Evolutionary constraints on yeast protein size

Background  

Despite a strong evolutionary pressure to reduce genome size, proteins vary in length over a surprisingly wide range also in very compact genomes. Here we investigated the evolutionary forces that act on protein size in the yeast Saccharomyces cerevisiae utilizing a system-wide bioinformatics approach. Data on yeast protein size was compared to global experimental data on protein expression, phenotypic pleiotropy, protein-protein interactions, protein evolutionary rate and biochemical classification.     

Reconstruction of ancestral protein sequences and its applications

Background  

Modern-day proteins were selected during long evolutionary history as descendants of ancient life forms. In silico reconstruction of such ancestral protein sequences facilitates our understanding of evolutionary processes, protein classification and biological function. Additionally, reconstructed ancestral protein sequences could serve to fill in sequence space thus aiding remote homology inference.     

Comparative analysis of the <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis> and <Emphasis Type="Italic">Caenorhabditis elegans</Emphasis> protein interaction networks

Background  

Protein interaction networks aim to summarize the complex interplay of proteins in an organism. Early studies suggested that the position of a protein in the network determines its evolutionary rate but there has been considerable disagreement as to what extent other factors, such as protein abundance, modify this reported dependence.     

Variability and conservation in hepatitis B virus core protein

Background  

Hepatitis B core protein (HBVc) has been extensively studied from both a structural and immunological point of view, but the evolutionary forces driving sequence variation within core are incompletely understood.     

Ab initio and homology based prediction of protein domains by recursive neural networks

Background  

Proteins, especially larger ones, are often composed of individual evolutionary units, domains, which have their own function and structural fold. Predicting domains is an important intermediate step in protein analyses, including the prediction of protein structures.     

Visualisation and graph-theoretic analysis of a large-scale protein structural interactome

Background  

Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network.     

Detection of distant evolutionary relationships between protein families using theory of sequence profile-profile comparison

Background  

Detection of common evolutionary origin (homology) is a primary means of inferring protein structure and function. At present, comparison of protein families represented as sequence profiles is arguably the most effective homology detection strategy. However, finding the best way to represent evolutionary information of a protein sequence family in the profile, to compare profiles and to estimate the biological significance of such comparisons, remains an active area of research.     

Long-term trends in evolution of indels in protein sequences

Background  

In this paper we describe an analysis of the size evolution of both protein domains and their indels, as inferred by changing sizes of whole domains or individual unaligned regions or "spacers". We studied relatively early evolutionary events and focused on protein domains which are conserved among various taxonomy groups.     

Support Vector Machines for predicting protein structural class

Background  

We apply a new machine learning method, the so-called Support Vector Machine method, to predict the protein structural class. Support Vector Machine method is performed based on the database derived from SCOP, in which protein domains are classified based on known structures and the evolutionary relationships and the principles that govern their 3-D structure.     

Identification of physicochemical selective pressure on protein encoding nucleotide sequences

Background  

Statistical methods for identifying positively selected sites in protein coding regions are one of the most commonly used tools in evolutionary bioinformatics. However, they have been limited by not taking the physiochemical properties of amino acids into account.     

Comparable contributions of structural-functional constraints and expression level to the rate of protein sequence evolution

Background  

Proteins show a broad range of evolutionary rates. Understanding the factors that are responsible for the characteristic rate of evolution of a given protein arguably is one of the major goals of evolutionary biology. A long-standing general assumption used to be that the evolution rate is, primarily, determined by the specific functional constraints that affect the given protein. These constrains were traditionally thought to depend both on the specific features of the protein's structure and its biological role. The advent of systems biology brought about new types of data, such as expression level and protein-protein interactions, and unexpectedly, a variety of correlations between protein evolution rate and these variables have been observed. The strongest connections by far were repeatedly seen between protein sequence evolution rate and the expression level of the respective gene. It has been hypothesized that this link is due to the selection for the robustness of the protein structure to mistranslation-induced misfolding that is particularly important for highly expressed proteins and is the dominant determinant of the sequence evolution rate.     

Exploring protein structural dissimilarity to facilitate structure classification

Background  

Classification of newly resolved protein structures is important in understanding their architectural, evolutionary and functional relatedness to known protein structures. Among various efforts to improve the database of Structural Classification of Proteins (SCOP), automation has received particular attention. Herein, we predict the deepest SCOP structural level that an unclassified protein shares with classified proteins with an equal number of secondary structure elements (SSEs).     

The relationship of protein conservation and sequence length

Background  

In general, the length of a protein sequence is determined by its function and the wide variance in the lengths of an organism's proteins reflects the diversity of specific functional roles for these proteins. However, additional evolutionary forces that affect the length of a protein may be revealed by studying the length distributions of proteins evolving under weaker functional constraints.     

Structure and evolution of protein interaction networks: a statistical model for link dynamics and gene duplications

Background  

The structure of molecular networks derives from dynamical processes on evolutionary time scales. For protein interaction networks, global statistical features of their structure can now be inferred consistently from several large-throughput datasets. Understanding the underlying evolutionary dynamics is crucial for discerning random parts of the network from biologically important properties shaped by natural selection.     

No simple dependence between protein evolution rate and the number of protein-protein interactions: only the most prolific interactors tend to evolve slowly

Background  

It has been suggested that rates of protein evolution are influenced, to a great extent, by the proportion of amino acid residues that are directly involved in protein function. In agreement with this hypothesis, recent work has shown a negative correlation between evolutionary rates and the number of protein-protein interactions. However, the extent to which the number of protein-protein interactions influences evolutionary rates remains unclear. Here, we address this question at several different levels of evolutionary relatedness.     

Protein protein interactions, evolutionary rate, abundance and age

Background

Does a relationship exist between a protein's evolutionary rate and its number of interactions? This relationship has been put forward many times, based on a biological premise that a highly interacting protein will be more restricted in its sequence changes. However, to date several studies have voiced conflicting views on the presence or absence of such a relationship.

Results

Here we perform a large scale study over multiple data sets in order to demonstrate that the major reason for conflict between previous studies is the use of different but overlapping datasets. We show that lack of correlation, between evolutionary rate and number of interactions in a data set is related to the error rate. We also demonstrate that the correlation is not an artifact of the underlying distributions of evolutionary distance and interactions and is therefore likely to be biologically relevant. Further to this, we consider the claim that the dependence is due to gene expression levels and find some supporting evidence. A strong and positive correlation between the number of interactions and the age of a protein is also observed and we show this relationship is independent of expression levels.

Conclusion

A correlation between number of interactions and evolutionary rate is observed but is dependent on the accuracy of the dataset being used. However it appears that the number of interactions a protein participates in depends more on the age of the protein than the rate at which it changes.     

Expression breadth and expression abundance behave differently in correlations with evolutionary rates

Background  

One of the main objectives of the molecular evolution and evolutionary systems biology field is to reveal the underlying principles that dictate protein evolutionary rates. Several studies argue that expression abundance is the most critical component in determining the rate of evolution, especially in unicellular organisms. However, the expression breadth also needs to be considered for multicellular organisms.     

PASS2: an automated database of protein alignments organised as structural superfamilies

Background  

The functional selection and three-dimensional structural constraints of proteins in nature often relates to the retention of significant sequence similarity between proteins of similar fold and function despite poor sequence identity. Organization of structure-based sequence alignments for distantly related proteins, provides a map of the conserved and critical regions of the protein universe that is useful for the analysis of folding principles, for the evolutionary unification of protein families and for maximizing the information return from experimental structure determination. The Protein Alignment organised as Structural Superfamily (PASS2) database represents continuously updated, structural alignments for evolutionary related, sequentially distant proteins.     

Tic62: a protein family from metabolism to protein translocation

Background  

The function and structure of protein translocons at the outer and inner envelope membrane of chloroplasts (Toc and Tic complexes, respectively) are a subject of intensive research. One of the proteins that have been ascribed to the Tic complex is Tic62. This protein was proposed as a redox sensor protein and may possibly act as a regulator during the translocation process. Tic62 is a bimodular protein that comprises an N-terminal module, responsible for binding to pyridine nucleotides, and a C-terminal module which serves as a docking site for ferredoxin-NAD(P)-oxido-reductase (FNR). This work focuses on evolutionary analysis of the Tic62-NAD(P)-related protein family, derived from the comparison of all available sequences, and discusses the structure of Tic62.     

A genome-wide survey of changes in protein evolutionary rates across four closely related species of <Emphasis Type="Italic">Saccharomyces</Emphasis> sensu stricto group

Background  

Changes in protein evolutionary rates among lineages have been frequently observed during periods of notable phenotypic evolution. It is also known that, following gene duplication and loss, the protein evolutionary rates of genes involved in such events changed because of changes in functional constraints acting on the genes. However, in the evolution of closely related species, excluding the aforementioned situations, the frequency of changes in protein evolutionary rates is still not clear at the genome-wide level. Here we examine the constancy of protein evolutionary rates in the evolution of four closely related species of the Saccharomyces sensu stricto group (S. cerevisiae, S. paradoxus, S. mikatae and S. bayanus).