Increased coverage of protein families with the blocks database servers

The Blocks Database WWW (http://blocks.fhcrc.org ) and Email (blocks@blocks.fhcrc.org ) servers provide tools to search DNA and protein queries against the Blocks+ Database of multiple alignments, which represent conserved protein regions. Blocks+ nearly doubles the number of protein families included in the database by adding families from the Pfam-A, ProDom and Domo databases to those from PROSITE and PRINTS. Other new features include improved Block Searcher statistics, searching with NCBI's IMPALA program and 3D display of blocks on PDB structures.     

Superior performance in protein homology detection with the Blocks Database servers.

The Blocks Database World Wide Web (http://www.blocks.fhcrc.org ) and Email (blocks@blocks.fhcrc.org) servers provide tools for the detection and analysis of protein homology based on alignment blocks representing conserved regions of proteins. During the past year, searching has been augmented by supplementation of the Blocks Database with blocks from the Prints Database, for a total of 4754 blocks from 1163 families. Blocks from both the Blocks and Prints Databases and blocks that are constructed from sequences submitted to Block Maker can be used for blocks-versus-blocks searching of these databases with LAMA, and for viewing logos and bootstrap trees. Sensitive searches of up-to-date protein sequence databanks are carried out via direct links to the MAST server using position-specific scoring matrices and to the BLAST and PSI-BLAST servers using consensus-embedded sequence queries. Utilizing the trypsin family to evaluate performance, we illustrate the superiority of blocks-based tools over expert pairwise searching or Hidden Markov Models.     

Blocks+: a non-redundant database of protein alignment blocks derived from multiple compilations.

MOTIVATION: As databanks grow, sequence classification and prediction of function by searching protein family databases becomes increasingly valuable. The original Blocks Database, which contains ungapped multiple alignments for families documented in Prosite, can be searched to classify new sequences. However, Prosite is incomplete, and families from other databases are now available to expand coverage of the Blocks Database. RESULTS: To take advantage of protein family information present in several existing compilations, we have used five databases to construct Blocks+, a unified database that is built on the PROTOMAT/BLOSUM scoring model and that can be searched using a single algorithm for consistent sequence classification. The LAMA blocks-versus-blocks searching program identifies overlapping protein families, making possible a non-redundant hierarchical compilation. Blocks+ consists of all blocks derived from PROSITE, blocks from Prints not present in PROSITE, blocks from Pfam-A not present in PROSITE or Prints, and so on for ProDom and Domo, for a total of 1995 protein families represented by 8909 blocks, doubling the coverage of the original Blocks Database. A challenge for any procedure aimed at non-redundancy is to retain related but distinct families while discarding those that are duplicates. We illustrate how using multiple compilations can minimize this potential problem by examining the SNF2 family of ATPases, which is detectably similar to distinct families of helicases and ATPases. AVAILABILITY: http://blocks.fhcrc.org/     

Searching databases of conserved sequence regions by aligning protein multiple-alignments.

A general searching method for comparing multiple sequence alignments was developed to detect sequence relationships between conserved protein regions. Multiple alignments are treated as sequences of amino acid distributions and aligned by comparing pairs of such distributions. Four different comparison measures were tested and the Pearson correlation coefficient chosen. The method is sensitive, detecting weak sequence relationships between protein families. Relationships are detected beyond the range of conventional sequence database searches, illustrating the potential usefulness of the method. The previously undetected relation between flavoprotein subunits of two oxidoreductase families points to the potential active site in one of the families. The similarity between the bacterial RecA, DnaA and Rad51 protein families reveals a region in DnaA and Rad51 proteins likely to bind and unstack single-stranded DNA. Helix--turn--helix DNA binding domains from diverse proteins are readily detected and shown to be similar to each other. Glycosylasparaginase and gamma-glutamyltransferase enzymes are found to be similar in their proteolytic cleavage sites. The method has been fully implemented on the World Wide Web at URL: http://blocks.fhcrc.org/blocks-bin/LAMAvsearch.     

CODEHOP (COnsensus-DEgenerate Hybrid Oligonucleotide Primer) PCR primer design

We have developed a new primer design strategy for PCR amplification of distantly related gene sequences based on consensus-degenerate hybrid oligonucleotide primers (CODEHOPs). An interactive program has been written to design CODEHOP PCR primers from conserved blocks of amino acids within multiply-aligned protein sequences. Each CODEHOP consists of a pool of related primers containing all possible nucleotide sequences encoding 3-4 highly conserved amino acids within a 3' degenerate core. A longer 5' non-degenerate clamp region contains the most probable nucleotide predicted for each flanking codon. CODEHOPs are used in PCR amplification to isolate distantly related sequences encoding the conserved amino acid sequence. The primer design software and the CODEHOP PCR strategy have been utilized for the identification and characterization of new gene orthologs and paralogs in different plant, animal and bacterial species. In addition, this approach has been successful in identifying new pathogen species. The CODEHOP designer (http://blocks.fhcrc.org/codehop.html) is linked to BlockMaker and the Multiple Alignment Processor within the Blocks Database World Wide Web (http://blocks.fhcrc.org).     

A transition probability model for amino acid substitutions from blocks.

Substitution matrices have been useful for sequence alignment and protein sequence comparisons. The BLOSUM series of matrices, which had been derived from a database of alignments of protein blocks, improved the accuracy of alignments previously obtained from the PAM-type matrices estimated from only closely related sequences. Although BLOSUM matrices are scoring matrices now widely used for protein sequence alignments, they do not describe an evolutionary model. BLOSUM matrices do not permit the estimation of the actual number of amino acid substitutions between sequences by correcting for multiple hits. The method presented here uses the Blocks database of protein alignments, along with the additivity of evolutionary distances, to approximate the amino acid substitution probabilities as a function of actual evolutionary distance. The PMB (Probability Matrix from Blocks) defines a new evolutionary model for protein evolution that can be used for evolutionary analyses of protein sequences. Our model is directly derived from, and thus compatible with, the BLOSUM matrices. The model has the additional advantage of being easily implemented.     

Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

Comparison of multiple protein structures has a broad range of applications in the analysis of protein structure, function and evolution. Multiple structure alignment tools (MSTAs) are necessary to obtain a simultaneous comparison of a family of related folds. In this study, we have developed a method for multiple structure comparison largely based on sequence alignment techniques. A widely used Structural Alphabet named Protein Blocks (PBs) was used to transform the information on 3D protein backbone conformation as a 1D sequence string. A progressive alignment strategy similar to CLUSTALW was adopted for multiple PB sequence alignment (mulPBA). Highly similar stretches identified by the pairwise alignments are given higher weights during the alignment. The residue equivalences from PB based alignments are used to obtain a three dimensional fit of the structures followed by an iterative refinement of the structural superposition. Systematic comparisons using benchmark datasets of MSTAs underlines that the alignment quality is better than MULTIPROT, MUSTANG and the alignments in HOMSTRAD, in more than 85% of the cases. Comparison with other rigid-body and flexible MSTAs also indicate that mulPBA alignments are superior to most of the rigid-body MSTAs and highly comparable to the flexible alignment methods.     

SIFT: Predicting amino acid changes that affect protein function

Single nucleotide polymorphism (SNP) studies and random mutagenesis projects identify amino acid substitutions in protein-coding regions. Each substitution has the potential to affect protein function. SIFT (Sorting Intolerant From Tolerant) is a program that predicts whether an amino acid substitution affects protein function so that users can prioritize substitutions for further study. We have shown that SIFT can distinguish between functionally neutral and deleterious amino acid changes in mutagenesis studies and on human polymorphisms. SIFT is available at http://blocks.fhcrc.org/sift/SIFT.html.     

Enhanced statistics for local alignment of multiple alignments improves prediction of protein function and structure

MOTIVATION: Improved comparisons of multiple sequence alignments (profiles) with other profiles can identify subtle relationships between protein families and motifs significantly beyond the resolution of sequence-based comparisons. RESULTS: The local alignment of multiple alignments (LAMA) method was modified to estimate alignment score significance by applying a new measure based on Fisher's combining method. To verify the new procedure, we used known protein structures, sequence annotations and cyclical relations consistency analysis (CYRCA) sets of consistently aligned blocks. Using the new significance measure improved the sensitivity of LAMA without altering its selectivity. The program performed better than other profile-to-profile methods (COMPASS and Prof_sim) and a sequence-to-profile method (PSI-BLAST). The testing was large scale and used several parameters, including pseudo-counts profile calculations and local ungapped blocks or more extended gapped profiles. This comparison provides guidelines to the relative advantages of each method for different cases. We demonstrate and discuss the unique advantages of using block multiple alignments of protein motifs.     

Multiple flexible structure alignment using partial order graphs

MOTIVATION: Existing comparisons of protein structures are not able to describe structural divergence and flexibility in the structures being compared because they focus on identifying a common invariant core and ignore parts of the structures outside this core. Understanding the structural divergence and flexibility is critical for studying the evolution of functions and specificities of proteins. RESULTS: A new method of multiple protein structure alignment, POSA (Partial Order Structure Alignment), was developed using a partial order graph representation of multiple alignments. POSA has two unique features: (1) identifies and classifies regions that are conserved only in a subset of input structures and (2) allows internal rearrangements in protein structures. POSA outperforms other programs in the cases where structural flexibilities exist and provides new insights by visualizing the mosaic nature of multiple structural alignments. POSA is an ideal tool for studying the variation of protein structures within diverse structural families. AVAILABILITY: POSA is freely available for academic users on a Web server at http://fatcat.burnham.org/POSA     

MUSTANG: a multiple structural alignment algorithm

Multiple structural alignment is a fundamental problem in structural genomics. In this article, we define a reliable and robust algorithm, MUSTANG (MUltiple STructural AligNment AlGorithm), for the alignment of multiple protein structures. Given a set of protein structures, the program constructs a multiple alignment using the spatial information of the C(alpha) atoms in the set. Broadly based on the progressive pairwise heuristic, this algorithm gains accuracy through novel and effective refinement phases. MUSTANG reports the multiple sequence alignment and the corresponding superposition of structures. Alignments generated by MUSTANG are compared with several handcurated alignments in the literature as well as with the benchmark alignments of 1033 alignment families from the HOMSTRAD database. The performance of MUSTANG was compared with DALI at a pairwise level, and with other multiple structural alignment tools such as POSA, CE-MC, MALECON, and MultiProt. MUSTANG performs comparably to popular pairwise and multiple structural alignment tools for closely related proteins, and performs more reliably than other multiple structural alignment methods on hard data sets containing distantly related proteins or proteins that show conformational changes.     

TIGRFAMs: a protein family resource for the functional identification of proteins

TIGRFAMs is a collection of protein families featuring curated multiple sequence alignments, hidden Markov models and associated information designed to support the automated functional identification of proteins by sequence homology. We introduce the term 'equivalog' to describe members of a set of homologous proteins that are conserved with respect to function since their last common ancestor. Related proteins are grouped into equivalog families where possible, and otherwise into protein families with other hierarchically defined homology types. TIGRFAMs currently contains over 800 protein families, available for searching or downloading at www.tigr.org/TIGRFAMs. Classification by equivalog family, where achievable, complements classification by orthology, superfamily, domain or motif. It provides the information best suited for automatic assignment of specific functions to proteins from large-scale genome sequencing projects.     

Identification of local conformational similarity in structurally variable regions of homologous proteins using protein blocks

Structure comparison tools can be used to align related protein structures to identify structurally conserved and variable regions and to infer functional and evolutionary relationships. While the conserved regions often superimpose well, the variable regions appear non superimposable. Differences in homologous protein structures are thought to be due to evolutionary plasticity to accommodate diverged sequences during evolution. One of the kinds of differences between 3-D structures of homologous proteins is rigid body displacement. A glaring example is not well superimposed equivalent regions of homologous proteins corresponding to α-helical conformation with different spatial orientations. In a rigid body superimposition, these regions would appear variable although they may contain local similarity. Also, due to high spatial deviation in the variable region, one-to-one correspondence at the residue level cannot be determined accurately. Another kind of difference is conformational variability and the most common example is topologically equivalent loops of two homologues but with different conformations. In the current study, we present a refined view of the "structurally variable" regions which may contain local similarity obscured in global alignment of homologous protein structures. As structural alphabet is able to describe local structures of proteins precisely through Protein Blocks approach, conformational similarity has been identified in a substantial number of 'variable' regions in a large data set of protein structural alignments; optimal residue-residue equivalences could be achieved on the basis of Protein Blocks which led to improved local alignments. Also, through an example, we have demonstrated how the additional information on local backbone structures through protein blocks can aid in comparative modeling of a loop region. In addition, understanding on sequence-structure relationships can be enhanced through our approach. This has been illustrated through examples where the equivalent regions in homologous protein structures share sequence similarity to varied extent but do not preserve local structure.     

ProDom: automated clustering of homologous domains

The ProDom database is a comprehensive set of protein domain families automatically generated from the SWISS-PROT and TrEMBL sequence databases. An associated database, ProDom-CG, has been derived as a restriction of ProDom to completely sequenced genomes. The ProDom construction method is based on iterative PSI-BLAST searches and multiple alignments are generated for each domain family. The ProDom web server provides the user with a set of tools to visualise multiple alignments, phylogenetic trees and domain architectures of proteins, as well as a BLAST-based server to analyse new sequences for homologous domains. The comprehensive nature of ProDom makes it particularly useful to help sustain the growth of InterPro.     

FastBLAST: homology relationships for millions of proteins

Background

All-versus-all BLAST, which searches for homologous pairs of sequences in a database of proteins, is used to identify potential orthologs, to find new protein families, and to provide rapid access to these homology relationships. As DNA sequencing accelerates and data sets grow, all-versus-all BLAST has become computationally demanding.

Methodology/Principal Findings

We present FastBLAST, a heuristic replacement for all-versus-all BLAST that relies on alignments of proteins to known families, obtained from tools such as PSI-BLAST and HMMer. FastBLAST avoids most of the work of all-versus-all BLAST by taking advantage of these alignments and by clustering similar sequences. FastBLAST runs in two stages: the first stage identifies additional families and aligns them, and the second stage quickly identifies the homologs of a query sequence, based on the alignments of the families, before generating pairwise alignments. On 6.53 million proteins from the non-redundant Genbank database (“NR”), FastBLAST identifies new families 25 times faster than all-versus-all BLAST. Once the first stage is completed, FastBLAST identifies homologs for the average query in less than 5 seconds (8.6 times faster than BLAST) and gives nearly identical results. For hits above 70 bits, FastBLAST identifies 98% of the top 3,250 hits per query.

Conclusions/Significance

FastBLAST enables research groups that do not have supercomputers to analyze large protein sequence data sets. FastBLAST is open source software and is available at http://microbesonline.org/fastblast.     

PATMAT: a searching and extraction program for sequence, pattern and block queries and databases

A program has been developed that provides molecular biologistswith multiple tools for searching databases, yet uses a verysimple interface. PATMATcan use protein or (translated) DNAsequences, patterns or blocks of aligned proteins as queriesof databases consisting of amino acid or nucleotide sequences,patterns or blocks. The ability to search databases of blocksby ‘on-the-fly’ conversion to scoring matrices providesa new tool for detection and evaluation of distant relationships.PATMAT uses a pull-down, menu-driven interface to carry outits multiple searching, extraction and viewing functions. Eachquery or database type is recognized, reported, and the appropriatesearch carried out, with matches and alignments reported inwindows as they occur. Any of the high scoring matches can beexported to a file, viewed and recalled as a query using onlya few keystrokes or mouse selections. Searches of multiple databasefiles are carried out by user selection within a window. PATMATruns under DOS; the searching engine also runs under UNIX.     

A workbench for multiple alignment construction and analysis

Multiple sequence alignment can be a useful technique for studying molecular evolution, as well as for analyzing relationships between structure or function and primary sequence. We have developed for this purpose an interactive program, MACAW (Multiple Alignment Construction and Analysis Workbench), that allows the user to construct multiple alignments by locating, analyzing, editing, and combining "blocks" of aligned sequence segments. MACAW incorporates several novel features. (1) Regions of local similarity are located by a new search algorithm that avoids many of the limitations of previous techniques. (2) The statistical significance of blocks of similarity is evaluated using a recently developed mathematical theory. (3) Candidate blocks may be evaluated for potential inclusion in a multiple alignment using a variety of visualization tools. (4) A user interface permits each block to be edited by moving its boundaries or by eliminating particular segments, and blocks may be linked to form a composite multiple alignment. No completely automatic program is likely to deal effectively with all the complexities of the multiple alignment problem; by combining a powerful similarity search algorithm with flexible editing, analysis and display tools, MACAW allows the alignment strategy to be tailored to the problem at hand.