Sensitive detection of sequence similarity using combinatorial pattern discovery: a challenging study of two distantly related protein families

We investigate the performance of combinatorial pattern discovery to detect remote sequence similarities in terms of both biological accuracy and computational efficiency for a pair of distantly related families, as a case study. The two families represent the cupredoxins and multicopper oxidases, both containing blue copper-binding domains. These families present a challenging case due to low sequence similarity, different local structure, and variable sequence conservation at their copper-binding active sites. In this study, we investigate a new approach for automatically identifying weak sequence similarities that is based on combinatorial pattern discovery. We compare its performance with a traditional, HMM-based scheme and obtain estimates for sensitivity and specificity of the two approaches. Our analysis suggests that pattern discovery methods can be substantially more sensitive in detecting remote protein relationships while at the same time guaranteeing high specificity.     

Bacillus subtilis YkuK protein is distantly related to RNase H

In addition to one hypothetical viral sequence from Bacteriophage KVP40, the PfamA family of unknown function DUF458 (Pfam Accession No. PF04308) encompasses several uncharacterized bacterial proteins including Bacillus subtilis YkuK protein. Using Meta-BASIC, a highly sensitive method for detection of distant similarity between proteins, we assign DUF458 family members to the ribonuclease H-like (RNase H-like) superfamily. DUF458 sequences maintain all core secondary structure elements of RNase H-like fold and share several conserved, presumably active site residues with RNase HI, including an invariant DDE motif. In addition to providing a model structure for a previously uncharacterized protein family, this finding suggests that DUF458 proteins function as nucleases. The unusual phyletic pattern, together with a presence of DUF458 in several thermophilic organisms, may suggest a potential role of these proteins in DNA repair in stressful conditions such as an extreme heat or other stress that causes spore formation.     

2-D graphical representation of protein sequences and its application to coronavirus phylogeny

Based on a five-letter model of the 20 amino acids, we propose a new 2-D graphical representation of protein sequence. Then we transform the 2-D graphical representation into a numerical characterization that will facilitate quantitative comparisons of protein sequences. As an application, we construct the phylogenetic tree of 56 coronavirus spike proteins. The resulting tree agrees well with the established taxonomic groups.     

Progressive combinatorial algorithm for multiple structural alignments: application to distantly related proteins

MALECON is a progressive combinatorial procedure for multiple alignments of protein structures. It searches a library of pairwise alignments for all three-protein alignments in which a specified number of residues is consistently aligned. These alignments are progressively expanded to include additional proteins and more spatially equivalent residues, subject to certain criteria. This action involves superimposing the aligned proteins by their hitherto equivalent residues and searching for additional Calpha atoms that lie close in space. The performance of MALECON is illustrated and compared with several extant multiple structure alignment methods by using as test the globin homologous superfamily, the OB and the Jellyrolls folds. MALECON gives better definitions of the common structural features in the structurally more diverse proteins of the OB and Jellyrolls folds, but it yields comparable results for the more similar globins. When no consistent multiple alignments can be derived for all members of a protein group, our procedure is still capable of automatically generating consistent alignments and common core definitions for subgroups of the members. This finding is illustrated for proteins of the OB fold and SH3 domains, believed to share common structural features, and should be very instrumental in homology modeling and investigations of protein evolution.     

INTERALIGN: interactive alignment editor for distantly related protein sequences

SUMMARY: Improving and ascertaining the quality of a multiple sequence alignment is a very challenging step in protein sequence analysis. This is particularly the case when dealing with sequences in the 'twilight zone', i.e. sharing < 30% identity. Here we describe INTERALIGN, a dedicated user-friendly alignment editor including a view of secondary structures and a synchronized display of carbon alpha traces of corresponding protein structures. Profile alignment, using CLUSTALW, is implemented to improve the alignment of a sequence of unknown structure with the visually optimized structural alignment as compared with a standard multiple sequence alignment. Tree-based ordering further helps in identifying the structure closest to a given sequence.     

蛋白质序列的一种新的三维图形表示及其应用

基于氨基酸的五字母模型,给出蛋白质序列的一种新的三维图形表示,然后构造一个12维向量来刻画蛋白质序列,这个向量的分量是与12个图形相对应的D／D矩阵的正规化的ALE-指标。最后基于s结构蛋白对冠状病毒进行系统发生分析来阐明该方法的有用性。     

Recognition of distantly related protein sequences using conserved motifs and neural networks.

A sensitive technique for protein sequence motif recognition based on neural networks has been developed. It involves three major steps. (1) At each appropriate alignment position of a set of N matched sequences, a set of N aligned oligopeptides is specified with preselected window length. N neural nets are subsequently and successively trained on N-1 amino acid spans after eliminating each ith oligopeptide. A test for recognition of each of the ith spans is performed. The average neural net recognition over N such trials is used as a measure of conservation for the particular windowed region of the multiple alignment. This process is repeated for all possible spans of given length in the multiple alignment. (2) The M most conserved regions are regarded as motifs and the oligopeptides within each are used to train intensively M individual neural networks. (3) The M networks are then applied in a search for related primary structures in a databank of known protein sequences. The oligopeptide spans in the database sequence with strongest neural net output for each of the M networks are saved and then scored according to the output signals and the proper combination that follows the expected N- to C-terminal sequence order. The motifs from the database with highest similarity scores can then be used to retrain the M neural nets, which can be subsequently utilized for further searches in the databank, thus providing even greater sensitivity to recognize distant familial proteins. This technique was successfully applied to the integrase, DNA-polymerase and immunoglobulin families.     

Identifying property based sequence motifs in protein families and superfamilies: application to DNase-1 related endonucleases

MOTIVATION: Identification of short conserved sequence motifs common to a protein family or superfamily can be more useful than overall sequence similarity in suggesting the function of novel gene products. Locating motifs still requires expert knowledge, as automated methods using stringent criteria may not differentiate subtle similarities from statistical noise. RESULTS: We have developed a novel automatic method, based on patterns of conservation of 237 physical-chemical properties of amino acids in aligned protein sequences, to find related motifs in proteins with little or no overall sequence similarity. As an application, our web-server MASIA identified 12 property-based motifs in the apurinic/apyrimidinic endonuclease (APE) family of DNA-repair enzymes of the DNase-I superfamily. Searching with these motifs located distantly related representatives of the DNase-I superfamily, such as Inositol 5'-polyphosphate phosphatases in the ASTRAL40 database, using a Bayesian scoring function. Other proteins containing APE motifs had no overall sequence or structural similarity. However, all were phosphatases and/or had a metal ion binding active site. Thus our automated method can identify discrete elements in distantly related proteins that define local structure and aspects of function. We anticipate that our method will complement existing ones to functionally annotate novel protein sequences from genomic projects. AVAILABILITY: MASIA WEB site: http://www.scsb.utmb.edu/masia/masia.html SUPPLEMENTARY INFORMATION: The dendrogram of 42 APE sequences used to derive motifs is available on http://www.scsb.utmb.edu/comp_biol.html/DNA_repair/publication.html     

Statistical potential-based amino acid similarity matrices for aligning distantly related protein sequences

Aligning distantly related protein sequences is a long-standing problem in bioinformatics, and a key for successful protein structure prediction. Its importance is increasing recently in the context of structural genomics projects because more and more experimentally solved structures are available as templates for protein structure modeling. Toward this end, recent structure prediction methods employ profile-profile alignments, and various ways of aligning two profiles have been developed. More fundamentally, a better amino acid similarity matrix can improve a profile itself; thereby resulting in more accurate profile-profile alignments. Here we have developed novel amino acid similarity matrices from knowledge-based amino acid contact potentials. Contact potentials are used because the contact propensity to the other amino acids would be one of the most conserved features of each position of a protein structure. The derived amino acid similarity matrices are tested on benchmark alignments at three different levels, namely, the family, the superfamily, and the fold level. Compared to BLOSUM45 and the other existing matrices, the contact potential-based matrices perform comparably in the family level alignments, but clearly outperform in the fold level alignments. The contact potential-based matrices perform even better when suboptimal alignments are considered. Comparing the matrices themselves with each other revealed that the contact potential-based matrices are very different from BLOSUM45 and the other matrices, indicating that they are located in a different basin in the amino acid similarity matrix space.     

The Caenorhabditis elegans vitellogenin gene family includes a gene encoding a distantly related protein.

While the nematode Caenorhabditis elegans is more primitive than most egg-laying organisms, it's vitellogenins, or yolk protein precursors, appear to be more complex. C. elegans oocytes accumulate two major classes of yolk proteins. The first consists of two polypeptides with an Mr of about 170,000 (yp170A and yp170B) encoded by a family of five closely related genes called vit-1 through vit-5. The second class consists of two smaller proteins with Mr values of 115,000 (yp115) and 88,000 (yp88) which are cut from a single precursor. Here we report the cloning and analysis of a single-copy gene (vit-6) that encodes this precursor. The lengths of the gene and its mRNA are about 5 X 10(3) base pairs. Like vit-1 through vit-5, vit-6 is expressed exclusively in adult hermaphrodites. Comparison of portions of the coding sequence indicates that vit-6 is distantly related to the vit-1 through vit-5 gene family. Thus, even though the two classes of yolk proteins are antigenically and physically distinct, they are encoded by a single highly diverged gene family.     

Expression and genomic analysis of midasin,a novel and highly conserved AAA protein distantly related to dynein

Background  

The largest open reading frame in the Saccharomyces genome encodes midasin (MDN1p, YLR106p), an AAA ATPase of 560 kDa that is essential for cell viability. Orthologs of midasin have been identified in the genome projects for Drosophila, Arabidopsis, and Schizosaccharomyces pombe.     

A novel phorbol ester receptor/protein kinase, nPKC, distantly related to the protein kinase C family

Protein kinase C (PKC)-related cDNA clones encode an 84 kd protein, nPKC. nPKC contains a cysteine-rich repeat sequence homologous to that seen in conventional PKCs (alpha, beta I, beta II, and gamma), which make up a family of 77-78 kd proteins with closely related sequences. nPKC, when expressed in COS cells, confers increased high-affinity phorbol ester receptor activity to intact cells. Antibodies raised against nPKC identified a 90 kd protein in rabbit brain extract as well as in extracts from COS cells transfected with the cDNA construct. nPKC shows protein kinase activity that is regulated by phospholipid, diacylglycerol, and phorbol ester but is independent of Ca2+. The structural and enzymological characteristics of nPKC clearly distinguish it from conventional PKCs, which until now have been the only substances believed to mediate the various effects of diacylglycerol and phorbol esters. These results suggest an additional signaling pathway involving nPKC.     

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.     

A novel approach to identifying regulatory motifs in distantly related genomes

Although proven successful in the identification of regulatory motifs, phylogenetic footprinting methods still show some shortcomings. To assess these difficulties, most apparent when applying phylogenetic footprinting to distantly related organisms, we developed a two-step procedure that combines the advantages of sequence alignment and motif detection approaches. The results on well-studied benchmark datasets indicate that the presented method outperforms other methods when the sequences become either too long or too heterogeneous in size.