Comparative analysis of sequence covariation methods to mine evolutionary hubs: Examples from selected GPCR families

Covariation between positions in a multiple sequence alignment may reflect structural, functional, and/or phylogenetic constraints and can be analyzed by a wide variety of methods. We explored several of these methods for their ability to identify covarying positions related to the divergence of a protein family at different hierarchical levels. Specifically, we compared seven methods on a model system composed of three nested sets of G‐protein‐coupled receptors (GPCRs) in which a divergence event occurred. The covariation methods analyzed were based on: χ² test, mutual information, substitution matrices, and perturbation methods. We first analyzed the dependence of the covariation scores on residue conservation (measured by sequence entropy), and then we analyzed the networking structure of the top pairs. Two methods out of seven—OMES (Observed minus Expected Squared) and ELSC (Explicit Likelihood of Subset Covariation)—favored pairs with intermediate entropy and a networking structure with a central residue involved in several high‐scoring pairs. This networking structure was observed for the three sequence sets. In each case, the central residue corresponded to a residue known to be crucial for the evolution of the GPCR family and the subfamily specificity. These central residues can be viewed as evolutionary hubs, in relation with an epistasis‐based mechanism of functional divergence within a protein family. Proteins 2014; 82:2141–2156. © 2014 Wiley Periodicals, Inc.     

Kinesin superfamily protein 3 (KIF3) motor transports fodrin-associating vesicles important for neurite building

Kinesin superfamily proteins (KIFs) comprise several dozen molecular motor proteins. The KIF3 heterotrimer complex is one of the most abundantly and ubiquitously expressed KIFs in mammalian cells. To unveil the functions of KIF3, microinjection of function-blocking monovalent antibodies against KIF3 into cultured superior cervical ganglion (SCG) neurons was carried out. They significantly blocked fast axonal transport and brought about inhibition of neurite extension. A yeast two-hybrid binding assay revealed the association of fodrin with the KIF3 motor through KAP3. This was further confirmed by using vesicles collected from large bundles of axons (cauda equina), from which membranous vesicles could be prepared in pure preparations. Both immunoprecipitation and immunoelectron microscopy indicated the colocalization of fodrin and KIF3 on the same vesicles, the results reinforcing the evidence that the cargo of the KIF3 motor consists of fodrin-associating vesicles. In addition, pulse-labeling study implied partial comigration of both molecules as fast flow components. Taken together, the KIF3 motor is engaged in fast axonal transport that conveys membranous components important for neurite extension.     

Combining protein sequence,structure, and dynamics: A novel approach for functional evolution analysis of PAS domain superfamily

PAS domains are widespread in archaea, bacteria, and eukaryota, and play important roles in various functions. In this study, we aim to explore functional evolutionary relationship among proteins in the PAS domain superfamily in view of the sequence‐structure‐dynamics‐function relationship. We collected protein sequences and crystal structure data from RCSB Protein Data Bank of the PAS domain superfamily belonging to three biological functions (nucleotide binding, photoreceptor activity, and transferase activity). Protein sequences were aligned and then used to select sequence‐conserved residues and build phylogenetic tree. Three‐dimensional structure alignment was also applied to obtain structure‐conserved residues. The protein dynamics were analyzed using elastic network model (ENM) and validated by molecular dynamics (MD) simulation. The result showed that the proteins with same function could be grouped by sequence similarity, and proteins in different functional groups displayed statistically significant difference in their vibrational patterns. Interestingly, in all three functional groups, conserved amino acid residues identified by sequence and structure conservation analysis generally have a lower fluctuation than other residues. In addition, the fluctuation of conserved residues in each biological function group was strongly correlated with the corresponding biological function. This research suggested a direct connection in which the protein sequences were related to various functions through structural dynamics. This is a new attempt to delineate functional evolution of proteins using the integrated information of sequence, structure, and dynamics.     

Optimal data collection for correlated mutation analysis

The main objective of correlated mutation analysis (CMA) is to predict intraprotein residue-residue interactions from sequence alone. Despite considerable progress in algorithms and computer capabilities, the performance of CMA methods remains quite low. Here we examine whether, and to what extent, the quality of CMA methods depends on the sequences that are included in the multiple sequence alignment (MSA). The results revealed a strong correlation between the number of homologs in an MSA and CMA prediction strength. Furthermore, many of the current methods include only orthologs in the MSA, we found that it is beneficial to include both orthologs and paralogs in the MSA. Remarkably, even remote homologs contribute to the improved accuracy. Based on our findings we put forward an automated data collection procedure, with a minimal coverage of 50% between the query protein and its orthologs and paralogs. This procedure improves accuracy even in the absence of manual curation. In this era of massive sequencing and exploding sequence data, our results suggest that correlated mutation-based methods have not reached their inherent performance limitations and that the role of CMA in structural biology is far from being fulfilled.     

Effective epitope identification employing phylogenetic,mutational variability,sequence entropy,and correlated mutation analysis targeting NS5B protein of hepatitis C virus: from bioinformatics to therapeutics

Hepatitis C virus (HCV) is considered as a foremost cause affecting numerous human liver‐related disorders. An effective immuno‐prophylactic measure (like stable vaccine) is still unavailable for HCV. We perform an in silico analysis of nonstructural protein 5B (NS5B) based CD4 and CD8 epitopes that might be implicated in improvement of treatment strategies for efficient vaccine development programs against HCV. Here, we report on effective utilization of knowledge obtained from multiple sequence alignment and phylogenetic analysis for investigation and evaluation of candidate epitopes that have enormous potential to be used in formulating proficient vaccine, embracing multiple strains prevalent among major geographical locations. Mutational variability data discussed herein focus on discriminating the region under active evolutionary pressure from those having lower mutational potential in existing experimentally verified epitopes, thus, providing a concrete framework for designing an effective peptide‐based vaccine against HCV. Additionally, we measured entropy distribution in NS5B residues and pinpoint the positions in epitopes that are more susceptible to mutations and, thus, account for virus strategy to evade the host immune system. Findings from this study are expected to add more details on the sequence and structural aspects of NS5B protein, ultimately facilitating our understanding about the pathophysiology of HCV and assisting advance studies on the function of NS5B antigen on the epitope level. We also report on the mutational crosstalk between functionally important coevolving residues, using correlated mutation analysis, and identify networks of coupled mutations that represent pathways of allosteric communication inside and among NS5B thumb, finger, and palm domains. Copyright © 2015 John Wiley & Sons, Ltd.     

Experimental analysis of co‐evolution within protein complexes: The yeast exosome as a model

Extensive bioinformatics analysis suggests that the stability and function of protein complexes are maintained throughout evolution by coordinated changes (co‐evolution) of complex subunits. Yet, relatively little is known regarding the actual dynamics of such processes and the functional implications of co‐evolution within protein complexes, since most of the bioinformatics predictions were not analyzed experimentally. Here, we describe a systematic experimental approach that allows a step‐by‐step observation of the co‐evolution process in protein complexes. The exosome complex, an essential complex exhibiting a 3′→5′ RNA degradation activity, served as a model system. In this study, we show that exosome subunits diverged very early during fungal evolution. Interestingly, we found that despite significant differences in conservation between Rrp41 and Mtr3 both subunits exhibit similar divergence pattern and co‐evolutionary behavior through fungi evolution. Activity analysis of mutated exosomes exposes another layer of co‐evolution between the core subunits and RNA substrates. Overall, our approach allows the experimental analysis of co‐evolution within protein complexes and together with bioinformatics analysis can significantly deepen our understanding of the evolution of these complexes. Proteins 2013; 81:1997–2006. © 2013 Wiley Periodicals, Inc.     

ProtaBank: A repository for protein design and engineering data

We present ProtaBank, a repository for storing, querying, analyzing, and sharing protein design and engineering data in an actively maintained and updated database. ProtaBank provides a format to describe and compare all types of protein mutational data, spanning a wide range of properties and techniques. It features a user‐friendly web interface and programming layer that streamlines data deposition and allows for batch input and queries. The database schema design incorporates a standard format for reporting protein sequences and experimental data that facilitates comparison of results across different data sets. A suite of analysis and visualization tools are provided to facilitate discovery, to guide future designs, and to benchmark and train new predictive tools and algorithms. ProtaBank will provide a valuable resource to the protein engineering community by storing and safeguarding newly generated data, allowing for fast searching and identification of relevant data from the existing literature, and exploring correlations between disparate data sets. ProtaBank invites researchers to contribute data to the database to make it accessible for search and analysis. ProtaBank is available at https://protabank.org .     

Sequence variations within protein families are linearly related to structural variations

It is commonly believed that similarities between the sequences of two proteins infer similarities between their structures. Sequence alignments reliably recognize pairs of protein of similar structures provided that the percentage sequence identity between their two sequences is sufficiently high. This distinction, however, is statistically less reliable when the percentage sequence identity is lower than 30% and little is known then about the detailed relationship between the two measures of similarity. Here, we investigate the inverse correlation between structural similarity and sequence similarity on 12 protein structure families. We define the structure similarity between two proteins as the cRMS distance between their structures. The sequence similarity for a pair of proteins is measured as the mean distance between the sequences in the subsets of sequence space compatible with their structures. We obtain an approximation of the sequence space compatible with a protein by designing a collection of protein sequences both stable and specific to the structure of that protein. Using these measures of sequence and structure similarities, we find that structural changes within a protein family are linearly related to changes in sequence similarity.     

Myosin binding protein C： Structural abnormalities in familial hypertrophic cardiomyopathy

The muscle protein myosin binding protein C (MyBPC) is a large multi-domain protein whose role in the sarcomere is complex and not yet fully understood. Mutations in MyBPC are strongly associated with the heart disease familial hypertrophic cardiomyopathy (FHC) and these experiments of nature have provided some insight into the intricate workings of this protein in the heart. While some regions of the MyBPC molecule have been assigned a function in the regulation of muscle contraction, the interaction of other regions with various parts of the myosin molecule and the sarcomeric proteins, actin and titin, remain obscure. In addition, several intra-domain interactions between adjacent MyBPC molecules have been identified. Although the basic structure of the molecule (a series of immunoglobulin and fibronectin domains) has been elucidated, the assembly of MyBPC in the sarcomere is a topic for debate. By analysing the MyBPC sequence with respect to FHC-causing mutations it is possible to identify individual residues or regions of each domain that may be important either for binding or regulation. This review looks at the current literature, in concert with alignments and the structural models of MyBPC, in an attempt to understand how FHC mutations may lead to the disease state.     

Definition of the tempo of sequence diversity across an alignment and automatic identification of sequence motifs: Application to protein homologous families and superfamilies

It is often possible to identify sequence motifs that characterize a protein family in terms of its fold and/or function from aligned protein sequences. Such motifs can be used to search for new family members. Partitioning of sequence alignments into regions of similar amino acid variability is usually done by hand. Here, I present a completely automatic method for this purpose: one that is guaranteed to produce globally optimal solutions at all levels of partition granularity. The method is used to compare the tempo of sequence diversity across reliable three-dimensional (3D) structure-based alignments of 209 protein families (HOMSTRAD) and that for 69 superfamilies (CAMPASS). (The mean alignment length for HOMSTRAD and CAMPASS are very similar.) Surprisingly, the optimal segmentation distributions for the closely related proteins and distantly related ones are found to be very similar. Also, optimal segmentation identifies an unusual protein superfamily. Finally, protein 3D structure clues from the tempo of sequence diversity across alignments are examined. The method is general, and could be applied to any area of comparative biological sequence and 3D structure analysis where the constraint of the inherent linear organization of the data imposes an ordering on the set of objects to be clustered.     

Computational Modeling of Protein Stability: Quantitative Analysis Reveals Solutions to Pervasive Problems

1. Download : Download high-res image (151KB)
2. Download : Download full-size image

     

Mining of assembled expressed sequence tag (EST) data for protein families: application to the G protein-coupled receptor superfamily

The availability of large expressed sequence tag (EST) databases has led to a revolution in the way new genes are identified. Mining of these databases using known protein sequences as queries is a powerful technique for discovering orthologous and paralogous genes. The scientist is often confronted, however, by an enormous amount of search output owing to the inherent redundancy of EST data. In addition, high search sensitivity often cannot be achieved using only a single member of a protein superfamily as a query. In this paper a technique for addressing both of these issues is described. Assembled EST databases are queried with every member of a protein superfamily, the results are integrated and false positives are pruned from the set. The result is a set of assemblies enriched in members of the protein superfamily under consideration. The technique is applied to the G protein-coupled receptor (GPCR) superfamily in the construction of a GPCR Resource. A novel full-length human GPCR identified from the GPCR Resource is presented, illustrating the utility of the method.     

The triterpene cyclase protein family: a systematic analysis

Triterpene cyclases catalyze a broad range of cyclization reactions to form polycyclic triterpenes. Triterpene cyclases that convert squalene to hopene are named squalene-hopene cyclases (SHC) and triterpene cyclases that convert oxidosqualene are named oxidosqualene cyclases (OSC). Many sequences have been published, but there is only one structure available for each of SHCs and OSCs. Although they catalyze a similar reaction, the sequence similarity between SHCs and OSCs is low. A family classification based on phylogenetic analysis revealed 20 homologous families which are grouped into two superfamilies, SHCs and OSCs. Based on this family assignment, the Triterpene Cyclase Engineering Database (TTCED) was established. It integrates available information on sequence and structure of 639 triterpene cyclases as well as on structurally and functionally relevant amino acids. Family specific multiple sequence alignments were generated to identify the functionally relevant residues. Based on sequence alignments, conserved residues in SHCs and OSCs were analyzed and compared to experimentally confirmed mutational data. Functional schematic models of the central cavities of OSCs and SHCs were derived from structure comparison and sequence conservation analysis. These models demonstrate the high similarity of the substrate binding cavity of SHCs and OSCs and the equivalences of the respective residues. The TTCED is a novel source for comprehensive information on the triterpene cyclase family, including a compilation of previously described mutational data. The schematic models present the conservation analysis in a readily available fashion and facilitate the correlation of residues to a specific function or substrate interaction.     

Structural model for family 32 of glycosyl-hydrolase enzymes

A structural model is presented for family 32 of the glycosyl-hydrolase enzymes based on the beta-propeller fold. The model is derived from the common prediction of two different threading methods, TOPITS and THREADER. In addition, we used a correlated mutation analysis and prediction of active-site residues to corroborate the proposed model. Physical techniques (circular dichroism and differential scanning calorimetry) confirmed two aspects of the prediction, the proposed all-beta fold and the multi-domain structure. The most reliable three-dimensional model was obtained using the structure of neuraminidase (1nscA) as template. The analysis of the position of the active site residues in this model is compatible with the catalytic mechanism proposed by Reddy and Maley (J. Biol. Chem. 271:13953–13958, 1996), which includes three conserved residues, Asp, Glu, and Cys. Based on this analysis, we propose the participation of one more conserved residue (Asp 162) in the catalytic mechanism. The model will facilitate further studies of the physical and biochemical characteristics of family 32 of the glycosyl-hydrolases. Proteins 33:383–395, 1998. © 1998 Wiley-Liss, Inc.     

In silico two-hybrid system for the selection of physically interacting protein pairs

Deciphering the interaction links between proteins has become one of the main tasks of experimental and bioinformatic methodologies. Reconstruction of complex networks of interactions in simple cellular systems by integrating predicted interaction networks with available experimental data is becoming one of the most demanding needs in the postgenomic era. On the basis of the study of correlated mutations in multiple sequence alignments, we propose a new method (in silico two-hybrid, i2h) that directly addresses the detection of physically interacting protein pairs and identifies the most likely sequence regions involved in the interactions. We have applied the system to several test sets, showing that it can discriminate between true and false interactions in a significant number of cases. We have also analyzed a large collection of E. coli protein pairs as a first step toward the virtual reconstruction of its complete interaction network.     

How aberrant N-glycosylation can alter protein functionality and ligand binding: An atomistic view

1. Download : Download high-res image (227KB)
2. Download : Download full-size image

     

Phylogenetic spread of sequence data affects fitness of consensus enzymes: Insights from triosephosphate isomerase

The concept of consensus in multiple sequence alignments (MSAs) has been used to design and engineer proteins previously with some success. However, consensus design implicitly assumes that all amino acid positions function independently, whereas in reality, the amino acids in a protein interact with each other and work cooperatively to produce the optimum structure required for its function. Correlation analysis is a tool that can capture the effect of such interactions. In a previously published study, we made consensus variants of the triosephosphate isomerase (TIM) protein using MSAs that included sequences form both prokaryotic and eukaryotic organisms. These variants were not completely native-like and were also surprisingly different from each other in terms of oligomeric state, structural dynamics, and activity. Extensive correlation analysis of the TIM database has revealed some clues about factors leading to the unusual behavior of the previously constructed consensus proteins. Among other things, we have found that the more ill-behaved consensus mutant had more broken correlations than the better-behaved consensus variant. Moreover, we report three correlation and phylogeny-based consensus variants of TIM. These variants were more native-like than the previous consensus mutants and considerably more stable than a wild-type TIM from a mesophilic organism. This study highlights the importance of choosing the appropriate diversity of MSA for consensus analysis and provides information that can be used to engineer stable enzymes.     

IWS: integrated web server for protein sequence and structure analysis

Rapid increase in protein sequence information from genome sequencing projects demand the intervention of bioinformatics tools to recognize interesting gene-products and associated function. Often, multiple algorithms need to be employed to improve accuracy in predictions and several structure prediction algorithms are on the public domain. Here, we report the availability of an Integrated Web-server as a bioinformatics online package dedicated for in-silico analysis of protein sequence and structure data (IWS). IWS provides web interface to both in-house and widely accepted programs from major bioinformatics groups, organized as 10 different modules. IWS also provides interactive images for Analysis Work Flow, which will provide transparency to the user to carry out analysis by moving across modules seamlessly and to perform their predictions in a rapid manner. AVAILABILITY: IWS IS AVAILABLE FROM THE URL: http://caps.ncbs.res.in/iws.     

Burkholderia genome analysis reveals new enzymes belonging to the nitrilase superfamily. The amidase of Burkholderia cepacia (hospital isolate)

Burkholderia cepacia (formerly Pseudomonas cepacia) grows in media containing acetamide or propionamide as C and N sources. Chromosomal DNA from a hospital isolate of B. cepacia served as a template in PCRs using primers designed for the amplification of the P. aeruginosa amiE gene that encodes an aliphatic amidase. Partial sequencing of the PCR products gave a translated sequence 100% identical with the amino acid sequence of P. aeruginosa amidase. A search of Burkholderia genomes detected a putative amidase in B. cepacia J2315 with high identity to the P. aeruginosa amidase and predicted that other Burkholderia species also possessed CN_hydrolases that use the same catalytic triad (Glu–Lys–Cys) as amidase. Superimposition of theoretical three-dimensional models suggested that differences in the amino acid sequences between amidases from B. cepacia (hospital isolate) and B. cepacia J2315 do not affect their three-dimensional structure.     

Molecular diversity and evolution of the large lipid transfer protein superfamily

Circulatory lipid transport in animals is mediated to a substantial extent by members of the large lipid transfer (LLT) protein (LLTP) superfamily. These proteins, including apolipoprotein B (apoB), bind lipids and constitute the structural basis for the assembly of lipoproteins. The current analyses of sequence data indicate that LLTPs are unique to animals and that these lipid binding proteins evolved in the earliest multicellular animals. In addition, two novel LLTPs were recognized in insects. Structural and phylogenetic analyses reveal three major families of LLTPs: the apoB-like LLTPs, the vitellogenin-like LLTPs, and the microsomal triglyceride transfer protein (MTP)-like LLTPs, or MTPs. The latter are ubiquitous, whereas the two other families are distributed differentially between animal groups. Besides similarities, remarkable variations are also found among LLTPs in their major lipid-binding sites (i.e., the LLT module as well as the predicted clusters of amphipathic secondary structure): variations such as protein modification and number, size, or occurrence of the clusters. Strikingly, comparative research has also highlighted a multitude of functions for LLTPs in addition to circulatory lipid transport. The integration of LLTP structure, function, and evolution reveals multiple adaptations, which have come about in part upon neofunctionalization of duplicated genes. Moreover, the change, exchange, and expansion of functions illustrate the opportune application of lipid-binding proteins in nature. Accordingly, comparative research exposes the structural and functional adaptations in animal lipid carriers and brings up novel possibilities for the manipulation of lipid transport.