Fast structure alignment for protein databank searching.

A fast method is described for searching and analyzing the protein structure databank. It uses secondary structure followed by residue matching to compare protein structures and is developed from a previous structural alignment method based on dynamic programming. Linear representations of secondary structures are derived and their features compared to identify equivalent elements in two proteins. The secondary structure alignment then constrains the residue alignment, which compares only residues within aligned secondary structures and with similar buried areas and torsional angles. The initial secondary structure alignment improves accuracy and provides a means of filtering out unrelated proteins before the slower residue alignment stage. It is possible to search or sort the protein structure databank very quickly using just secondary structure comparisons. A search through 720 structures with a probe protein of 10 secondary structures required 1.7 CPU hours on a Sun 4/280. Alternatively, combined secondary structure and residue alignments, with a cutoff on the secondary structure score to remove pairs of unrelated proteins from further analysis, took 10.1 CPU hours. The method was applied in searches on different classes of proteins and to cluster a subset of the databank into structurally related groups. Relationships were consistent with known families of protein structure.     

Molecular evolution of protein conformational changes revealed by a network of evolutionarily coupled residues

An improved understanding of protein conformational changes has broad implications for elucidating the mechanisms of various biological processes and for the design of protein engineering experiments. Understanding rearrangements of residue interactions is a key component in the challenge of describing structural transitions. Evolutionary properties of protein sequences and structures are extensively studied; however, evolution of protein motions, especially with respect to interaction rearrangements, has yet to be explored. Here, we investigated the relationship between sequence evolution and protein conformational changes and discovered that structural transitions are encoded in amino acid sequences as coevolving residue pairs. Furthermore, we found that highly coevolving residues are clustered in the flexible regions of proteins and facilitate structural transitions by forming and disrupting their interactions cooperatively. Our results provide insight into the evolution of protein conformational changes and help to identify residues important for structural transitions.     

Charged residues at protein interaction interfaces: unexpected conservation and orchestrated divergence

Protein-protein interactions play an essential role in the functioning of cell. The importance of charged residues and their diverse role in protein-protein interactions have been well studied using experimental and computational methods. Often, charged residues located in protein interaction interfaces are conserved across the families of homologous proteins and protein complexes. However, on a large scale, it has been recently shown that charged residues are significantly less conserved than other residue types in protein interaction interfaces. The goal of this work is to understand the role of charged residues in the protein interaction interfaces through their conservation patterns. Here, we propose a simple approach where the structural conservation of the charged residue pairs is analyzed among the pairs of homologous binary complexes. Specifically, we determine a large set of homologous interactions using an interaction interface similarity measure and catalog the basic types of conservation patterns among the charged residue pairs. We find an unexpected conservation pattern, which we call the correlated reappearance, occurring among the pairs of homologous interfaces more frequently than the fully conserved pairs of charged residues. Furthermore, the analysis of the conservation patterns across different superkingdoms as well as structural classes of proteins has revealed that the correlated reappearance of charged residues is by far the most prevalent conservation pattern, often occurring more frequently than the unconserved charged residues. We discuss a possible role that the new conservation pattern may play in the long-range electrostatic steering effect.     

Regions of minimal structural variation among members of protein domain superfamilies: application to remote homology detection and modelling using distant relationships

Structurally conserved regions or structural templates have been identified and examined for features such as amino acid content, solvent accessibility, secondary structures, non-polar interaction, residue packing and extent of structural deviations in 179 aligned members of superfamilies involving 1208 pairs of protein domains. An analysis of these structural features shows that the retention of secondary structural conservation and similar hydrogen bonding pattern within the templates is 2.5 and 1.8 times higher, respectively, than full-length alignments suggesting that they form the minimum structural requirement of a superfamily. The identification and availability of structural templates find value in different areas of protein structure prediction and modelling such as in sensitive sequence searches, accurate sequence alignment and three-dimensional modelling on the basis of distant relationships.     

Suggestions for "safe" residue substitutions in site-directed mutagenesis

The conserved topological structure observed in various molecular families such as globins or cytochromes c allows structural equivalencing of residues in every homologous structure and defines in a coherent way a global alignment in each sequence family. A search was performed for equivalent residue pairs in various topological families that were buried in protein cores or exposed at the protein surface and that had mutated but maintained similar unmutated environments. Amino acid residues with atoms in contact with the mutated residue pairs defined the environment. Matrices of preferred amino acid exchanges were then constructed and preferred or avoided amino acid substitutions deduced. Given the conserved atomic neighborhoods, such natural in vivo substitutions are subject to similar constrains as point mutations performed in site-directed mutagenesis experiments. The exchange matrices should provide guidelines for "safe" amino acid substitutions least likely to disturb the protein structure, either locally or in its overall folding pathway, and most likely to allow probing the structural and functional significance of the substituted site.     

MatAlign: precise protein structure comparison by matrix alignment

We propose a detailed protein structure alignment method named "MatAlign". It is a two-step algorithm. Firstly, we represent 3D protein structures as 2D distance matrices, and align these matrices by means of dynamic programming in order to find the initially aligned residue pairs. Secondly, we refine the initial alignment iteratively into the optimal one according to an objective scoring function. We compare our method against DALI and CE, which are among the most accurate and the most widely used of the existing structural comparison tools. On the benchmark set of 68 protein structure pairs by Fischer et al., MatAlign provides better alignment results, according to four different criteria, than both DALI and CE in a majority of cases. MatAlign also performs as well in structural database search as DALI does, and much better than CE does. MatAlign is about two to three times faster than DALI, and has about the same speed as CE. The software and the supplementary information for this paper are available at http://xena1.ddns.comp.nus.edu.sg/~genesis/MatAlign/.     

Adaptive Smith–Waterman residue match seeding for protein structural alignment

The POLYFIT rigid‐body algorithm for automated global pairwise and multiple protein structural alignment is presented. Smith–Waterman local alignment is used to establish a set of seed equivalences that are extended using Needleman–Wunsch dynamic programming techniques. Structural and functional interaction constraints provided by evolution are encoded as one‐dimensional residue physical environment strings for alignment of highly structurally overlapped protein pairs. Local structure alignment of more distantly related pairs is carried out using rigid‐body conformational matching of 15‐residue fragments, with allowance made for less stringent conformational matching of metal‐ion and small molecule ligand‐contact, disulphide bridge, and cis‐peptide correspondences. Protein structural plasticity is accommodated through the stepped adjustment of a single empirical distance parameter value in the calculation of the Smith–Waterman dynamic programming matrix. Structural overlap is used both as a measure of similarity and to assess alignment quality. Pairwise alignment accuracy has been benchmarked against that of 10 widely used aligners on the Sippl and Wiederstein set of difficult pairwise structure alignment problems, and more extensively against that of Matt, SALIGN, and MUSTANG in pairwise and multiple structural alignments of protein domains with low shared sequence identity in the SCOP‐ASTRAL 40% compendium. The results demonstrate the advantages of POLYFIT over other aligners in the efficient and robust identification of matching seed residue positions in distantly related protein targets and in the generation of longer structurally overlapped alignment lengths. Superposition‐based application areas include comparative modeling and protein and ligand design. POLYFIT is available on the Web server at http://polyfit.insa‐toulouse.fr . Proteins 2013; 81:1823–1839. © 2013 Wiley Periodicals, Inc.     

Using a residue clash map to functionally characterize protein recombination hybrids

In this article, we introduce a rapid, protein sequence database-driven approach to characterize all contacting residue pairs present in protein hybrids for inconsistency with protein family structural features. This approach is based on examining contacting residue pairs with different parental origins for different types of potentially unfavorable interactions (i.e. electrostatic repulsion, steric hindrance, cavity formation and hydrogen bond disruption). The identified clashing residue pairs between members of a protein family are then contrasted against functionally characterized hybrid libraries. Comparisons for five different protein recombination studies available in the literature: (i) glycinamide ribonucleotide transformylase (GART) from Escherichia coli (purN) and human (hGART), (ii) human Mu class glutathione S-transferase (GST) M1-1 and M2-2, (iii) beta-lactamase TEM-1 and PSE-4, (iv) catechol-2,3-oxygenase xylE and nahH, and (v) dioxygenases (toluene dioxygenase, tetrachlorobenzene dioxygenase and biphenyl dioxygenase) reveal that the patterns of identified clashing residue pairs are remarkably consistent with experimentally found patterns of functional crossover profiles. Specifically, we show that the proposed residue clash maps are on average 5.0 times more effective than randomly generated clashes and 1.6 times more effective than residue contact maps at explaining the observed crossover distributions among functional members of hybrid libraries. This suggests that residue clash maps can provide quantitative guidelines for the placement of crossovers in the design of protein recombination experiments.     

Using multiple sequence correlation analysis to characterize functionally important protein regions

Protein co-evolution under structural and functional constraints necessitates the preservation of important interactions. Identifying functionally important regions poses many obstacles in protein engineering efforts. In this paper, we present a bioinformatics-inspired approach (residue correlation analysis, RCA) for predicting functionally important domains from protein family sequence data. RCA is comprised of two major steps: (i) identifying pairs of residue positions that mutate in a coordinated manner, and (ii) using these results to identify protein regions that interact with an uncommonly high number of other residues. We hypothesize that strongly correlated pairs result not only from contacting pairs, but also from residues that participate in conformational changes involved during catalysis or important interactions necessary for retaining functionality. The results show that highly mobile loops that assist in ligand association/dissociation tend to exhibit high correlation. RCA results exhibit good agreement with the findings of experimental and molecular dynamics studies for the three protein families that are analyzed: (i) DHFR (dihydrofolate reductase), (ii) cyclophilin, and (iii) formyl-transferase. Specifically, the specificity (percentage of correct predictions) in all three cases is substantially higher than those obtained by entropic measures or contacting residue pairs. In addition, we use our approach in a predictive fashion to identify important regions of a transmembrane amino acid transporter protein for which there is limited structural and functional information available.     

Toward optimal fragment generations for ab initio protein structure assembly

Fragment assembly using structural motifs excised from other solved proteins has shown to be an efficient method for ab initio protein‐structure prediction. However, how to construct accurate fragments, how to derive optimal restraints from fragments, and what the best fragment length is are the basic issues yet to be systematically examined. In this work, we developed a gapless‐threading method to generate position‐specific structure fragments. Distance profiles and torsion angle pairs are then derived from the fragments by statistical consistency analysis, which achieved comparable accuracy with the machine‐learning‐based methods although the fragments were taken from unrelated proteins. When measured by both accuracies of the derived distance profiles and torsion angle pairs, we come to a consistent conclusion that the optimal fragment length for structural assembly is around 10, and at least 100 fragments at each location are needed to achieve optimal structure assembly. The distant profiles and torsion angle pairs as derived by the fragments have been successfully used in QUARK for ab initio protein structure assembly and are provided by the QUARK online server at http://zhanglab.ccmb. med.umich.edu/QUARK/ . Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Multiple protein sequence alignment from tertiary structure comparison: assignment of global and residue confidence levels.

An algorithm is presented for the accurate and rapid generation of multiple protein sequence alignments from tertiary structure comparisons. A preliminary multiple sequence alignment is performed using sequence information, which then determines an initial superposition of the structures. A structure comparison algorithm is applied to all pairs of proteins in the superimposed set and a similarity tree calculated. Multiple sequence alignments are then generated by following the tree from the branches to the root. At each branchpoint of the tree, a structure-based sequence alignment and coordinate transformations are output, with the multiple alignment of all structures output at the root. The algorithm encoded in STAMP (STructural Alignment of Multiple Proteins) is shown to give alignments in good agreement with published structural accounts within the dehydrogenase fold domains, globins, and serine proteinases. In order to reduce the need for visual verification, two similarity indices are introduced to determine the quality of each generated structural alignment. Sc quantifies the global structural similarity between pairs or groups of proteins, whereas Pij' provides a normalized measure of the confidence in the alignment of each residue. STAMP alignments have the quality of each alignment characterized by Sc and Pij' values and thus provide a reproducible resource for studies of residue conservation within structural motifs.     

Analysis on sliding helices and strands in protein structural comparisons: a case study with protein kinases

Protein structural alignments are generally considered as 'golden standard' for the alignment at the level of amino acid residues. In this study we have compared the quality of pairwise and multiple structural alignments of about 5900 homologous proteins from 718 families of known 3-D structures. We observe shifts in the alignment of regular secondary structural elements (helices and strands) between pairwise and multiple structural alignments. The differences between pairwise and multiple structural alignments within helical and beta-strand regions often correspond to 4 and 2 residue positions respectively. Such shifts correspond approximately to "one turn" of these regular secondary structures. We have performed manual analysis explicitly on the family of protein kinases. We note shifts of one or two turns in helix-helix alignments obtained using pairwise and multiple structural alignments. Investigations on the quality of the equivalent helix-helix, strand-strand pairs in terms of their residue side-chain accessibilities have been made. Our results indicate that the quality of the pairwise alignments is comparable to that of the multiple structural alignments and, in fact, is often better. We propose that pairwise alignment of protein structures should also be used in formulation of methods for structure prediction and evolutionary analysis.     

Detection of Pairwise Residue Proximity by Covariation Analysis for 3D-Structure Prediction of G-Protein-Coupled Receptors

G-protein-coupled receptor (GPCR) is one of the most important targets for medicines. Homology modeling based on the crystal structure of bovine rhodopsin is currently the most frequently used method for GPCR targeted drug design. Information about residue-residue contacts and the structural specificity in the subfamily is essential for constructing more precise 3D structures, to distinguish the structural differences between the template and targets. In this study, we adopted the covariation analysis to extract information about residue-residue interactions from the amino acid sequence. In the opsin family, a large number of adjacent covarying residue pairs were detected. The detected residue pairs have a strong tendency to gather in some regions important for the structure and function. These results suggest that the covariation analysis is practically utilized to detect adjacent residue pairs and also to apply for predicting functional sites. Analyses of other GPCR subfamilies, olfactory receptor and chemokine receptor families, demonstrated that some adjacent covarying residue pairs were common. Thus, the covariation analysis has possibilities in the substantial improvement of the 3D-structure modeling of GPCRs and in the detection of functional sites such as the ligand-binding sites.     

Statistical analysis of pair-wise compatibility of spatially nearest neighbor and adjacent residues in alpha-helix and beta-strands: application to a minimal model for secondary structure prediction

Secondary structural elements like alpha-helix and beta-strands possess distinctly different structural features and thus the relative positioning of the nearest neighbor residues, and also the sequence-wise adjacent residues is important in determining the structural preference. In the present work we have statistically examined the pair-wise compatibility pattern of physically nearest neighbors and separately the adjacent residue pairs along the sequence in between the nearest neighbor partners in alpha-helices and beta-strands. It has been demonstrated that the patterns and hence, the physical basis of the compatibility of adjacent residue pairs and the spatially nearest neighbors are significantly different in most cases. The influence of tertiary contacts on the pair-wise compatibility is shown to be significant for beta-strands while it is small for alpha-helices. Based on the compatibility of physically nearest neighbors and the sequence-wise adjacent residue pairs, a minimal model has been constructed to predict the alpha-helices, beta-strands and coils of a protein from its sequence. Application of this method to 100 sequences shows that it has a predictive capability comparable to that of other more sophisticated statistical methods.     

Determination of reliable regions in protein sequence alignments

Judging the significance of alignments is still a major problem in sequence comparison. We present a method to delineate reliable regions within an alignment. This differs from standard approaches in that it does not attempt to attribute one significance value to the alignment as a whole, but assesses alignment quality locally. An algorithm is provided that predicts which residue pairs in an alignment are likely to be correctly matched. The predictions are evaluated by comparison with alignments taken from tertiary structural superpositions.     

A segment alignment approach to protein comparison

MOTIVATION: Local structure segments (LSSs) are small structural units shared by unrelated proteins. They are extensively used in protein structure comparison, and predicted LSSs (PLSSs) are used very successfully in ab initio folding simulations. However, predicted or real LSSs are rarely exploited by protein sequence comparison programs that are based on position-by-position alignments. RESULTS: We developed a SEgment Alignment algorithm (SEA) to compare proteins described as a collection of predicted local structure segments (PLSSs), which is equivalent to an unweighted graph (network). Any specific structure, real or predicted corresponds to a specific path in this network. SEA then uses a network matching approach to find two most similar paths in networks representing two proteins. SEA explores the uncertainty and diversity of predicted local structure information to search for a globally optimal solution. It simultaneously solves two related problems: the alignment of two proteins and the local structure prediction for each of them. On a benchmark of protein pairs with low sequence similarity, we show that application of the SEA algorithm improves alignment quality as compared to FFAS profile-profile alignment, and in some cases SEA alignments can match the structural alignments, a feat previously impossible for any sequence based alignment methods.     

Analysis on sliding helices and strands in protein structural comparisons: A case study with protein kinases

Protein structural alignments are generally considered as ‘golden standard’ for the alignment at the level of amino acid residues. In this study we have compared the quality of pairwise and multiple structural alignments of about 5900 homologous proteins from 718 families of known 3-D structures. We observe shifts in the alignment of regular secondary structural elements (helices and strands) between pairwise and multiple structural alignments. The differences between pairwise and multiple structural alignments within helical and β-strand regions often correspond to 4 and 2 residue positions respectively. Such shifts correspond approximately to “one turn” of these regular secondary structures. We have performed manual analysis explicitly on the family of protein kinases. We note shifts of one or two turns in helix-helix alignments obtained using pairwise and multiple structural alignments. Investigations on the quality of the equivalent helix-helix, strand-strand pairs in terms of their residue side-chain accessibilities have been made. Our results indicate that the quality of the pairwise alignments is comparable to that of the multiple structural alignments and, in fact, is often better. We propose that pairwise alignment of protein structures should also be used in formulation of methods for structure prediction and evolutionary analysis.     

Integrated analysis of residue coevolution and protein structure in ABC transporters

Intraprotein side chain contacts can couple the evolutionary process of amino acid substitution at one position to that at another. This coupling, known as residue coevolution, may vary in strength. Conserved contacts thus not only define 3-dimensional protein structure, but also indicate which residue-residue interactions are crucial to a protein's function. Therefore, prediction of strongly coevolving residue-pairs helps clarify molecular mechanisms underlying function. Previously, various coevolution detectors have been employed separately to predict these pairs purely from multiple sequence alignments, while disregarding available structural information. This study introduces an integrative framework that improves the accuracy of such predictions, relative to previous approaches, by combining multiple coevolution detectors and incorporating structural contact information. This framework is applied to the ABC-B and ABC-C transporter families, which include the drug exporter P-glycoprotein involved in multidrug resistance of cancer cells, as well as the CFTR chloride channel linked to cystic fibrosis disease. The predicted coevolving pairs are further analyzed based on conformational changes inferred from outward- and inward-facing transporter structures. The analysis suggests that some pairs coevolved to directly regulate conformational changes of the alternating-access transport mechanism, while others to stabilize rigid-body-like components of the protein structure. Moreover, some identified pairs correspond to residues previously implicated in cystic fibrosis.