secondary structure, solvent accessibility, torsion angle and inferred residue pair coupling information. The evaluation showed that the secondary structure, relative solvent accessibility and torsion angle information significantly improved the alignment accuracy in comparison with the state of the art methods HHsearch and HHsuite. The evolutionary constraint information did help in some cases, especially the alignments of the proteins which are of short lengths, typically 100 to 500 residues. Protein Model selection is also a key step in protein tertiary structure prediction. We developed two SVM model quality assessment methods taking query-template alignment as input. The assessment results illustrated that this could help improve the model selection, protein structure prediction and many other bioinformatics problems. Moreover, we also developed a protein tertiary structure prediction pipeline, of which many components were built in our group’s MULTICOM system. The MULTICOM performed well in the CASP10 (Critical Assessment of Techniques for Protein Structure Prediction) competition.

scholarly journals Predicting evolutionary site variability from structure in viral proteins: buriedness, packing, flexibility, and design

2014 ◽  
Author(s):  
Amir Shahmoradi ◽  
Dariya K. Sydykova ◽  
Stephanie J. Spielman ◽  
Eleisha L. Jackson ◽  
Eric T. Dawson ◽  
...  
Keyword(s):  
Structural Properties ◽  
Packing Density ◽  
Sequence Variation ◽  
Solvent Accessibility ◽  
Protein Structures ◽  
Structural Flexibility ◽  
Relative Solvent Accessibility ◽  
Dynamic Simulations ◽  
Evolutionary Variation ◽  
Flexibility Measures

Several recent works have shown that protein structure can predict site-specific evolutionary sequence variation. In particular, sites that are buried and/or have many contacts with other sites in a structure have been shown to evolve more slowly, on average, than surface sites with few contacts. Here, we present a comprehensive study of the extent to which numerous structural properties can predict sequence variation. The quantities we considered include buriedness (as measured by relative solvent accessibility), packing density (as measured by contact number), structural flexibility (as measured by B factors, root-mean-square fluctuations, and variation in dihedral angles), and variability in designed structures. We obtained structural flexibility measures both from molecular dynamics simulations performed on 9 non-homologous viral protein structures and from variation in homologous variants of those proteins, where available. We obtained measures of variability in designed structures from flexible-backbone design in the Rosetta software. We found that most of the structural properties correlate with site variation in the majority of structures, though the correlations are generally weak (correlation coefficients of 0.1 to 0.4). Moreover, we found that buriedness and packing density were better predictors of evolutionary variation than was structural flexibility. Finally, variability in designed structures was a weaker predictor of evolutionary variability than was buriedness or packing density, but it was comparable in its predictive power to the best structural flexibility measures. We conclude that simple measures of buriedness and packing density are better predictors of evolutionary variation than are more complicated predictors obtained from dynamic simulations, ensembles of homologous structures, or computational protein design.

scholarly journals Roles of Solvent Accessibility and Gene Expression in Modeling Protein Sequence Evolution

2015 ◽  
Vol 11 ◽  
pp. EBO.S22911 ◽  
Author(s):  
Kuangyu Wang ◽  
Shuhui Yu ◽  
Xiang Ji ◽  
Clemens Lakner ◽  
Alexander Griffing ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Sequence ◽  
Solvent Accessibility ◽  
Sequence Evolution ◽  
Protein Sequence Evolution
Sign in / Sign up

Export Citation Format

Share Document