真核翻译延伸因子1A蛋白家族功能位点的进化踪迹分析

真核翻译延伸因子1A（eEF1A）是真核生物蛋白质翻译过程中能将氨酰tRNA运送到核糖体A位点参与多肽延伸反应的多功能蛋白质. 本文主要利用多种生物信息学分析工具进行地中海涡虫翻译延伸因子1A（SmEF1A）蛋白序列的查找与eEF1A直系同源蛋白的搜索, 并基于90条直系同源蛋白进行eEF1A蛋白家族的进化踪迹分析和SmEF1A蛋白功能位点的比较研究. 结果表明,在eEF1A蛋白家族中共识别到338个踪迹残基位点和20个踪迹残基富集区域,SmEF1A蛋白的功能位点与踪迹残基位点密切相关,与GTP/Mg2+结合相关的S21、T72、D91、G94等重要位点均为全家族保守的踪迹残基,N 糖基化、磷酸化等蛋白修饰位点中踪迹残基位点往往是被修饰的部位或修饰功能发挥的关键辅助位点,而位于分子表面的配基结合口袋则与20个踪迹残基富集区域在分子表面形成的踪迹残基簇关系密切. eEF1A蛋白家族的进化踪迹分析为eEF1A蛋白重要功能区域关键残基的确定和未知功能位点的预测提供了重要信息.     

Integration of Evolutionary Features for the Identification of Functionally Important Residues in Major Facilitator Superfamily Transporters

The identification of functionally important residues is an important challenge for understanding the molecular mechanisms of proteins. Membrane protein transporters operate two-state allosteric conformational changes using functionally important cooperative residues that mediate long-range communication from the substrate binding site to the translocation pathway. In this study, we identified functionally important cooperative residues of membrane protein transporters by integrating sequence conservation and co-evolutionary information. A newly derived evolutionary feature, the co-evolutionary coupling number, was introduced to measure the connectivity of co-evolving residue pairs and was integrated with the sequence conservation score. We tested this method on three Major Facilitator Superfamily (MFS) transporters, LacY, GlpT, and EmrD. MFS transporters are an important family of membrane protein transporters, which utilize diverse substrates, catalyze different modes of transport using unique combinations of functional residues, and have enough characterized functional residues to validate the performance of our method. We found that the conserved cores of evolutionarily coupled residues are involved in specific substrate recognition and translocation of MFS transporters. Furthermore, a subset of the residues forms an interaction network connecting functional sites in the protein structure. We also confirmed that our method is effective on other membrane protein transporters. Our results provide insight into the location of functional residues important for the molecular mechanisms of membrane protein transporters.     

Functional divergence after gene duplication and sequence-structure relationship: a case study of G-protein alpha subunits

In this article, we use animal G-protein alpha subunit family as an example to illustrate a comprehensive analytical pipeline for detecting different types of functional divergence of protein families, which is phylogeny-dependent, combined with ancestral sequence inference and available protein structure information. In particular, we focus on (i) Type-I functional divergence, or site-specific rate shift, as typically exemplified by amino acid residue highly conserved in a subset of homologous genes but highly variable in a different subset of homologous genes, and (ii) Type-II functional divergence, or the shift of cluster-specific amino acid property, as exemplified by a radical shift of amino acid property between duplicate genes, which is otherwise evolutionally conserved. We utilized the software DIVERGE2 to carry out these analyses. In the case of G-protein alpha subunit gene family, we have predicted amino acid residues that are related to either Type-I or Type-II functional divergence. The inferred ancestral sequences for these sites are helpful to explore the trends of functional divergence. Finally, these predicted residues are mapped to the protein structures to test whether these residues may have 3D structure or solvent accessibility preference.     

TheInt family of site-specific recombinases: Some thoughts on a general reaction mechanism

The FLP recombinase of the yeast 2 micron circle plasmid belongs to theInt family of recombinases. Only three amino acid residues are invariant among members of this family. Functional analyses of FLP protein variants mutated at these three residues suggest their involvement at specific steps of the recombination pathway. We propose that these residues play the same functional role in the mechanism of action of all theInt family recombinases.     

Predicting ligand binding residues and functional sites using multipositional correlations with graph theoretic clustering and kernel CCA

We present a new computational method for predicting ligand binding residues and functional sites in protein sequences. These residues and sites tend to be not only conserved, but also exhibit strong correlation due to the selection pressure during evolution in order to maintain the required structure and/or function. To explore the effect of correlations among multiple positions in the sequences, the method uses graph theoretic clustering and kernel-based canonical correlation analysis (kCCA) to identify binding and functional sites in protein sequences as the residues that exhibit strong correlation between the residues’ evolutionary characterization at the sites and the structure-based functional classification of the proteins in the context of a functional family. The results of testing the method on two well-curated data sets show that the prediction accuracy as measured by Receiver Operating Characteristic (ROC) scores improves significantly when multipositional correlations are accounted for.     

Automatic methods for predicting functionally important residues

Sequence analysis is often the first guide for the prediction of residues in a protein family that may have functional significance. A few methods have been proposed which use the division of protein families into subfamilies in the search for those positions that could have some functional significance for the whole family, but at the same time which exhibit the specificity of each subfamily ("Tree-determinant residues"). However, there are still many unsolved questions like the best division of a protein family into subfamilies, or the accurate detection of sequence variation patterns characteristic of different subfamilies. Here we present a systematic study in a significant number of protein families, testing the statistical meaning of the Tree-determinant residues predicted by three different methods that represent the range of available approaches. The first method takes as a starting point a phylogenetic representation of a protein family and, following the principle of Relative Entropy from Information Theory, automatically searches for the optimal division of the family into subfamilies. The second method looks for positions whose mutational behavior is reminiscent of the mutational behavior of the full-length proteins, by directly comparing the corresponding distance matrices. The third method is an automation of the analysis of distribution of sequences and amino acid positions in the corresponding multidimensional spaces using a vector-based principal component analysis. These three methods have been tested on two non-redundant lists of protein families: one composed by proteins that bind a variety of ligand groups, and the other composed by proteins with annotated functionally relevant sites. In most cases, the residues predicted by the three methods show a clear tendency to be close to bound ligands of biological relevance and to those amino acids described as participants in key aspects of protein function. These three automatic methods provide a wide range of possibilities for biologists to analyze their families of interest, in a similar way to the one presented here for the family of proteins related with ras-p21.     

Evolutionarily conserved networks of residues mediate allosteric communication in proteins

A fundamental goal in cellular signaling is to understand allosteric communication, the process by which signals originating at one site in a protein propagate reliably to affect distant functional sites. The general principles of protein structure that underlie this process remain unknown. Here, we describe a sequence-based statistical method for quantitatively mapping the global network of amino acid interactions in a protein. Application of this method for three structurally and functionally distinct protein families (G protein-coupled receptors, the chymotrypsin class of serine proteases and hemoglobins) reveals a surprisingly simple architecture for amino acid interactions in each protein family: a small subset of residues forms physically connected networks that link distant functional sites in the tertiary structure. Although small in number, residues comprising the network show excellent correlation with the large body of mechanistic data available for each family. The data suggest that evolutionarily conserved sparse networks of amino acid interactions represent structural motifs for allosteric communication in proteins.     

Polar residues in a conserved motif spanning helices 1 and 2 are functionally important in the SulP transporter family

The SulP family (including the SLC26 family) is a diverse family of anion transporters found in all domains of life, with different members transporting different anions. We used sequence and bioinformatics analysis of helices 1 and 2 of SulP family members to identify a conserved motif, extending the previously defined 'sulfate transporter motif'. The analysis showed that in addition to being highly conserved in both sequence and spacing, helices 1 and 2 contain a significant number of polar residues and are predicted to be buried within the protein interior, with at least some faces packed closely against other helices. This suggests a significant functional role for this region and we tested this by mutating polar residues in helices 1 and 2 in the sulfate transporter, SHST1. All mutations made, even those removing only a single hydroxyl group, had significant effects on transport. Many mutations abolished transport without affecting plasma membrane expression of the mutant protein, suggesting a functional role for these residues. Different helical faces appear to have different roles, with the most severe effects being localised to two interacting faces of helices 1 and 2. Our results confirm the predicted importance of conserved polar residues in helices 1 and 2 and suggest that transport of sulfate by SHST1 is dependent on a network of polar and aromatic interactions between these two helices.     

A Combinatorial Approach to Detect Coevolved Amino Acid Networks in Protein Families of Variable Divergence

Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence.     

Identification of a glycine motif required for packing in EmrE, a multidrug transporter from Escherichia coli

Glycine residues may play functional and structural roles in membrane proteins. In this work we studied the role of glycine residues in EmrE, a small multidrug transporter from Escherichia coli. EmrE extrudes various drugs across the plasma membrane in exchange with protons and, as a result, confers resistance against their toxic effects. Each of 12 glycine residues was replaced by site-directed mutagenesis. Four of the 12 glycine residues in EmrE are evolutionary conserved within the small multidrug resistance family of multidrug transporters. Our analysis reveals that only two (Gly-67 and Gly-97) of these four highly conserved residues are essential for transporter activity. Moreover, two glycine positions that are less conserved, Gly-17 and Gly-90, demonstrate also a nil phenotype when substituted. Our present results identifying Gly-17 and Gly-67 as irreplaceable reinforce the importance of previously defined functional clusters. Two essential glycine residues, Gly-90 and Gly-97, form a protein motif in which glycine residues are separated by six other residues (GG7). Upon substitution of glycine in these positions, the protein ability to form dimers is impaired as evaluated by cross-linking and pull-down experiments.     

Chasing long-range evolutionary couplings in the AlphaFold era

Coevolution between protein residues is normally interpreted as direct contact. However, the evolutionary record of a protein sequence contains rich information that may include long-range functional couplings, couplings that report on homo-oligomeric states or even conformational changes. Due to the complexity of the sequence space and the lack of structural information on various members of a protein family, it has been difficult to effectively mine the additional information encoded in a multiple sequence alignment (MSA). Here, taking advantage of the recent release of the AlphaFold (AF) database we attempt to identify coevolutionary couplings that cannot be explained simply by spatial proximity. We propose a simple computational method that performs direct coupling analysis on a MSA and searches for couplings that are not satisfied in any of the AF models of members of the identified protein family. Application of this method on 2012 protein families suggests that ~12% of the total identified coevolving residue pairs are spatially distant and more likely to be disordered than their contacting counterparts. We expect that this analysis will help improve the quality of coevolutionary distance restraints used for structure determination and will be useful in identifying potentially functional/allosteric cross-talk between distant residues.     

Identification of functional subclasses in the DJ-1 superfamily proteins

Genomics has posed the challenge of determination of protein function from sequence and/or 3-D structure. Functional assignment from sequence relationships can be misleading, and structural similarity does not necessarily imply functional similarity. Proteins in the DJ-1 family, many of which are of unknown function, are examples of proteins with both sequence and fold similarity that span multiple functional classes. THEMATICS (theoretical microscopic titration curves), an electrostatics-based computational approach to functional site prediction, is used to sort proteins in the DJ-1 family into different functional classes. Active site residues are predicted for the eight distinct DJ-1 proteins with available 3-D structures. Placement of the predicted residues onto a structural alignment for six of these proteins reveals three distinct types of active sites. Each type overlaps only partially with the others, with only one residue in common across all six sets of predicted residues. Human DJ-1 and YajL from Escherichia coli have very similar predicted active sites and belong to the same probable functional group. Protease I, a known cysteine protease from Pyrococcus horikoshii, and PfpI/YhbO from E. coli, a hypothetical protein of unknown function, belong to a separate class. THEMATICS predicts a set of residues that is typical of a cysteine protease for Protease I; the prediction for PfpI/YhbO bears some similarity. YDR533Cp from Saccharomyces cerevisiae, of unknown function, and the known chaperone Hsp31 from E. coli constitute a third group with nearly identical predicted active sites. While the first four proteins have predicted active sites at dimer interfaces, YDR533Cp and Hsp31 both have predicted sites contained within each subunit. Although YDR533Cp and Hsp31 form different dimers with different orientations between the subunits, the predicted active sites are superimposable within the monomer structures. Thus, the three predicted functional classes form four different types of quaternary structures. The computational prediction of the functional sites for protein structures of unknown function provides valuable clues for functional classification.     

Prediction and confirmation of a site critical for effector regulation of RGS domain activity

A critical challenge of structural genomics is to extract functional information from protein structures. We present an example of how this may be accomplished using the Evolutionary Trace (ET) method in the context of the regulators of G protein signaling (RGS) family. We have previously applied ET to the RGS family and identified a novel, evolutionarily privileged site on the RGS domain as important for regulating RGS activity. Here we confirm through targeted mutagenesis of RGS7 that these ET-identified residues are critical for RGS domain regulation and are likely to function as global determinants of RGS function. We also discuss how the recent structure of the complex of RGS9, Gt/i1alpha-GDP-AlF4- and the effector subunit PDEgamma confirms their contact with the effector-G protein interface, forming a structural pathway that communicates from the effector-contacting surface of the G protein and RGS catalytic core domain to the catalytic interface between Galpha and RGS. These results demonstrate the effectiveness of ET for identifying binding sites and efficiently focusing mutational studies on their key residues, thereby linking raw sequence and structure data to functional information.     

Functional divergence and catalytic properties of dehydroascorbate reductase family proteins from Populus tomentosa

Dehydroascorbate reductase (DHAR) is a key enzyme in the ascorbate–glutathione cycle that maintains reduced pools of ascorbic acid and serves as an important antioxidant. In this study, to investigate functional divergence of plant DHAR family and catalytic characteristics of the glutathione binding site (G-site) residues of DHAR proteins, we cloned three DHAR genes (PtoDHAR1/2/3) from Populus tomentosa and predicted the G-site residues. PtoDHAR1 protein was localized in chloroplast, while PtoDHAR2/3 proteins showed cytosolic localizations. Three DHAR proteins showed different enzymatic activities, apparent kinetic characteristics, optimum T _m and pH profiles, indicating their functional divergence. Cys20, Lys8, Pro61, Asp72 and Ser73 of PtoDHAR2 were predicted as G-site residues based on their N-terminal amino acid sequence identity and the available crystal structures of glutathione S-transferases. The biochemical functions of these residues are examined in this study through site-directed mutagenesis. The aforementioned five residues are critical components of active sites that contribute to the enzyme’s catalytic activity. Cys20, Pro61 and Asp72 of PtoDHAR2 are also responsible for maintaining proper protein structure. This study provides new insights into the functional divergence of the plant DHAR family and biochemical properties of the G-site residues in plant DHAR proteins.     

Inferring functional relationships of proteins from local sequence and spatial surface patterns

We describe a novel approach for inferring functional relationship of proteins by detecting sequence and spatial patterns of protein surfaces. Well-formed concave surface regions in the form of pockets and voids are examined to identify similarity relationship that might be directly related to protein function. We first exhaustively identify and measure analytically all 910,379 surface pockets and interior voids on 12,177 protein structures from the Protein Data Bank. The similarity of patterns of residues forming pockets and voids are then assessed in sequence, in spatial arrangement, and in orientational arrangement. Statistical significance in the form of E and p-values is then estimated for each of the three types of similarity measurements. Our method is fully automated without human intervention and can be used without input of query patterns. It does not assume any prior knowledge of functional residues of a protein, and can detect similarity based on surface patterns small and large. It also tolerates, to some extent, conformational flexibility of functional sites. We show with examples that this method can detect functional relationship with specificity for members of the same protein family and superfamily, as well as remotely related functional surfaces from proteins of different fold structures. We envision that this method can be used for discovering novel functional relationship of protein surfaces, for functional annotation of protein structures with unknown biological roles, and for further inquiries on evolutionary origins of structural elements important for protein function.     

Structure-function analysis of the dolichyl phosphate-mannose: protein O-mannosyltransferase ScPmt1p

Protein O-mannosylation is an essential protein modification. It is initiated at the endoplasmic reticulum by a family of dolichyl phosphate-mannose:protein O-mannosyltransferases (Pmts), which is evolutionarily conserved from yeast to humans. Saccharomyces cerevisiae Pmt1p is an integral membrane protein of the endoplasmic reticulum. ScPmt1p forms a complex with ScPmt2p that is required for maximum transferase activity. Recently, we proposed a seven-transmembrane structural model for ScPmt1p. A large, hydrophilic, endoplasmic reticulum-oriented segment is flanked by five amino-terminal and two carboxyl-terminal membrane-spanning domains. Based on this model, a structure-function analysis of ScPmt1p was performed. Deletion mutagenesis identified the N-terminal third of the transferase as being essential for the formation of a functional ScPmt1p-ScPmt2p complex. Deletion of the central hydrophilic loop eliminates mannosyltransferase activity, but not ScPmt1p-ScPmt2p interactions. Alignment of all fully characterized PMT family members revealed that this central loop region contains three highly conserved peptide motifs, which can be considered as signatures of the PMT family. In addition, a number of invariant amino acid residues were identified throughout the entire protein sequence. In order to evaluate the functional significance of these conserved residues site-directed mutagenesis was performed. We show that several amino acid substitutions in the conserved motifs significantly reduce ScPmt1p activity. Further, the invariant residues Arg-64, Glu-78, Arg-138, and Leu-408 are essential for ScPmt1p function. In particular, Arg-138 is crucial for ScPmt1p-ScPmt2p complex formation.     

Correlation analysis for protein evolutionary family based on amino acid position mutations and application in PDZ domain

Background

It has been widely recognized that the mutations at specific directions are caused by the functional constraints in protein family and the directional mutations at certain positions control the evolutionary direction of the protein family. The mutations at different positions, even distantly separated, are mutually coupled and form an evolutionary network. Finding the controlling mutative positions and the mutative network among residues are firstly important for protein rational design and enzyme engineering.

Methodology

A computational approach, namely amino acid position conservation-mutation correlation analysis (CMCA), is developed to predict mutually mutative positions and find the evolutionary network in protein family. The amino acid position mutative function, which is the foundational equation of CMCA measuring the mutation of a residue at a position, is derived from the MSA (multiple structure alignment) database of protein evolutionary family. Then the position conservation correlation matrix and position mutation correlation matrix is constructed from the amino acid position mutative equation. Unlike traditional SCA (statistical coupling analysis) approach, which is based on the statistical analysis of position conservations, the CMCA focuses on the correlation analysis of position mutations.

Conclusions

As an example the CMCA approach is used to study the PDZ domain of protein family, and the results well illustrate the distantly allosteric mechanism in PDZ protein family, and find the functional mutative network among residues. We expect that the CMCA approach may find applications in protein engineering study, and suggest new strategy to improve bioactivities and physicochemical properties of enzymes.