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Sensitive pattern discovery with 'fuzzy' alignments of distantly related proteins.

MOTIVATION: Evolutionary comparison leads to efficient functional characterisation of hypothetical proteins. Here, our goal is to map specific sequence patterns to putative functional classes. The evolutionary signal stands out most clearly in a maximally diverse set of homologues. This diversity, however, leads to a number of technical difficulties. The targeted patterns-as gleaned from structure comparisons-are too sparse for statistically significant signals of sequence similarity and accurate multiple sequence alignment. RESULTS: We address this problem by a fuzzy alignment model, which probabilistically assigns residues to structurally equivalent positions (attributes) of the proteins. We then apply multivariate analysis to the 'attributes x proteins' matrix. The dimensionality of the space is reduced using non-negative matrix factorization. The method is general, fully automatic and works without assumptions about pattern density, minimum support, explicit multiple alignments, phylogenetic trees, etc. We demonstrate the discovery of biologically meaningful patterns in an extremely diverse superfamily related to urease.

Algorithms↗

Recognition of remotely related structural homologues using sequence profiles of aligned homologous protein structures.

In order to bridge the gap between proteins with three-dimensional (3-D) structural information and those without 3-D structures, extensive experimental and computational efforts for structure recognition are being invested. One of the rapid and simple computational approaches for structure recognition makes use of sequence profiles with sensitive profile matching procedures to identify remotely related homologous families. While adopting this approach we used profiles that are generated from structure-based sequence alignment of homologous protein domains of known structures integrated with sequence homologues. We present an assessment of this fast and simple approach. About one year ago, using this approach, we had identified structural homologues for 315 sequence families, which were not known to have any 3-D structural information. The subsequent experimental structure determination for at least one of the members in 110 of 315 sequence families allowed a retrospective assessment of the correctness of structure recognition. We demonstrate that correct folds are detected with an accuracy of 96.4% (106/110). Most (81/106) of the associations are made correctly to the specific structural family. For 23/106, the structure associations are valid at the superfamily level. Thus, profiles of protein families of known structure when used with sensitive profile-based search procedure result in structure association of high confidence. Further assignment at the level of superfamily or family would provide clues to probable functions of new proteins. Importantly, the public availability of these profiles from us could enable one to perform genome wide structure assignment in a local machine in a fast and accurate manner.

Amino Acid Sequence↗

Align-m--a new algorithm for multiple alignment of highly divergent sequences.

MOTIVATION: Multiple alignment of highly divergent sequences is a challenging problem for which available programs tend to show poor performance. Generally, this is due to a scoring function that does not describe biological reality accurately enough or a heuristic that cannot explore solution space efficiently enough. In this respect, we present a new program, Align-m, that uses a non-progressive local approach to guide a global alignment. RESULTS: Two large test sets were used that represent the entire SCOP classification and cover sequence similarities between 0 and 50% identity. Performance was compared with the publicly available algorithms ClustalW, T-Coffee and DiAlign. In general, Align-m has comparable or slightly higher accuracy in terms of correctly aligned residues, especially for distantly related sequences. Importantly, it aligns much fewer residues incorrectly, with average differences of over 15% compared with some of the other algorithms. AVAILABILITY: Align-m and the test sets are available at http://bioinformatics.vub.ac.be

Algorithms↗

Indelign: a probabilistic framework for annotation of insertions and deletions in a multiple alignment.

MOTIVATION: A quantitative study of molecular evolutionary events such as substitutions, insertions and deletions from closely related genomes requires (1) an accurate multiple sequence alignment program and (2) a method to annotate the insertions and deletions that explain the 'gaps' in the alignment. Although the former requirement has been extensively addressed, the latter problem has received little attention, especially in a comprehensive probabilistic framework. RESULTS: Here, we present Indelign, a program that uses a probabilistic evolutionary model to compute the most likely scenario of insertions and deletions consistent with an input multiple alignment. It is also capable of modifying the given alignment so as to obtain a better agreement with the evolutionary model. We find close to optimal performance and substantial improvement over alternative methods, in tests of Indelign on synthetic data. We use Indelign to analyze regulatory sequences in Drosophila, and find an excess of insertions over deletions, which is different from what has been reported for neutral sequences. AVAILABILITY: The Indelign program may be downloaded from the website http://veda.cs.uiuc.edu/indelign/ SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.

Algorithms↗

Alignments grow, secondary structure prediction improves.

Using information from sequence alignments significantly improves protein secondary structure prediction. Typically, more divergent profiles yield better predictions. Recently, various groups have shown that accuracy can be improved significantly by using PSI-BLAST profiles to develop new prediction methods. Here, we focused on the influences of various alignment strategies on two 8-year-old PHD methods. The following results stood out. (i) PHD using pairwise alignments predicts about 72% of all residues correctly in one of the three states: helix, strand, and other. Using larger databases and PSI-BLAST raised accuracy to 75%. (ii) More than 60% of the improvement originated from the growth of current sequence databases; about 20% resulted from detailed changes in the alignment procedure (substitution matrix, thresholds, and gap penalties). Another 20% of the improvement resulted from carefully using iterated PSI-BLAST searches. (iii) It is of interest that we failed to improve prediction accuracy further when attempting to refine the alignment by dynamic programming (MaxHom and ClustalW). (iv) Improvement through family growth appears to saturate at some point. However, most families have not reached this saturation. Hence, we anticipate that prediction accuracy will continue to rise with database growth.

Databases, Protein↗

Assessment of comparative modeling in CASP2.

An assessment is presented for all submissions to the comparative modeling challenge in the 1996 Critical Assessment of Structure Prediction (CASP2). Of the original 12 target structures, 9 were solved prior to the meeting: 8 by X-ray crystallography and 1 by NMR spectroscopy. These targets varied over a large range of difficulty, as assessed by the percentage sequence identity with the principal parent structure, which ranged from 20% up to 85%. The overall quality of the models reflected the similarity of the principal parent. As expected, when the sequence alignment was correct, the core was accurately modeled, with the largest deviations occurring in the loops. Models were built which gave C alpha root-mean-square deviations (RMSDs) compared with the observed structure of < 1 A for targets with high parental similarity; even at 26% sequence identity, the best model structures had C alpha deviations of only 2.2 A. Overall, these deviations are comparable with those observed between the parent structure and the target, but locally there are several examples where the model approaches closer to the target than does the parent. There were three targets below 25% sequence identity, and the models generated for these targets were, in general, significantly less accurate. This principally reflects errors in the alignment which, if systematically shifted, can generate C alpha RMSDs > 18 A. Compared with CASP1, the geometry of the models was significantly improved with no D-amino acids. By far the major contribution to RMSD error was the alignment accuracy, which varied from 100% down to 7% over the range of targets. In the structurally variable regions, global shifts, caused by hinge bending, were the major source of error, giving significantly lower local RMSDs than global RMSDs. In over 50% of these noncore regions, the difference between global and local RMSDs was more than 3 A, and was as high as 10 A for one structurally variable region. For the side chains, the chi 1 RMSDs are strongly correlated with the C alpha RMSDs. For models with C alpha deviations less than 1 A, on average 78.5% of side chains are placed in the correct rotamer, although the chi 1 RMSDs, though clearly better than random, were disappointing at around 46 degrees. As the backbone deviations increased, the side chain placement became less accurate, with an average chi 1 RMSD of 75 degrees on a 1.5-2.5 A C alpha backbone (average 51.4% correct rotamer). Refinement by energy minimization or molecular dynamics made only minor adjustments to improve local geometry and generally made small, but not significant, improvements to the RMSD. In total, 19 groups submitted 62 models (89 coordinate sets) that could be assessed. Most modelers used manual adjustments to sequence alignments and, in general, good alignments were obtained down to 25% sequence identity. The modeling methods ranged from "classical" modeling, involving core building followed by loop and side chain addition, to more sophisticated approaches based on probability distributions, Monte Carlo sampling or distance geometry. For each target, several groups produced equally good models, given the expected errors in the structures (about 0.5 A). No one method came out as clearly superior, although the approaches that inherit directly from the parents generally performed better than the more radical techniques. However, for each target there were some poor models, usually reflecting a poor sequence alignment, and the range of accuracy for each target is therefore large. Fully automated methods are able to perform very well for "easy" targets (85% sequence identity with parent), but when modeling using a distantly related parent, care and expertise, especially in performing the alignment, still appear to be important factors in generating accurate models.

Models, Molecular↗

Amino acid sequence analysis of bovine rotavirus B223 reveals a unique outer capsid protein VP4 and confirms a third bovine VP4 type.

The nucleotide and deduced amino acid sequence of the gene 4 of bovine rotavirus strain B223 is described. The open reading frame is predicted to encode a VP4 of 772 amino acids, shorter than described for any other rotavirus strain sequenced to date. B223 VP4 shows 70 to 73% similarity to other rotavirus VP4 proteins, demonstrating the presence of a unique VP4 type, and confirming a third VP4 allele in the bovine rotavirus population. Multiple sequence alignment with several other rotavirus strains created gaps in the sequence to account for a shorter VP4. The alignment shows a two contiguous amino acid deletions within the trypsin cleavage region of B223 VP4. Comparisons of two regions flanking the trypsin cleavage site, (aa 224 to 235, and aa 257 to 271) which show high homologies between strains, demonstrate that the region 5' to the trypsin cut site has a low homology (66%) to other rotavirus strains, although the region 3' to the trypsin cleavage site shows high homologies (86 to 93%) with other rotavirus strains. The lack of a conserved proline residue within the 5' flanking region suggests a possible altered local conformation of this site in B223 VP4. A second gap inserted into the VP4 of B223 on multiple sequence alignment is a three contiguous amino acid deletion at position 613-615 in the VP5* subunit. Previously defined biologic properties of this strain in relation to the determination of the amino acid composition of VP4 are discussed.

Alleles↗

DNA sequence and structure: direct and indirect recognition in protein-DNA binding.

MOTIVATION: Direct recognition, or direct readout, of DNA bases by a DNA-binding protein involves amino acids that interact directly with features specific to each base. Experimental evidence also shows that in many cases the protein achieves partial sequence specificity by indirect recognition, i.e., by recognizing structural properties of the DNA. (1) Could threading a DNA sequence onto a crystal structure of bound DNA help explain the indirect recognition component of sequence specificity? (2) Might the resulting pure-structure computational motif manifest itself in familiar sequence-based computational motifs? RESULTS: The starting structure motif was a crystal structure of DNA bound to the integration host factor protein (IHF) of E. coli. IHF is known to exhibit both direct and indirect recognition of its binding sites. (1) Threading DNA sequences onto the crystal structure showed statistically significant partial separation of 60 IHF binding sites from random and intragenic sequences and was positively correlated with binding affinity. (2) The crystal structure was shown to be equivalent to a linear Markov network, and so, to a joint probability distribution over sequences, computable in linear time. It was transformed algorithmically into several common pure-sequence representations, including (a) small sets of short exact strings, (b) weight matrices, (c) consensus regular patterns, (d) multiple sequence alignments, and (e) phylogenetic trees. In all cases the pure-sequence motifs retained statistically significant partial separation of the IHF binding sites from random and intragenic sequences. Most exhibited positive correlation with binding affinity. The multiple alignment showed some conserved columns, and the phylogenetic tree partially mixed low-energy sequences with IHF binding sites but separated high-energy sequences. The conclusion is that deformation energy explains part of indirect recognition, which explains part of IHF sequence-specific binding.

Algorithms↗

Reconstructing evolutionary trees from DNA and protein sequences: paralinear distances.

The reconstruction of phylogenetic trees from DNA and protein sequences is confounded by unequal rate effects. These effects can group rapidly evolving taxa with other rapidly evolving taxa, whether or not they are genealogically related. All algorithms are sensitive to these effects whenever the assumptions on which they are based are not met. The algorithm presented here, called paralinear distances, is valid for a much broader class of substitution processes than previous algorithms and is accordingly less affected by unequal rate effects. It may be used with all nucleic acid, protein, or other sequences, provided that their evolution may be modeled as a succession of Markov processes. The properties of the method have been proven both analytically and by computer simulations. Like all other methods, paralinear distances can fail when sequences are misaligned or when site-to-site sequence variation of rates is extensive. To examine the usefulness of paralinear distances, the "origin of the eukaryotes" has been investigated by the analysis of elongation factor Tu sequences with a variety of sequence alignments. It has been found that the order in which sequences are pairwise aligned strongly determines the topology which is reconstructed by paralinear distances (as it does for all other reconstruction methods tested). When the parts of the alignment that are unaffected by alignment order are analyzed, paralinear distances strongly select the eocyte topology. This provides evidence that the eocyte prokaryotes are the closest prokaryotic relatives of the eukaryotes.

Algorithms↗

A major component approach to presenting consensus sequences.

MOTIVATION: Summarizing and displaying the information contained in a set of aligned sequences is an important aid to identifying patterns within the sequences. A variety of forms of consensus sequences have been used previously to provide this information. However, these methods can cause a loss of information or introduce ambiguities into the consensus sequence, and some graphical approaches may become difficult to interpret due to visual distortion. RESULTS: We have developed a method to present a more precise and graphically clear view of a consensus sequence by using an approach based on defining the major components at each position in a sequence set. The major components are given in an ordered list and their frequencies are shown as histograms which can be colour coded to reflect conservative groupings. Minor components, a one-line character-based consensus sequence and information statistics can also be presented. As well as identifying the dominant sources of variation and conservation in the sequence set, the method also enables similarities and differences between subgroups of a sequence set to be readily assessed. AVAILIABILITY: On request from the authors. CONTACT: bcsmith@usthk.ust.hk, hxue@usthk. ust.hk

Amino Acid Sequence↗

Automated generation of heuristics for biological sequence comparison.

BACKGROUND: Exhaustive methods of sequence alignment are accurate but slow, whereas heuristic approaches run quickly, but their complexity makes them more difficult to implement. We introduce bounded sparse dynamic programming (BSDP) to allow rapid approximation to exhaustive alignment. This is used within a framework whereby the alignment algorithms are described in terms of their underlying model, to allow automated development of efficient heuristic implementations which may be applied to a general set of sequence comparison problems. RESULTS: The speed and accuracy of this approach compares favourably with existing methods. Examples of its use in the context of genome annotation are given. CONCLUSIONS: This system allows rapid implementation of heuristics approximating to many complex alignment models, and has been incorporated into the freely available sequence alignment program, exonerate.

Algorithms↗

Partial rRNA sequences in marine yeasts: a model for identification of marine eukaryotes.

The V3 variable region of the large subunit rRNA was examined for nucleotide sequence signatures as potential taxonomic tools. Data are presented on 117 species, representing 23 genera of basidiomycetous yeasts. The results of nucleotide sequence alignments indicate that strains within species have identical base sequences and that species may differ from one another by one to more than 100 base positions. Phylogenetic analyses of the alignments indicates relationships among species, including the prediction of synonymous species and the clustering of species belonging to the Ustilaginales and Tremellales. These results suggest that species-specific nucleotide sequences can be used for the development of techniques for population analyses of a variety of marine and other microeukaryotes.

Animals↗

Retrovirus integrase: identification of a potential leucine zipper motif.

The secondary structure of the retrovirus integration protein (IN) was predicted from seven inferred retrovirus IN sequences. The IN sequences were aligned by computer and the phylogenetic relationships between them were determined. The secondary structure of the aligned IN sequences was predicted by two consensus prediction methods. The predicted secondary structural patterns from the two consensus prediction schemes were compared with and superimposed on a composite structural profile of hydropathic/chain flexibility/amphipathic indexes with each index profile being calculated independently for the aligned IN sequences. The use of this composite structural profile not only enhanced the prediction accuracy but also helped in defining the surface loop regions which would be otherwise unpredictable by the use of consensus prediction methods alone. An amphipathic helix was identified by these united structural prediction-chain property profiles. Helical wheel analysis gave the amphipathic helix a coiled-coil like pattern which was similar to the leucine zipper discovered for some eukaryotic gene regulatory proteins. The proposed amphipathic helix may play an essential role in defining the biological properties of IN.

Amino Acid Sequence↗

Protein family classification based on searching a database of blocks.

The most highly conserved regions of proteins can be represented as "blocks" of locally aligned sequence segments. Previously, an automated system was introduced to generate a database of blocks that is searched for local similarities using a sequence query. Here, we describe a method for searching this database that can also reveal significant global similarities. Local and global alignments are scored independently, so they can be used in concert to infer homology. A set of 7082 diverse sequences not represented in the database provided queries for testing this approach. The resulting distributions of scores led to guidelines for interpretation of search data and to the classification of 289 uncatalogued sequences into known groups. Thirty-eight of these relationships appear to be new discoveries. We also show how searching a database of blocks can be used to detect repeated domains and to find distinct cross-family relationships that were missed in searches of sequence databases.

Animals↗

Improving contact predictions by the combination of correlated mutations and other sources of sequence information.

We have previously developed a method for predicting interresidue contacts using information about correlated mutations in multiple sequence alignments. The predictions generated with this method were clearly better than random but not enough for their use in de novo protein folding experiments. We assess the possibility of improving contact predictions combining information from the following variables: correlated mutations, sequence conservation, sequence separation along the chain, alignment stability, family size, residue-specific contact occupancy and formation of contact networks. The application of a protocol for combining these independent variables leads to contact predictions that are on average two times better than those obtained initially with correlated mutations. Correlated mutations can be effectively combined with other types of information derived from multiple sequence alignments. Among the different variables tried, sequence conservation and contact density are particularly relevant for the combination with correlated mutations.

Amino Acid Sequence↗

Structure function relationship among alpha-crystallin related small heat shock proteins.

A sequence alignment is presented which permits the detection of the sequence and structural homology among alpha-crystallin subunits, alphaA and alphaB, and distantly related sHsps, MjHsp16.5 and wheat Hsp16.9. This alignment shows that homology extends beyond the alpha-crystallin domain. Variations in the polydisperse quaternary structure appear, in part, dependent upon the N-terminal 18 and 19 amino acids that are essential for subunit interactions in polydisperse sHsps. The hydrophobic sequence that follows these N-terminal amino acids shares a number of aromatic amino acids and has significant homology with MjHsp16.5. In the second exon of alpha-crystallin, sequence homology is concentrated in a region with chaperone and ANS binding sites. It is clear that the binding site for ANS and its derivative, bis-ANS, requires both positively charged amino acids and hydrophobic interactions. Therefore, its binding is not a true measure of hydrophobic surface exposure. The limited homology and secondary structure in the following C-terminal sequences is related to the pattern of association of other sHsp subunits and/or functional differences. Our study suggests that alphaA has evolved in the lens to chaperone exposed beta-sheet edges of the betagamma crystallins and their proteolytic fragments. Also, both time and a harsh environment such as that in the lens interior, beta-sheet proteins would naturally generate beta-sheet edges. The interaction between such edges results in insoluble, abnormal protein aggregation and in the lens, light scattering elements that cause cataract.

Amino Acid Sequence↗

Convergent Island Statistics: a fast method for determining local alignment score significance.

MOTIVATION: Background distribution statistics for profile-based sequence alignment algorithms cannot be calculated analytically, and hence such algorithms must resort to measuring the significance of an alignment score by assessing its location among a distribution of background alignment scores. The Gumbel parameters that describe this background distribution are usually pre-computed for a limited number of scoring systems, gap schemes, and sequence lengths and compositions. The use of such look-ups is known to introduce errors, which compromise the significance assessment of a remote homology relationship. One solution is to estimate the background distribution for each pair of interest by generating a large number of sequence shuffles and use the distribution of their scores to approximate the parameters of the underlying extreme value distribution. This is computationally very expensive, as a large number of shuffles are needed to precisely estimate the score statistics. RESULTS: Convergent Island Statistics (CIS) is a computationally efficient solution to the problem of calculating the Gumbel distribution parameters for an arbitrary pair of sequences and an arbitrary set of gap and scoring schemes. The basic idea behind our method is to recognize the lack of similarity for any pair of sequences early in the shuffling process and thus save on the search time. The method is particularly useful in the context of profile-profile alignment algorithms where the normalization of alignment scores has traditionally been a challenging task. CONTACT: aleksandar@eidogen.com SUPPLEMENTARY INFORMATION: http://www.eidogen-sertanty.com/Documents/convergent_island_stats_sup.pdf.

Algorithms↗

The context-dependence of amino acid properties.

One of the current limitations of using sequence alignments to identify proteins with similar structures is that some proteins with similar structures do not have significant sequence similarity by identity. One way to address this "hidden-homology" problem is to match amino acids based on their chemical and physical properties. However, the amino acid properties overlap, creating orthogonal dimensions of similarity, the relative strengths of which are ambiguous. It has been observed that the role an amino acid plays (and hence the property that is important) at a site in a protein depends on its secondary and tertiary environment. To approximate and take advantage of this dependence on context for improving the sensitivity of alignments of proteins whose structures are unknown, we propose a surrogate definition of context based on the pattern of hydropathy in a small window of contiguous neighbors surrounding each amino acid. We present the results of an experiment in which a search-based program iteratively tests and selects various properties in independent contexts, and incrementally increases the ability of sequence alignments to detect relationships among distantly-related proteins. The method is shown to perform better than using the MDM78 substitution table for partial match scores.

Amino Acid Sequence↗