Browse
Submit Data
Databases
API
Help

Dataset Information

29 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

The relationship between relative solvent accessibility and evolutionary rate in protein evolution.

ABSTRACT: Recent work with Saccharomyces cerevisiae shows a linear relationship between the evolutionary rate of sites and the relative solvent accessibility (RSA) of the corresponding residues in the folded protein. Here, we aim to develop a mathematical model that can reproduce this linear relationship. We first demonstrate that two models that both seem reasonable choices (a simple model in which selection strength correlates with RSA and a more complex model based on RSA-dependent amino acid distributions) fail to reproduce the observed relationship. We then develop a model on the basis of observed site-specific amino acid distributions and show that this model behaves appropriately. We conclude that evolutionary rates are directly linked to the distribution of amino acids at individual sites. Because of this link, any future insight into the biophysical mechanisms that determine amino acid distributions will improve our understanding of evolutionary rates.

SUBMITTER: Ramsey DC

PROVIDER: S-EPMC3122320 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

The relationship between relative solvent accessibility and evolutionary rate in protein evolution.

Ramsey Duncan C DC Scherrer Michael P MP Zhou Tong T Wilke Claus O CO

Genetics 20110405 2

Recent work with Saccharomyces cerevisiae shows a linear relationship between the evolutionary rate of sites and the relative solvent accessibility (RSA) of the corresponding residues in the folded protein. Here, we aim to develop a mathematical model that can reproduce this linear relationship. We first demonstrate that two models that both seem reasonable choices (a simple model in which selection strength correlates with RSA and a more complex model based on RSA-dependent amino acid distribut ...[more]

PMID: 21467571

Similar Datasets

Accurate prediction of protein relative solvent accessibility using a balanced model.

Project description:BackgroundProtein relative solvent accessibility provides insight into understanding protein structure and function. Prediction of protein relative solvent accessibility is often the first stage of predicting other protein properties. Recent predictors of relative solvent accessibility discriminate against exposed regions as compared with buried regions, resulting in higher prediction accuracy associated with buried regions relative to exposed regions.MethodsHere, we propose a more accurate and balanced predictor of protein relative solvent accessibility. First, we collected known proteins in three subsets according to sequence length and constructed a balanced dataset after reducing redundancy within each subset. Next, we measured the performance associated with different variables and variable combinations to determine the best variable combination. Finally, a predictor called BMRSA was constructed for modelling and prediction, which used the balanced set as the training set, the position- specific scoring matrix, predicted secondary structure, buried-exposed profile, and length of a query sequence as variables, and the conditional random field as the machine-learning method.ResultsBMRSA performance on test sets confirmed that our approach improved prediction accuracy relative to state-of-the-art approaches and was balanced in its comparison of buried and exposed regions. Our method is valuable when higher levels of accuracy in predicting exposed-residue states are required. The BMRSA is available at: http://cheminfo.tongji.edu.cn:8080/BMRSA/.

| S-EPMC5259893 | biostudies-literature

Roles of solvent accessibility and gene expression in modeling protein sequence evolution.

Project description:Models of protein evolution tend to ignore functional constraints, although structural constraints are sometimes incorporated. Here we propose a probabilistic framework for codon substitution that evaluates joint effects of relative solvent accessibility (RSA), a structural constraint; and gene expression, a functional constraint. First, we explore the relationship between RSA and codon usage at the genomic scale as well as at the individual gene scale. Motivated by these results, we construct our framework by determining how probable is an amino acid, given RSA and gene expression, and then evaluating the relative probability of observing a codon compared to other synonymous codons. We come to the biologically plausible conclusion that both RSA and gene expression are related to amino acid frequencies, but, among synonymous codons, the relative probability of a particular codon is more closely related to gene expression than RSA. To illustrate the potential applications of our framework, we propose a new codon substitution model. Using this model, we obtain estimates of 2N s, the product of effective population size N, and relative fitness difference of allele s. For a training data set consisting of human proteins with known structures and expression data, 2N s is estimated separately for synonymous and nonsynonymous substitutions in each protein. We then contrast the patterns of synonymous and nonsynonymous 2N s estimates across proteins while also taking gene expression levels of the proteins into account. We conclude that our 2N s estimates are too concentrated around 0, and we discuss potential explanations for this lack of variability.

| S-EPMC4415675 | biostudies-literature

Scatter-search with support vector machine for prediction of relative solvent accessibility.

Project description:Proteins have vital roles in the living cells. The protein function is almost completely dependent on protein structure. The prediction of relative solvent accessibility gives helpful information for the prediction of tertiary structure of a protein. In recent years several relative solvent accessibility (RSA) prediction methods including those that generate real values and those that predict discrete states have been developed. The proposed method consists of two main steps: the first one, provided subset selection of quantitative features based on selected qualitative features and the second, dedicated to train a model with selected quantitative features for RSA prediction. The results show that the proposed method has an improvement in average prediction accuracy and training time. The proposed method can dig out all the valuable knowledge about which physicochemical features of amino acids are deemed more important in prediction of RSA without human supervision, which is of great importance for biologists and their future researches.

| S-EPMC4531788 | biostudies-literature

Lineage-specific sequence evolution and exon edge conservation partially explain the relationship between evolutionary rate and expression level in A. thaliana.

Project description:Rapidly evolving proteins can aid the identification of genes underlying phenotypic adaptation across taxa, but functional and structural elements of genes can also affect evolutionary rates. In plants, the 'edges' of exons, flanking intron junctions, are known to contain splice enhancers and to have a higher degree of conservation compared to the remainder of the coding region. However, the extent to which these regions may be masking indicators of positive selection or account for the relationship between dN/dS and other genomic parameters is unclear. We investigate the effects of exon edge conservation on the relationship of dN/dS to various sequence characteristics and gene expression parameters in the model plant Arabidopsis thaliana. We also obtain lineage-specific dN/dS estimates, making use of the recently sequenced genome of Thellungiella parvula, the second closest sequenced relative after the sister species Arabidopsis lyrata. Overall, we find that the effect of exon edge conservation, as well as the use of lineage-specific substitution estimates, upon dN/dS ratios partly explains the relationship between the rates of protein evolution and expression level. Furthermore, the removal of exon edges shifts dN/dS estimates upwards, increasing the proportion of genes potentially under adaptive selection. We conclude that lineage-specific substitutions and exon edge conservation have an important effect on dN/dS ratios and should be considered when assessing their relationship with other genomic parameters.

| S-EPMC4480654 | biostudies-literature

An account of solvent accessibility in protein-RNA recognition.

Project description:Protein-RNA recognition often induces conformational changes in binding partners. Consequently, the solvent accessible surface area (SASA) buried in contact estimated from the co-crystal structures may differ from that calculated using their unbound forms. To evaluate the change in accessibility upon binding, we compare SASA of 126 protein-RNA complexes between bound and unbound forms. We observe, in majority of cases the interface of both the binding partners gain accessibility upon binding, which is often associated with either large domain movements or secondary structural transitions in RNA-binding proteins (RBPs), and binding-induced conformational changes in RNAs. At the non-interface region, majority of RNAs lose accessibility upon binding, however, no such preference is observed for RBPs. Side chains of RBPs have major contribution in change in accessibility. In case of flexible binding, we find a moderate correlation between the binding free energy and change in accessibility at the interface. Finally, we introduce a parameter, the ratio of gain to loss of accessibility upon binding, which can be used to identify the native solution among the flexible docking models. Our findings provide fundamental insights into the relationship between flexibility and solvent accessibility, and advance our understanding on binding induced folding in protein-RNA recognition.

| S-EPMC6043566 | biostudies-literature

Macromolecular Crowding Tunes Protein Stability by Manipulating Solvent Accessibility.

Project description:In all intracellular processes, protein structure and dynamics are subject to the influence of macromolecular crowding (MC). Here, the impact of MC agents of different types and sizes on the model protein Bacillus subtilis Cold shock protein B (BsCspB) during both thermal and chemical denaturation have been comprehensively investigated. We consistently reveal a distinct stabilization of BsCspB in a manner dependent on the MC concentration but not on viscosity, polarity, or size of the MC agent used. This general stabilization has been decoded by use of NMR spectroscopy, through monitoring of chemical shift (CS) perturbations and the intramolecular hydrogen-bonding networks, as well as local protection of amide protons against exchange with solvent protons. Whereas CSs and hydrogen-bonding networks are not systematically affected in the presence of MC, we detected a pronounced reduction in exchange in loop regions of BsCspB. We conclude that this reduced accessibility of solvent protons is a key parameter for the increases in protein stability seen under MC.

| S-EPMC6582440 | biostudies-literature

The Identification of Metal Ion Ligand-Binding Residues by Adding the Reclassified Relative Solvent Accessibility.

Project description:Many proteins realize their special functions by binding with specific metal ion ligands during a cell's life cycle. The ability to correctly identify metal ion ligand-binding residues is valuable for the human health and the design of molecular drug. Precisely identifying these residues, however, remains challenging work. We have presented an improved computational approach for predicting the binding residues of 10 metal ion ligands (Zn2+, Cu2+, Fe2+, Fe3+, Co2+, Ca2+, Mg2+, Mn2+, Na+, and K+) by adding reclassified relative solvent accessibility (RSA). The best accuracy of fivefold cross-validation was higher than 77.9%, which was about 16% higher than the previous result on the same dataset. It was found that different reclassification of the RSA information can make different contributions to the identification of specific ligand binding residues. Our study has provided an additional understanding of the effect of the RSA on the identification of metal ion ligand binding residues.

| S-EPMC7096583 | biostudies-literature

Identification of protein-protein interfaces by decreased amide proton solvent accessibility.

Project description:Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry was used to identify peptic fragments from protein complexes that retained deuterium under hydrogen exchange conditions due to decreased solvent accessibility at the interface of the complex. Short deuteration times allowed preferential labeling of rapidly exchanging surface amides so that primarily solvent accessibility changes and not conformational changes were detected. A single mass spectrum of the peptic digest mixture was analyzed to determine the deuterium content of all proteolytic fragments of the protein. The protein-protein interface was reliably indicated by those peptides that retained more deuterons in the complex compared with control experiments in which only one protein was present. The method was used to identify the kinase inhibitor [PKI(5-24)] and ATP-binding sites in the cyclic-AMP-dependent protein kinase. Three overlapping peptides identified the ATP-binding site, three overlapping peptides identified the glycine-rich loop, and two peptides identified the PKI(5-24)-binding site. A complex of unknown structure also was analyzed, human alpha-thrombin bound to an 83-aa fragment of human thrombomodulin [TMEGF(4-5)]. Five peptides from thrombin showed significantly decreased solvent accessibility in the complex. Three peptides identified the anion-binding exosite I, confirming ligand competition experiments. Two peptides identified a new region of thrombin near the active site providing a potential mechanism of how thrombomodulin alters thrombin substrate specificity.

| S-EPMC24513 | biostudies-literature

The relationship among gene expression, the evolution of gene dosage, and the rate of protein evolution.

Project description:The understanding of selective constraints affecting genes is a major issue in biology. It is well established that gene expression level is a major determinant of the rate of protein evolution, but the reasons for this relationship remain highly debated. Here we demonstrate that gene expression is also a major determinant of the evolution of gene dosage: the rate of gene losses after whole genome duplications in the Paramecium lineage is negatively correlated to the level of gene expression, and this relationship is not a byproduct of other factors known to affect the fate of gene duplicates. This indicates that changes in gene dosage are generally more deleterious for highly expressed genes. This rule also holds for other taxa: in yeast, we find a clear relationship between gene expression level and the fitness impact of reduction in gene dosage. To explain these observations, we propose a model based on the fact that the optimal expression level of a gene corresponds to a trade-off between the benefit and cost of its expression. This COSTEX model predicts that selective pressure against mutations changing gene expression level or affecting the encoded protein should on average be stronger in highly expressed genes and hence that both the frequency of gene loss and the rate of protein evolution should correlate negatively with gene expression. Thus, the COSTEX model provides a simple and common explanation for the general relationship observed between the level of gene expression and the different facets of gene evolution.

| S-EPMC2869310 | biostudies-literature

Role of solvent accessibility for aggregation-prone patches in protein folding.

Project description:The arrangement of amino acids in a protein sequence encodes its native folding. However, the same arrangement in aggregation-prone regions may cause misfolding as a result of local environmental stress. Under normal physiological conditions, such regions congregate in the protein's interior to avoid aggregation and attain the native fold. We have used solvent accessibility of aggregation patches (SAAPp) to determine the packing of aggregation-prone residues. Our results showed that SAAPp has low values for native crystal structures, consistent with protein folding as a mechanism to minimize the solvent accessibility of aggregation-prone residues. SAAPp also shows an average correlation of 0.76 with the global distance test (GDT) score on CASP12 template-based protein models. Using SAAPp scores and five structural features, a random forest machine learning quality assessment tool, SAAP-QA, showed 2.32 average GDT loss between best model predicted and actual best based on GDT score on independent CASP test data, with the ability to discriminate native-like folds having an AUC of 0.94. Overall, the Pearson correlation coefficient (PCC) between true and predicted GDT scores on independent CASP data was 0.86 while on the external CAMEO dataset, comprising high quality protein structures, PCC and average GDT loss were 0.71 and 4.46 respectively. SAAP-QA can be used to detect the quality of models and iteratively improve them to native or near-native structures.

| S-EPMC6110721 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data