Structural classification of thioredoxin-like fold proteins

Protein structure classification is necessary to comprehend the rapidly growing structural data for better understanding of protein evolution and sequence-structure-function relationships. Thioredoxins are important proteins that ubiquitously regulate cellular redox status and various other crucial functions. We define the thioredoxin-like fold using the structure consensus of thioredoxin homologs and consider all circular permutations of the fold. The search for thioredoxin-like fold proteins in the PDB database identified 723 protein domains. These domains are grouped into eleven evolutionary families based on combined sequence, structural, and functional evidence. Analysis of the protein-ligand structure complexes reveals two major active site locations for the thioredoxin-like proteins. Comparison to existing structure classifications reveals that our thioredoxin-like fold group is broader and more inclusive, unifying proteins from five SCOP folds, five CATH topologies and seven DALI domain dictionary globular folding topologies. Considering these structurally similar domains together sheds new light on the relationships between sequence, structure, function and evolution of thioredoxins.     

DOM-fold: a structure with crossing loops found in DmpA, ornithine acetyltransferase, and molybdenum cofactor-binding domain

Understanding relationships between sequence, structure, and evolution is important for functional characterization of proteins. Here, we define a novel DOM-fold as a consensus structure of the domains in DmpA (L-aminopeptidase D-Ala-esterase/amidase), OAT (ornithine acetyltransferase), and MocoBD (molybdenum cofactor-binding domain), and discuss possible evolutionary scenarios of its origin. As shown by a comprehensive structure similarity search, DOM-fold distinguished by a two-layered beta/alpha architecture of a particular topology with unusual crossing loops is unique to those three protein families. DmpA and OAT are evolutionarily related as indicated by their sequence, structural, and functional similarities. Structural similarity between the DmpA/OAT superfamily and the MocoBD domains has not been reported before. Contrary to previous reports, we conclude that functional similarities between DmpA/OAT proteins and N-terminal nucleophile (Ntn) hydrolases are convergent and are unlikely to be inherited from a common ancestor.     

Combining pairwise sequence similarity and support vector machines for detecting remote protein evolutionary and structural relationships.

One key element in understanding the molecular machinery of the cell is to understand the structure and function of each protein encoded in the genome. A very successful means of inferring the structure or function of a previously unannotated protein is via sequence similarity with one or more proteins whose structure or function is already known. Toward this end, we propose a means of representing proteins using pairwise sequence similarity scores. This representation, combined with a discriminative classification algorithm known as the support vector machine (SVM), provides a powerful means of detecting subtle structural and evolutionary relationships among proteins. The algorithm, called SVM-pairwise, when tested on its ability to recognize previously unseen families from the SCOP database, yields significantly better performance than SVM-Fisher, profile HMMs, and PSI-BLAST.     

Angle-distance image matching techniques for protein structure comparison

Proteins that contain similar structural elements often have analogous functions regardless of the degree of sequence similarity or structure connectivity in space. In general, protein structure comparison (PSC) provides a straightforward methodology for biologists to determine critical aspects of structure and function. Here, we developed a novel PSC technique based on angle-distance image (A-D image) transformation and matching, which is independent of sequence similarity and connectivity of secondary structure elements (SSEs). An A-D image is constructed by utilizing protein secondary structure information. According to various types of SSEs, the mutual SSE pairs of the query protein are classified into three different types of sub-images. Subsequently, corresponding sub-images between query and target protein structures are compared using modified cross-correlation approaches to identify the similarity of various patterns. Structural relationships among proteins are displayed by hierarchical clustering trees, which facilitate the establishment of the evolutionary relationships between structure and function of various proteins.Four standard testing datasets and one newly created dataset were used to evaluate the proposed method. The results demonstrate that proteins from these five datasets can be categorized in conformity with their spatial distribution of SSEs. Moreover, for proteins with low sequence identity that share high structure similarity, the proposed algorithms are an efficient and effective method for structural comparison.     

Folding studies of immunoglobulin-like beta-sandwich proteins suggest that they share a common folding pathway.

BACKGROUND: Are folding pathways conserved in protein families? To test this explicitly and ask to what extent structure specifies folding pathways requires comparison of proteins with a common fold. Our strategy is to choose members of a highly diverse protein family with no conservation of function and little or no sequence identity, but with structures that are essentially the same. The immunoglobulin-like fold is one of the most common structural families, and is subdivided into superfamilies with no detectable evolutionary or functional relationship. RESULTS: We compared the folding of a number of immunoglobulin-like proteins that have a common structural core and found a strong correlation between folding rate and stability. The results suggest that the folding pathways of these immunoglobulin-like proteins share common features. CONCLUSIONS: This study is the first to compare the folding of structurally related proteins that are members of different superfamilies. The most likely explanation for the results is that interactions that are important in defining the structure of immunoglobulin-like proteins are also used to guide folding.     

Coordinated amino acid changes in homologous protein families

In the tobamovirus coat protein family, amino acid residues at some spatially close positions are found to be substituted in a coordinated manner [Altschuh et al. (1987) J. Mol. Biol., 193, 693]. Therefore, these positions show an identical pattern of amino acid substitutions when amino acid sequences of these homologous proteins are aligned. Based on this principle, coordinated substitutions have been searched for in three additional protein families: serine proteases, cysteine proteases and the haemoglobins. Coordinated changes have been found in all three protein families mostly within structurally constrained regions. This method works with a varying degree of success depending on the function of the proteins, the range of sequence similarities and the number of sequences considered. By relaxing the criteria for residue selection, the method was adapted to cover a broader range of protein families and to study regions of the proteins having weaker structural constraints. The information derived by these methods provides a general guide for engineering of a large variety of proteins to analyse structure-function relationships.     

Structure and sequence relationships in the lipocalins and related proteins.

The lipocalins and fatty acid-binding proteins (FABPs) are two recently identified protein families that both function by binding small hydrophobic molecules. We have sought to clarify relationships within and between these two groups through an analysis of both structure and sequence. Within a similar overall folding pattern, we find large parts of the lipocalin and FABP structures to be quantitatively equivalent. The three largest structurally conserved regions within the lipocalin common core correspond to characteristic sequence motifs that we have used to determine the constitution of this family using an iterative sequence analysis procedure. This afforded a new interpretation of the family, which highlighted the difficulties of determining a comprehensive and coherent classification of the lipocalins. The first of the three conserved sequence motifs is also common to the FABPs and corresponds to a conserved structural element characteristic of both families. Similarities of structure and sequence within the two families suggests that they form part of a larger "structural superfamily"; we have christened this overall group the calycins to reflect the cup-shaped structure of its members.     

Structural and evolutionary relationships among the immunophilins: two ubiquitous families of peptidyl-prolyl cis-trans isomerases.

The immunophilins, protein receptors for the immunosuppressing drugs cyclosporin A and FK506 and related proteins from plants, fungi, and bacteria, have been analyzed structurally and evolutionarily. The cyclosporin A binding proteins (cyclophilins) represent one ubiquitous family of homologous proteins, and the FK506- and rapamycin-binding proteins (FKBPs) constitute a second, unrelated family. Multiple sequence alignments of members of each of these two protein families define the highly conserved residues that are likely to play important structural and functional roles, and mutations in representative members of these two families that abolish or alter function have been evaluated. FKBPs have undergone greater evolutionary divergence than the cyclophilins. Evolutionary trees were constructed using two distinct programs, and these trees establish the structural relationships that allow division of each of these families into subgroups. The results lead to the suggestion that several genes encoding isozymic forms of the FKBPs and possibly also of the cyclophilins existed in prokaryotes before the emergence of eukaryotes on earth and that representatives of these genes were transmitted to both kingdoms to give rise to current subfamilies of these proteins. By contrast, compartmentalization of both classes of immunophilins appears to have arisen independently in prokaryotes and eukaryotes, late in evolutionary history.     

The ion transporter superfamily

We define a novel superfamily of secondary carriers specific for cationic and anionic compounds, which we have termed the ion transporter (IT) superfamily. Twelve recognized and functionally defined families constitute this superfamily. We provide statistical sequence analyses demonstrating that these families were in fact derived from a common ancestor. Further, we characterize the 12 families in terms of (1) the known substrates transported, (2) the modes of transport and energy coupling mechanisms used, (3) the family sizes (in numbers of sequenced protein members in the current NCBI database), (4) the organismal distributions of the members of each family, (5) the size ranges of the constituent proteins, (6) the predicted topologies of these proteins, and (7) the occurrence of non-homologous auxiliary proteins that may either facilitate or be required for transport. No member of the superfamily is known to function in a capacity other than transport. Proteins in several of the constituent families are shown to have arisen by tandem intragenic duplication events, but topological variation has resulted from a variety of dissimilar genetic fusion, splicing and insertional events. The evolutionary relationships between the members of each family are defined, leading to predictions of functionally relevant orthologous relationships. Some but not all of the families include functionally dissimilar paralogues that arose by early extragenic duplication events.     

Genome archeology leading to the characterization and classification of transport proteins.

In the study of transmembrane transport, molecular phylogeny provides a reliable guide to protein structure, catalytic and noncatalytic transport mechanisms, mode of energy coupling and substrate specificity. It also allows prediction of the evolutionary history of a transporter family, leading to estimations of its age, source, and route of appearance. Phylogenetic analyses, therefore, provide a rational basis for the characterization and classification of transporters. A universal classification system has been described, based on both function and phylogeny, which has been designed to be applicable to all currently recognized and yet-to-be discovered transport proteins found in living organisms on Earth.     

ECOD: An Evolutionary Classification of Protein Domains

Understanding the evolution of a protein, including both close and distant relationships, often reveals insight into its structure and function. Fast and easy access to such up-to-date information facilitates research. We have developed a hierarchical evolutionary classification of all proteins with experimentally determined spatial structures, and presented it as an interactive and updatable online database. ECOD (Evolutionary Classification of protein Domains) is distinct from other structural classifications in that it groups domains primarily by evolutionary relationships (homology), rather than topology (or “fold”). This distinction highlights cases of homology between domains of differing topology to aid in understanding of protein structure evolution. ECOD uniquely emphasizes distantly related homologs that are difficult to detect, and thus catalogs the largest number of evolutionary links among structural domain classifications. Placing distant homologs together underscores the ancestral similarities of these proteins and draws attention to the most important regions of sequence and structure, as well as conserved functional sites. ECOD also recognizes closer sequence-based relationships between protein domains. Currently, approximately 100,000 protein structures are classified in ECOD into 9,000 sequence families clustered into close to 2,000 evolutionary groups. The classification is assisted by an automated pipeline that quickly and consistently classifies weekly releases of PDB structures and allows for continual updates. This synchronization with PDB uniquely distinguishes ECOD among all protein classifications. Finally, we present several case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.     

Efficient recognition of protein fold at low sequence identity by conservative application of Psi-BLAST: application

Based on a study involving structural comparisons of proteins sharing 25% or less sequence identity, three rounds of Psi-BLAST appear capable of identifying remote evolutionary homologs with greater than 95% confidence provided that more than 50% of the query sequence can be aligned with the target sequence. Since it seems that more than 80% of all homologous protein pairs may be characterized by a lack of significant sequence similarity, the experimental biologist is often confronted with a lack of guidance from conventional homology searches involving pair-wise sequence comparisons. The ability to disregard levels of sequence identity and expect value in Psi-BLAST if at least 50% of the query sequence has been aligned allows for generation of new hypotheses by consideration of matches that are conventionally disregarded. In one example, we suggest a possible evolutionary linkage between the cupredoxin and immunoglobulin fold families. A thermostable hypothetical protein of unknown function may be a circularly permuted homolog to phosphotriesterase, an enzyme capable of detoxifying organophosphate nerve agents. In a third example, the amino acid sequence of another hypothetical protein of unknown function reveals the ATP binding-site, metal binding site, and catalytic sidechain consistent with kinase activity of unknown specificity. This approach significantly expands the utility of existing sequence data to define the primary structure degeneracy of binding sites for substrates, cofactors and other proteins.     

Sialidase-like Asp-boxes: sequence-similar structures within different protein folds

Sequence similarity is the most common measure currently used to infer homology between proteins. Typically, homologous protein domains show sequence similarity over their entire lengths. Here we identify Asp box motifs, initially found as repeats in sialidases and neuraminidases, in new structural and sequence contexts. These motifs represent significantly similar sequences, localized to beta hairpins within proteins that are otherwise different in sequence and three-dimensional structure. By performing a combined sequence- and structure-based analysis we detect Asp boxes in more than nine protein families, including bacterial ribonucleases, sulfite oxidases, reelin, netrins, some lipoprotein receptors, and a variety of glycosyl hydrolases. Although the function common to each of these proteins, if any, remains unclear, we discuss possible functions of Asp boxes on the basis of previously determined experimental results and discuss different evolutionary scenarios for the origin of Asp-box containing proteins.     

Incorporation of evolutionary information into Rosetta comparative modeling

Prediction of protein structures from sequences is a fundamental problem in computational biology. Algorithms that attempt to predict a structure from sequence primarily use two sources of information. The first source is physical in nature: proteins fold into their lowest energy state. Given an energy function that describes the interactions governing folding, a method for constructing models of protein structures, and the amino acid sequence of a protein of interest, the structure prediction problem becomes a search for the lowest energy structure. Evolution provides an orthogonal source of information: proteins of similar sequences have similar structure, and therefore proteins of known structure can guide modeling. The relatively successful Rosetta approach takes advantage of the first, but not the second source of information during model optimization. Following the classic work by Andrej Sali and colleagues, we develop a probabilistic approach to derive spatial restraints from proteins of known structure using advances in alignment technology and the growth in the number of structures in the Protein Data Bank. These restraints define a region of conformational space that is high-probability, given the template information, and we incorporate them into Rosetta's comparative modeling protocol. The combined approach performs considerably better on a benchmark based on previous CASP experiments. Incorporating evolutionary information into Rosetta is analogous to incorporating sparse experimental data: in both cases, the additional information eliminates large regions of conformational space and increases the probability that energy-based refinement will hone in on the deep energy minimum at the native state.     

Evolutionary information hidden in a single protein structure

The knowledge of conserved sequences in proteins is valuable in identifying functionally or structurally important residues. Generating the conservation profile of a sequence requires aligning families of homologous sequences and having knowledge of their evolutionary relationships. Here, we report that the conservation profile at the residue level can be quantitatively derived from a single protein structure with only backbone information. We found that the reciprocal packing density profiles of protein structures closely resemble their sequence conservation profiles. For a set of 554 nonhomologous enzymes, 74% (408/554) of the proteins have a correlation coefficient > 0.5 between these two profiles. Our results indicate that the three-dimensional structure, instead of being a mere scaffold for positioning amino acid residues, exerts such strong evolutionary constraints on the residues of the protein that its profile of sequence conservation essentially reflects that of its structural characteristics.     

One fold with many functions: the evolutionary relationships between TIM barrel families based on their sequences,structures and functions

The eightfold (betaalpha) barrel structure, first observed in triose-phosphate isomerase, occurs ubiquitously in nature. It is nearly always an enzyme and most often involved in molecular or energy metabolism within the cell. In this review we bring together data on the sequence, structure and function of the proteins known to adopt this fold. We highlight the sequence and functional diversity in the 21 homologous superfamilies, which include 76 different sequence families. In many structures, the barrels are "mixed and matched" with other domains generating additional variety. Global and local structure-based alignments are used to explore the distribution of the associated functional residues on this common structural scaffold. Many of the substrates/co-factors include a phosphate moiety, which is usually but not always bound towards the C-terminal end of the sequence. Some, but not all, of these structures, exhibit a structurally conserved "phosphate binding motif". In contrast metal-ligating residues and catalytic residues are distributed along the sequence. However, we also found striking structural superposition of some of these residues. Lastly we consider the possible evolutionary relationships between these proteins, whose sequences are so diverse that even the most powerful approaches find few relationships, yet whose active sites all cluster at one end of the barrel. This extreme example of the "one fold-many functions" paradigm illustrates the difficulty of assigning function through a structural genomics approach for some folds.