Verification of the PREFAB alignment database

The verification of the PREFAB database containing golden standard protein alignments was performed. It has revealed a significant number of differences between the sequences from PREFAB and PDB databases. It was shown that compared to the sequences given in the PDB database 575 alignments refered to a sequence with a gap; such alignments were excluded. Furthermore, compared to the PDB-sequences a single substitute or the insertions were found for 440 aminoacid sequences from PREFAB database; these sequences were edited. SCOP domain analysis has shown that only 502 alignments in the resulting set contain the sequences from the same family. Finally, eliminating duplicates, we have created a new golden standard alignment database PREFAB-P based on PREFAB; the PREFAB-P database contains 581 alignments.     

MUSCLE: multiple sequence alignment with high accuracy and high throughput

We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.     

LigBase: a database of families of aligned ligand binding sites in known protein sequences and structures

A database comprising all ligand-binding sites of known structure aligned with all related protein sequences and structures is described. Currently, the database contains approximately 50000 ligand-binding sites for small molecules found in the Protein Data Bank (PDB). The structure-structure alignments are obtained by the Combinatorial Extension (CE) program (Shindyalov and Bourne, Protein Eng., 11, 739-747, 1998) and sequence-structure alignments are extracted from the ModBase database of comparative protein structure models for all known protein sequences (Sanchez et al., Nucleic Acids Res., 28, 250-253, 2000). It is possible to search for binding sites in LigBase by a variety of criteria. LigBase reports summarize ligand data including relevant structural information from the PDB file, such as ligand type and size, and contain links to all related protein sequences in the TrEMBL database. Residues in the binding sites are graphically depicted for comparison with other structurally defined family members. LigBase provides a resource for the analysis of families of related binding sites.     

Building multiple sequence alignments with a flavor of HSSP alignments

Homology-derived secondary structure of proteins (HSSP) is a well-known database of multiple sequence alignments (MSAs) which merges information of protein sequences and their three-dimensional structures. It is available for all proteins whose structure is deposited in the PDB. It is also used by STING and (Java)Protein Dossier to calculate and present relative entropy as a measure of the degree of conservation for each residue of proteins whose structure has been solved and deposited in the PDB. However, if the STING and (Java)Protein Dossier are to provide support for analysis of protein structures modeled in computers or being experimentally solved but not yet deposited in the PDB, then we need a new method for building alignments having a flavor of HSSP alignments (myMSAr). The present study describes a new method and its corresponding databank (SH2QS--database of sequences homologue to the query [structure-having] sequence). Our main interest in making myMSAr was to measure the degree of residue conservation for a given query sequence, regardless of whether it has a corresponding structure deposited in the PDB. In this study, we compare the measurement of residue conservation provided by corresponding alignments produced by HSSP and SH2QS. As a case study, we also present two biologically relevant examples, the first one highlighting the equivalence of analysis of the degree of residue conservation by using HSSP or SH2QS alignments, and the second one presenting the degree of residue conservation for a structure modeled in a computer, which , as a consequence, does not have an alignment reported by HSSP.     

PISCES: a protein sequence culling server

PISCES is a public server for culling sets of protein sequences from the Protein Data Bank (PDB) by sequence identity and structural quality criteria. PISCES can provide lists culled from the entire PDB or from lists of PDB entries or chains provided by the user. The sequence identities are obtained from PSI-BLAST alignments with position-specific substitution matrices derived from the non-redundant protein sequence database. PISCES therefore provides better lists than servers that use BLAST, which is unable to identify many relationships below 40% sequence identity and often overestimates sequence identity by aligning only well-conserved fragments. PDB sequences are updated weekly. PISCES can also cull non-PDB sequences provided by the user as a list of GenBank identifiers, a FASTA format file, or BLAST/PSI-BLAST output.     

Reconstruction of genuine pair-wise sequence alignment.

In many applications, the algorithmically obtained alignment ideally should restore the "golden standard" (GS) alignment, which superimposes positions originating from the same position of the common ancestor of the compared sequences. The average similarity between the algorithmically obtained and GS alignments ("the quality") is an important characteristic of an alignment algorithm. We proposed to determine the quality of an algorithm, using sequences that were artificially generated in accordance with an appropriate evolution model; the approach was applied to the global version of the Smith-Waterman algorithm (SWA). The quality of SWA is between 97% (for a PAM distance of 60) and 70% (for a PAM distance of 300). The percentage of identical aligned residues is the same for algorithmic and GS alignments. The total length of indels in algorithmic alignments is less than in the GS-mainly due to a substantial decrease in the number of indels in algorithmic alignments.     

The PAS fold. A redefinition of the PAS domain based upon structural prediction.

In the postgenomic era it is essential that protein sequences are annotated correctly in order to help in the assignment of their putative functions. Over 1300 proteins in current protein sequence databases are predicted to contain a PAS domain based upon amino acid sequence alignments. One of the problems with the current annotation of the PAS domain is that this domain exhibits limited similarity at the amino acid sequence level. It is therefore essential, when using proteins with low-sequence similarities, to apply profile hidden Markov model searches for the PAS domain-containing proteins, as for the PFAM database. From recent 3D X-ray and NMR structures, however, PAS domains appear to have a conserved 3D fold as shown here by structural alignment of the six representative 3D-structures from the PDB database. Large-scale modelling of the PAS sequences from the PFAM database against the 3D-structures of these six structural prototypes was performed. All 3D models generated (> 5700) were evaluated using prosaii. We conclude from our large-scale modelling studies that the PAS and PAC motifs (which are separately defined in the PFAM database) are directly linked and that these two motifs form the PAS fold. The existing subdivision in PAS and PAC motifs, as used by the PFAM and SMART databases, appears to be caused by major differences in sequences in the region connecting these two motifs. This region, as has been shown by Gardner and coworkers for human PAS kinase (Amezcua, C.A., Harper, S.M., Rutter, J. & Gardner, K.H. (2002) Structure 10, 1349-1361, [1]), is very flexible and adopts different conformations depending on the bound ligand. Some PAS sequences present in the PFAM database did not produce a good structural model, even after realignment using a structure-based alignment method, suggesting that these representatives are unlikely to have a fold resembling any of the structural prototypes of the PAS domain superfamily.     

Sequence-similar, structure-dissimilar protein pairs in the PDB

It is often assumed that in the Protein Data Bank (PDB), two proteins with similar sequences will also have similar structures. Accordingly, it has proved useful to develop subsets of the PDB from which "redundant" structures have been removed, based on a sequence-based criterion for similarity. Similarly, when predicting protein structure using homology modeling, if a template structure for modeling a target sequence is selected by sequence alone, this implicitly assumes that all sequence-similar templates are equivalent. Here, we show that this assumption is often not correct and that standard approaches to create subsets of the PDB can lead to the loss of structurally and functionally important information. We have carried out sequence-based structural superpositions and geometry-based structural alignments of a large number of protein pairs to determine the extent to which sequence similarity ensures structural similarity. We find many examples where two proteins that are similar in sequence have structures that differ significantly from one another. The source of the structural differences usually has a functional basis. The number of such proteins pairs that are identified and the magnitude of the dissimilarity depend on the approach that is used to calculate the differences; in particular sequence-based structure superpositioning will identify a larger number of structurally dissimilar pairs than geometry-based structural alignments. When two sequences can be aligned in a statistically meaningful way, sequence-based structural superpositioning provides a meaningful measure of structural differences. This approach and geometry-based structure alignments reveal somewhat different information and one or the other might be preferable in a given application. Our results suggest that in some cases, notably homology modeling, the common use of nonredundant datasets, culled from the PDB based on sequence, may mask important structural and functional information. We have established a data base of sequence-similar, structurally dissimilar protein pairs that will help address this problem (http://luna.bioc.columbia.edu/rachel/seqsimstrdiff.htm).     

CKAAPs DB: a conserved key amino acid positions database

The Conserved Key Amino Acid Positions DataBase (CKAAPs DB) provides access to an analysis of structurally similar proteins with dissimilar sequences where key residues within a common fold are identified. The derivation and significance of CKAAPs starting from pairwise structure alignments is described fully in Reddy et al. [Reddy,B.V.B., Li,W.W., Shindyalov,I.N. and Bourne,P.E. (2000) PROTEINS:, in press]. The CKAAPs identified from this theoretical analysis are provided to experimentalists and theoreticians for potential use in protein engineering and modeling. It has been suggested that CKAAPs may be crucial features for protein folding, structural stability and function. Over 170 substructures, as defined by the Combinatorial Extension (CE) database, which are found in approximately 3000 representative polypeptide chains have been analyzed and are available in the CKAAPs DB. CKAAPs DB also provides CKAAPs of the representative set of proteins derived from the CE and FSSP databases. Thus the database contains over 5000 representative poly-peptide chains, covering all known structures in the PDB. A web interface to a relational database permits fast retrieval of structure-sequence alignments, CKAAPs and associated statistics. Users may query by PDB ID, protein name, function and Enzyme Classification number. Users may also submit protein alignments of their own to obtain CKAAPs. An interface to display CKAAPs on each structure from a web browser is also being implemented. CKAAPs DB is maintained by the San Diego Supercomputer Center and accessible at the URL http://ckaaps.sdsc.edu.     

Pandit: a database of protein and associated nucleotide domains with inferred trees

MOTIVATION: A large, high-quality database of homologous sequence alignments with good estimates of their corresponding phylogenetic trees will be a valuable resource to those studying phylogenetics. It will allow researchers to compare current and new models of sequence evolution across a large variety of sequences. The large quantity of data may provide inspiration for new models and methodology to study sequence evolution and may allow general statements about the relative effect of different molecular processes on evolution. RESULTS: The Pandit 7.6 database contains 4341 families of sequences derived from the seed alignments of the Pfam database of amino acid alignments of families of homologous protein domains (Bateman et al., 2002). Each family in Pandit includes an alignment of amino acid sequences that matches the corresponding Pfam family seed alignment, an alignment of DNA sequences that contain the coding sequence of the Pfam alignment when they can be recovered (overall, 82.9% of sequences taken from Pfam) and the alignment of amino acid sequences restricted to only those sequences for which a DNA sequence could be recovered. Each of the alignments has an estimate of the phylogenetic tree associated with it. The tree topologies were obtained using the neighbor joining method based on maximum likelihood estimates of the evolutionary distances, with branch lengths then calculated using a standard maximum likelihood approach.     

DNA reference alignment benchmarks based on tertiary structure of encoded proteins

MOTIVATION: Multiple sequence alignments (MSAs) are at the heart of bioinformatics analysis. Recently, a number of multiple protein sequence alignment benchmarks (i.e. BAliBASE, OXBench, PREFAB and SMART) have been released to evaluate new and existing MSA applications. These databases have been well received by researchers and help to quantitatively evaluate MSA programs on protein sequences. Unfortunately, analogous DNA benchmarks are not available, making evaluation of MSA programs difficult for DNA sequences. RESULTS: This work presents the first known multiple DNA sequence alignment benchmarks that are (1) comprised of protein-coding portions of DNA (2) based on biological features such as the tertiary structure of encoded proteins. These reference DNA databases contain a total of 3545 alignments, comprising of 68 581 sequences. Two versions of the database are available: mdsa_100s and mdsa_all. The mdsa_100s version contains the alignments of the data sets that TBLASTN found 100% sequence identity for each sequence. The mdsa_all version includes all hits with an E-value score above the threshold of 0.001. A primary use of these databases is to benchmark the performance of MSA applications on DNA data sets. The first such case study is included in the Supplementary Material.     

Information about the protein secondary structure improves quality of an alignment of protein sequences

All popular algorithms of pair-wise alignment of protein primary structures (e.g. Smith-Waterman (SW), FASTA, BLAST, et al.) utilize only amino acid sequences. The SW-algorithm is the most accurate among them, i.e. it produces alignments that are most similar to the alignments obtained by superposition of protein 3D-structures. But even the SW-algorithm is unable to restore the 3D-based alignment if similarity of amino acid sequences (%id) is below 30%. We have proposed a novel alignment method that explicitly takes into account the secondary structure of the compared proteins. We have shown that it creates significantly more accurate alignments compared to SW-algorithm. In particular, for sequences with %id < 30% the average accuracy of the new method is 58% compared to 35% for SW-algorithm (the accuracy of an algorithmic sequence alignment is the part of restored position of a "golden standard" alignment obtained by superposition of corresponding 3D-structures). The accuracy of the proposed method is approximately identical both for experimental, and for theoretically predicted secondary structures. Thus the method can be applied for alignment of protein sequences even if protein 3D-structure is unknown. The program is available at ftp://194.149.64.196/STRUSWER/.     

The PSSH database of alignments between protein sequences and tertiary structures

We introduce the PSSH ('Protein Sequence-to-Structure Homologies') database derived from HSSP2, an improved version of the HSSP ('Homology-derived Secondary Structure of Proteins') database [Dodge et al. (1998) Nucleic Acids Res., 26, 313-315]. Whereas each HSSP entry lists all protein sequences related to a given 3D structure, PSSH is the 'inverse', with each entry listing all structures related to a given sequence. In addition, we introduce two other derived databases: HSSPchain, in which each entry lists all sequences related to a given PDB chain, and HSSPalign, in which each entry gives details of one sequence aligned onto one PDB chain. This re-organization makes it easier to navigate from sequence to structure, and to map sequence features onto 3D structures. Currently (September 2002), PSSH provides structural information for over 400 000 protein sequences, covering 48% of SWALL and 61% of SWISS-PROT sequences; HSSPchain provides sequence information for over 25 000 PDB chains, and HSSPalign gives over 14 million sequence-to-structure alignments. The databases can be accessed via SRS 3D, an extension to the SRS system, at http://srs3d.ebi.ac.uk/.     

A database and tools for 3-D protein structure comparison and alignment using the Combinatorial Extension (CE) algorithm

The database reported here is derived using the Combinatorial Extension (CE) algorithm which compares pairs of protein polypeptide chains and provides a list of structurally similar proteins along with their structure alignments. Using CE, structure-structure alignments can provide insights into biological function. When a protein of known function is shown to be structurally similar to a protein of unknown function, a relationship might be inferred; a relationship not necessarily detectable from sequence comparison alone. Establishing structure-structure relationships in this way is of great importance as we enter an era of structural genomics where there is a likelihood of an increasing number of structures with unknown functions being determined. Thus the CE database is an example of a useful tool in the annotation of protein structures of unknown function. Comparisons can be performed on the complete PDB or on a structurally representative subset of proteins. The source protein(s) can be from the PDB (updated monthly) or uploaded by the user. CE provides sequence alignments resulting from structural alignments and Cartesian coordinates for the aligned structures, which may be analyzed using the supplied Compare3D Java applet, or downloaded for further local analysis. Searches can be run from the CE web site, http://cl.sdsc.edu/ce.html, or the database and software downloaded from the site for local use.     

The ProDom database of protein domain families.

The ProDom database contains protein domain families generated from the SWISS-PROT database by automated sequence comparisons. It can be searched on the World Wide Web (http://protein.toulouse.inra. fr/prodom.html ) or by E-mail (prodom@toulouse.inra.fr) to study domain arrangements within known families or new proteins. Strong emphasis has been put on the graphical user interface which allows for interactive analysis of protein homology relationships. Recent improvements to the server include: ProDom search by keyword; links to PROSITE and PDB entries; more sensitive ProDom similarity search with BLAST or WU-BLAST; alignments of query sequences with homologous ProDom domain families; and links to the SWISS-MODEL server (http: //www.expasy.ch/swissmod/SWISS-MODEL.html ) for homology based 3-D domain modelling where possible.     

Simple sequences are rare in the Protein Data Bank

A simple sequence is abundant in the proteins that have been sequenced to date. But unusual protein features, such as a simple sequence, are not present in the same high frequency within structural databases. A subset of these simple sequences, a group with a highly repetitive nature has been shown to be abundant in eukaryotes but not in prokaryotes. In this study, an examination of the eukaryotic proteins in the Protein Data Bank (PDB) has revealed a large deficiency of low complexity, highly repetitive protein repeats. Through simulated databases of similar samples of eukaryotic proteins taken from the National Center for Biotechnology Information (NCBI) database, it is shown that the PDB contains a significantly less highly repetitive, simple sequence than artificial databases of similar composition randomly derived from NCBI. When the structural data for those few PDB sequences that did contain a highly repetitive simple sequence is examined in detail, it is found that in most cases the tertiary structure is unknown for the regions consisting of a simple sequence. This lack of a simple sequence both in the PDB database and in the structural information suggests that this type of simple sequence may produce disordered structures that make structural characterization difficult.     

Increasing Sequence Search Sensitivity with Transitive Alignments

Sequence alignment is an important bioinformatics tool for identifying homology, but searching against the full set of available sequences is likely to result in many hits to poorly annotated sequences providing very little information. Consequently, we often want alignments against a specific subset of sequences: for instance, we are looking for sequences from a particular species, sequences that have known 3d-structures, sequences that have a reliable (curated) function annotation, and so on. Although such subset databases are readily available, they only represent a small fraction of all sequences. Thus, the likelihood of finding close homologs for query sequences is smaller, and the alignments will in general have lower scores. This makes it difficult to distinguish hits to homologous sequences from random hits to unrelated sequences. Here, we propose a method that addresses this problem by first aligning query sequences against a large database representing the corpus of known sequences, and then constructing indirect (or transitive) alignments by combining the results with alignments from the large database against the desired target database. We compare the results to direct pairwise alignments, and show that our method gives us higher sensitivity alignments against the target database.     

Protein-protein complex structure predictions by multimeric threading and template recombination

The total number of protein-protein complex structures currently available in the Protein Data Bank (PDB) is six times smaller than the total number of tertiary structures in the PDB, which limits the power of homology-based approaches to complex structure modeling. We present a threading-recombination approach, COTH, to boost the protein complex structure library by combining tertiary structure templates with complex alignments. The query sequences are first aligned to complex templates using a modified dynamic programming algorithm, guided by ab initio binding-site predictions. The monomer alignments are then shifted to the multimeric template framework by structural alignments. COTH was tested on 500 nonhomologous dimeric proteins, which can successfully detect correct templates for 50% of the cases after homologous templates are excluded, which significantly outperforms conventional homology modeling algorithms. It also shows a higher accuracy in interface modeling than rigid-body docking of unbound structures from ZDOCK although with lower coverage. These data demonstrate new avenues to model complex structures from nonhomologous templates.     

The ASTRAL compendium for protein structure and sequence analysis

The ASTRAL compendium provides several databases and tools to aid in the analysis of protein structures, particularly through the use of their sequences. The SPACI scores included in the system summarize the overall characteristics of a protein structure. A structural alignments database indicates residue equivalencies in superimposed protein domain structures. The PDB sequence-map files provide a linkage between the amino acid sequence of the molecule studied (SEQRES records in a database entry) and the sequence of the atoms experimentally observed in the structure (ATOM records). These maps are combined with information in the SCOPdatabase to provide sequences of protein domains. Selected subsets of the domain database, with varying degrees of similarity measured in several different ways, are also available. ASTRALmay be accessed at http://astral.stanford.edu/     

Large-scale comparison of protein sequence alignment algorithms with structure alignments

Sequence alignment programs such as BLAST and PSI-BLAST are used routinely in pairwise, profile-based, or intermediate-sequence-search (ISS) methods to detect remote homologies for the purposes of fold assignment and comparative modeling. Yet, the sequence alignment quality of these methods at low sequence identity is not known. We have used the CE structure alignment program (Shindyalov and Bourne, Prot Eng 1998;11:739) to derive sequence alignments for all superfamily and family-level related proteins in the SCOP domain database. CE aligns structures and their sequences based on distances within each protein, rather than on interprotein distances. We compared BLAST, PSI-BLAST, CLUSTALW, and ISS alignments with the CE structural alignments. We found that global alignments with CLUSTALW were very poor at low sequence identity (<25%), as judged by the CE alignments. We used PSI-BLAST to search the nonredundant sequence database (nr) with every sequence in SCOP using up to four iterations. The resulting matrix was used to search a database of SCOP sequences. PSI-BLAST is only slightly better than BLAST in alignment accuracy on a per-residue basis, but PSI-BLAST matrix alignments are much longer than BLAST's, and so align correctly a larger fraction of the total number of aligned residues in the structure alignments. Any two SCOP sequences in the same superfamily that shared a hit or hits in the nr PSI-BLAST searches were identified as linked by the shared intermediate sequence. We examined the quality of the longest SCOP-query/ SCOP-hit alignment via an intermediate sequence, and found that ISS produced longer alignments than PSI-BLAST searches alone, of nearly comparable per-residue quality. At 10-15% sequence identity, BLAST correctly aligns 28%, PSI-BLAST 40%, and ISS 46% of residues according to the structure alignments. We also compared CE structure alignments with FSSP structure alignments generated by the DALI program. In contrast to the sequence methods, CE and structure alignments from the FSSP database identically align 75% of residue pairs at the 10-15% level of sequence identity, indicating that there is substantial room for improvement in these sequence alignment methods. BLAST produced alignments for 8% of the 10,665 nonimmunoglobulin SCOP superfamily sequence pairs (nearly all <25% sequence identity), PSI-BLAST matched 17% and the double-PSI-BLAST ISS method aligned 38% with E-values <10.0. The results indicate that intermediate sequences may be useful not only in fold assignment but also in achieving more complete sequence alignments for comparative modeling.