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PubMed2000

Iterative sequence/secondary structure search for protein homologs: comparison with amino acid sequence alignments and application to fold recognition in genome databases.

MOTIVATION: Sequence alignment techniques have been developed into extremely powerful tools for identifying the folding families and function of proteins in newly sequenced genomes. For a sufficiently low sequence identity it is necessary to incorporate additional structural information to positively detect homologous proteins. We have carried out an extensive analysis of the effectiveness of incorporating secondary structure information directly into the alignments for fold recognition and identification of distant protein homologs. A secondary structure similarity matrix based on a database of three-dimensionally aligned proteins was first constructed. An iterative application of dynamic programming was used which incorporates linear combinations of amino acid and secondary structure sequence similarity scores. Initially, only primary sequence information is used. Subsequently contributions from secondary structure are phased in and new homologous proteins are positively identified if their scores are consistent with the predetermined error rate. RESULTS: We used the SCOP40 database, where only PDB sequences that have 40% homology or less are included, to calibrate homology detection by the combined amino acid and secondary structure sequence alignments. Combining predicted secondary structure with sequence information results in a 8-15% increase in homology detection within SCOP40 relative to the pairwise alignments using only amino acid sequence data at an error rate of 0.01 errors per query; a 35% increase is observed when the actual secondary structure sequences are used. Incorporating predicted secondary structure information in the analysis of six small genomes yields an improvement in the homology detection of approximately 20% over SSEARCH pairwise alignments, but no improvement in the total number of homologs detected over PSI-BLAST, at an error rate of 0.01 errors per query. However, because the pairwise alignments based on combinations of amino acid and secondary structure similarity are different from those produced by PSI-BLAST and the error rates can be calibrated, it is possible to combine the results of both searches. An additional 25% relative improvement in the number of genes identified at an error rate of 0.01 is observed when the data is pooled in this way. Similarly for the SCOP40 dataset, PSI-BLAST detected 15% of all possible homologs, whereas the pooled results increased the total number of homologs detected to 19%. These results are compared with recent reports of homology detection using sequence profiling methods. AVAILABILITY: Secondary structure alignment homepage at http://lutece.rutgers.edu/ssas CONTACT: anders@rutchem.rutgers.edu; ronlevy@lutece.rutgers.edu SUPPLEMENTARY INFORMATION: Genome sequence/structure alignment results at http://lutece.rutgers.edu/ss_fold_predictions.

Algorithms↗
PubMed1992

Towards an automatic method of predicting protein structure by homology: an evaluation of suboptimal sequence alignments.

A major problem in predicting protein structure by homology modelling is that the sequence alignment from which the model is built may not be the best one in terms of the correct equivalencing of residues assessed by structural or functional criteria. A useful strategy is to generate and examine a number of suboptimal alignments as better alignments can often be found away from the optimal. A procedure to filter rapidly suboptimal alignments based on measurement of core volumes and packing pair potentials is investigated. The approach is benchmarked on three pairs of sequences which are non-trivial to align correctly, namely two immunoglobulin domains, plastocyanin with azurin and two distant globin sequences. It is shown to be useful to reduce a large ensemble of possible alignments down to a few which correspond more closely to the correct (structure based) alignment.

Algorithms↗
PubMed1991

Database of homology-derived protein structures and the structural meaning of sequence alignment.

The database of known protein three-dimensional structures can be significantly increased by the use of sequence homology, based on the following observations. (1) The database of known sequences, currently at more than 12,000 proteins, is two orders of magnitude larger than the database of known structures. (2) The currently most powerful method of predicting protein structures is model building by homology. (3) Structural homology can be inferred from the level of sequence similarity. (4) The threshold of sequence similarity sufficient for structural homology depends strongly on the length of the alignment. Here, we first quantify the relation between sequence similarity, structure similarity, and alignment length by an exhaustive survey of alignments between proteins of known structure and report a homology threshold curve as a function of alignment length. We then produce a database of homology-derived secondary structure of proteins (HSSP) by aligning to each protein of known structure all sequences deemed homologous on the basis of the threshold curve. For each known protein structure, the derived database contains the aligned sequences, secondary structure, sequence variability, and sequence profile. Tertiary structures of the aligned sequences are implied, but not modeled explicitly. The database effectively increases the number of known protein structures by a factor of five to more than 1800. The results may be useful in assessing the structural significance of matches in sequence database searches, in deriving preferences and patterns for structure prediction, in elucidating the structural role of conserved residues, and in modeling three-dimensional detail by homology.

Amino Acid Sequence↗
PubMed1997

Visible volume: a robust measure for protein structure characterization.

We propose a new characterization of protein structure based on the natural tetrahedral geometry of the beta-carbon and a new geometric measure of structural similarity, called visible volume. In our model, the side-chains are replaced by an ideal tetrahedron, the orientation of which is fixed with respect to the backbone and corresponds to the preferred rotamer directions. Visible volume is a measure of the non-occluded empty space surrounding each residue position after the side-chains have been removed. It is a robust, parameter-free, locally computed quantity that accounts for many of the spatial constraints that are of relevance to the corresponding position in the native structure. When computing visible volume, we ignore the nature of both the residue observed at each side and the ones surrounding it. We focus instead on the space that, together, these residues could occupy. By doing so, we are able to quantify a new kind of invariance beyond the apparent variations within protein families, namely, the conservation of the physical space available at structurally equivalent positions for side-chain packing. Corresponding positions in native structures are likely to be of interest in protein structure prediction, protein design, and homology modeling. Visible volume is related to the degree of exposure of a residue position and to the actual rotamers in native proteins. Here, we discuss the properties of this new measure, namely, its robustness with respect to both crystallographic uncertainties and naturally occurring variations in atomic coordinates, and the remarkable fact that it is essentially independent of the choice of the parameters used in calculating it. We also show how visible volume can be used to align protein structures, to identify structurally equivalent positions that are conserved in a family of proteins, and to single out positions in a protein that are likely to be of biological interest. These properties qualify visible volume as a powerful tool in a variety of applications, from the detailed analysis of protein structure to homology modeling, protein structural alignment, and the definition of better scoring functions for threading purposes.

Animals↗
PubMedDate not supplied

Cloning and recombinant expression of a barred sand bass (Paralabrax nebulifer) cDNA. The encoded protein displays structural homology and immunological crossreactivity to human complement/cofactor related plasma proteins.

A new cofactor related cDNA in the bony fish Paralablax nebulifer, (barred sand bass) was isolated from a sand bass liver cDNA library. The clone (c71) is 1040 bp in size and the predicted translation product of 204 amino acids contains a hydrophobic signal peptide, which is followed by a region of three short consensus repeats (SCRs). The three SCRs display high homology to SCRs of the 110 kDa chain of the sand bass plasma cofactor protein, and to a lesser degree to human complement factor H related protein 3 (FHR-3) and to human factor H. Recombinant expression of the c71 cDNA in the baculovirus system shows a product of an apparent molecular mass of 27 kDa, which is secreted and glycosylated. It also contains a His-tag for purification purposes. Removal of the His-tag yields a 24 kDa protein, and deglycosylation further reduces the molecular mass to 21 kDa. This size is in agreement with the calculated molecular mass based on amino acid composition. The sand bass SBCFR-1 protein is immunologically related to the human complement proteins, factor H and factor H-related protein 3. The recombinantly expressed protein reacted with antisera against the human FHR-3 protein and SCRs 19-20 of human factor H. The presence of SCR-containing proteins in sand bass plasma and their structural and immunological homology to human FHR-3 and factor H suggests for a common function between these evolutionary related proteins.

Amino Acid Sequence↗
PubMed2004

Consensus alignment server for reliable comparative modeling with distant templates.

Consensus is a server developed to produce high-quality alignments for comparative modeling, and to identify the alignment regions reliable for copying from a given template. This is accomplished even when target-template sequence identity is as low as 5%. Combining the output from five different alignment methods, the server produces a consensus alignment, with a reliability measure indicated for each position and a prediction of the regions suitable for modeling. Models built using the server predictions are typically within 3 A rms deviations from the crystal structure. Users can upload a target protein sequence and specify a template (PDB code); if no template is given, the server will search for one. The method has been validated on a large set of homologous protein structure pairs. The Consensus server should prove useful for modelers for whom the structural reliability of the model is critical in their applications. It is currently available at http://structure.bu.edu/cgi-bin/consensus/consensus.cgi.

Algorithms↗
PubMed1992

cDNA sequence analysis of CP94: rat lens fiber cell beaded-filament structural protein shows homology to cytokeratins.

To study the molecular structure of the gene responsible for a lens fiber cell beaded-filament structural protein of 94kDa (CP94), we isolated its specific cDNA from a rat lens cDNA library by use of anti-mouse CP94 antiserum. The expressed fusion protein kept the epitopes specific against anti-chick CP97 as well as anti-mouse CP94 antibody, and the size was estimated as 190-200kDa, indicating that the cDNA insert of the clone seemed to encode a polypeptide with 80-90kDa in appearance. Northern analysis indicated that CP94 mRNA is expressed only in the lens, and not in the brain, skin, heart, kidney, lung, and liver, and the size was estimated to 2.1-2.3kb. In a lens of inherited microphthalmic mouse, Elo, a trace amount of mRNA with the size closely similar to that of rat mRNA was observed. The entire compiled sequence (1,873bp) showed an open reading frame covering the sequence of 533 amino acids totalling 58,857Da. No sequence homologous to the entire CP94 was found among the entries of any nucleotide and amino acid sequence databases; but with respect to a limited amino acid sequence of N-side region of CP94, a significant homology with cytokeratins was found.

Amino Acid Sequence↗
PubMed2004

Sequence patterns derived from the automated prediction of functional residues in structurally-aligned homologous protein families.

MOTIVATION: Most proteins have evolved to perform specific functions that are dependent on the adoption of well-defined three-dimensional (3D) structures. Specific patterns of conserved residues in amino acid sequences of divergently evolved proteins are frequently observed; these may reflect evolutionary restraints arising both from the need to maintain tertiary structure and the requirement to conserve residues more directly involved in function. Databases of such sequence patterns are valuable in identifying distant homologues, in predicting function and in the study of evolution. RESULTS: A fully automated database of protein sequence patterns, Functional Protein Sequence Pattern Database (FPSPD), has been derived from the analysis of the conserved residues that are predicted to be functional in structurally aligned homologous families in the HOMSTRAD database. Environment-dependent substitution tables, evolutionary trace analysis, solvent accessibility calculations and 3D-structures were used to obtain the FPSPD. The method yielded 3584 patterns that are considered functional and 3049 patterns that are probably functional. FPSPD could be useful for assigning a protein to a homologous superfamily and thereby providing clues about function. AVAILABILITY: FPSPD is available at http://www-cryst.bioc.cam.ac.uk/~fpspd/

Algorithms↗
PubMed2001

Langat virus M protein is structurally homologous to prM.

Langat (LGT) virus M protein has been generated in a recombinant system. Antiserum raised against the LGT virus M protein neutralizes tick-borne encephalitis serocomplex flaviviruses but not mosquito-borne flaviviruses, indicating that the M protein is exposed on the surface of virions. The antiserum recognizes intracellular LGT virus prM/M and binds to prM and M in Western blots of whole-cell lysates and purified virus, respectively. These data suggest that the prM and M proteins are structurally similar under native conditions and support the hypothesis that the "pr" portion of prM facilitates proper folding of the M protein for expression on the virion surface.

Amino Acid Sequence↗
PubMed1999

Addressing the issue of sequence-to-structure alignments in comparative modeling of CASP3 target proteins.

During a blind protein structure prediction experiment (the third round of the Critical Assessment of Techniques for Protein Structure Prediction; URL http://PredictionCenter.llnl.gov/casp3/) , four target proteins, T0047, T0048, T0055, and T0070, were modeled by comparison. These proteins display 62%, 29%, 24%, and 19% sequence identity, respectively, to the structurally homologous proteins most similar in sequence. The issue of sequence-to-structure alignment in cases of low sequence homology was the main emphasis. Selection of alignments was made by constructing and evaluating three-dimensional models based on series of samples produced mainly by automatic multiple sequence alignments. Sequence-to-structure alignments were correct in all but two regions, in which significant changes in target structures compared with related proteins were the source of errors. Template choice is an important determinant of model quality, and a correct selection was made of a lower homology template for modeling of T0070; however, in the case of T0055, a template with 8% greater sequence homology proved deceptive. Loops and some ungapped template regions were assigned conformations taken from other proteins. Using fragments from homologous structures led to improvement over template backbone more often than cases in which nonhomologous structures were the source. The results also indicate that side-chain prediction accuracy depends not only on sequence similarity but also on accuracy of the backbone.

Algorithms↗
PubMed1996

Determination of the primary structure of homologous proteins by sequence analysis of peptide mixtures.

We propose a rapid method to determine the primary structure of a protein knowing the sequence of a homologous protein. The method consists in submitting both the reduced and alkylated proteins to an enzymatic or chemical hydrolysis and performing the sequence analysis of the peptide mixtures. The assessment of the unknown sequence and the degree of identify of the two proteins are reached by comparing the two sequence analyses. The sequences of all the possible peptides present in the two mixtures are reconstructed and the differences in the two sequences are determined. If necessary, the differences can be confirmed by performing a mass spectrometric analysis of the two mixtures. We used this procedure on two homologous proteins of known sequence to furnish an application example of the method.

Amino Acid Sequence↗
PubMed2006

Using protein homology models for structure-based studies: approaches to model refinement.

Homology modeling is a computational methodology to assign a 3-D structure to a target protein when experimental data are not available. The methodology uses another protein with a known structure that shares some sequence identity with the target as a template. The crudest approach is to thread the target protein backbone atoms over the backbone atoms of the template protein, but necessary refinement methods are needed to produce realistic models. In this mini-review anchored within the scope of drug design, we show the validity of using homology models of proteins in the discovery of binders for potential therapeutic targets. We also report several different approaches to homology model refinement, going from very simple to the most elaborate. Results show that refinement approaches are system dependent and that more elaborate methodologies do not always correlate with better performances from built homology models.

Computational Biology↗
PubMed2001

Identification of homology in protein structure classification.

Structural biology and structural genomics are expected to produce many three-dimensional protein structures in the near future. Each new structure raises questions about its function and evolution. Correct functional and evolutionary classification of a new structure is difficult for distantly related proteins and error-prone using simple statistical scores based on sequence or structure similarity. Here we present an accurate numerical method for the identification of evolutionary relationships (homology). The method is based on the principle that natural selection maintains structural and functional continuity within a diverging protein family. The problem of different rates of structural divergence between different families is solved by first using structural similarities to produce a global map of folds in protein space and then further subdividing fold neighborhoods into superfamilies based on functional similarities. In a validation test against a classification by human experts (SCOP), 77% of homologous pairs were identified with 92% reliability. The method is fully automated, allowing fast, self-consistent and complete classification of large numbers of protein structures. In particular, the discrimination between analogy and homology of close structural neighbors will lead to functional predictions while avoiding overprediction.

Automation↗
PubMed2006

Coverage of whole proteome by structural genomics observed through protein homology modeling database.

We have been developing FAMSBASE, a protein homology-modeling database of whole ORFs predicted from genome sequences. The latest update of FAMSBASE ( http://daisy.nagahama-i-bio.ac.jp/Famsbase/ ), which is based on the protein three-dimensional (3D) structures released by November 2003, contains modeled 3D structures for 368,724 open reading frames (ORFs) derived from genomes of 276 species, namely 17 archaebacterial, 130 eubacterial, 18 eukaryotic and 111 phage genomes. Those 276 genomes are predicted to have 734,193 ORFs in total and the current FAMSBASE contains protein 3D structure of approximately 50% of the ORF products. However, cases that a modeled 3D structure covers the whole part of an ORF product are rare. When portion of an ORF with 3D structure is compared in three kingdoms of life, in archaebacteria and eubacteria, approximately 60% of the ORFs have modeled 3D structures covering almost the entire amino acid sequences, however, the percentage falls to about 30% in eukaryotes. When annual differences in the number of ORFs with modeled 3D structure are calculated, the fraction of modeled 3D structures of soluble protein for archaebacteria is increased by 5%, and that for eubacteria by 7% in the last 3 years. Assuming that this rate would be maintained and that determination of 3D structures for predicted disordered regions is unattainable, whole soluble protein model structures of prokaryotes without the putative disordered regions will be in hand within 15 years. For eukaryotic proteins, they will be in hand within 25 years. The 3D structures we will have at those times are not the 3D structure of the entire proteins encoded in single ORFs, but the 3D structures of separate structural domains. Measuring or predicting spatial arrangements of structural domains in an ORF will then be a coming issue of structural genomics.

Amino Acid Sequence↗
PubMed2006

SISYPHUS--structural alignments for proteins with non-trivial relationships.

With the increasing amount of structural data, the number of homologous protein structures bearing topological irregularities is steadily growing. These include proteins with circular permutations, segment-swapping, context-dependent folding or chameleon sequences that can adopt alternative secondary structures. Their non-trivial structural relationships are readily identified during expert analysis but their automatic identification using the existing computational tools still remains difficult or impossible. Such non-trivial cases of protein relationships are known to pose a problem to multiple alignment algorithms and to impede comparative modeling studies. They support a new emerging concept of evolutionary changeable protein fold, which creates practical difficulties for the hierarchical classifications of protein structures.To facilitate the understanding of, and to provide a comprehensive annotation of proteins with such non-trivial structural relationships we have created SISYPHUS ([Sigmaomeganuphiomicronzeta]--in Greek crafty), a compendium to the SCOP database. The SISYPHUS database contains a collection of manually curated structural alignments and their inter-relationships. The multiple alignments are constructed for protein structural regions that range from oligomeric biological units, or individual domains to fragments of different size. The SISYPHUS multiple alignments are displayed with SPICE, a browser that provides an integrated view of protein sequences, structures and their annotations. The database is available from http://sisyphus.mrc-cpe.cam.ac.uk.

Databases, Protein↗
PubMed2000

Use of residue pairs in protein sequence-sequence and sequence-structure alignments.

Two new sets of scoring matrices are introduced: H2 for the protein sequence comparison and T2 for the protein sequence-structure correlation. Each element of H2 or T2 measures the frequency with which a pair of amino acid types in one protein, k-residues apart in the sequence, is aligned with another pair of residues, of given amino acid types (for H2) or in given structural states (for T2), in other structurally homologous proteins. There are four types, corresponding to the k-values of 1 to 4, for both H2 and T2. These matrices were set up using a large number of structurally homologous protein pairs, with little sequence homology between the pair, that were recently generated using the structure comparison program SHEBA. The two scoring matrices were incorporated into the main body of the sequence alignment program SSEARCH in the FASTA package and tested in a fold recognition setting in which a set of 107 test sequences were aligned to each of a panel of 3,539 domains that represent all known protein structures. Six procedures were tested; the straight Smith-Waterman (SW) and FASTA procedures, which used the Blosum62 single residue type substitution matrix; BLAST and PSI-BLAST procedures, which also used the Blosum62 matrix; PASH, which used Blosum62 and H2 matrices; and PASSC, which used Blosum62, H2, and T2 matrices. All procedures gave similar results when the probe and target sequences had greater than 30% sequence identity. However, when the sequence identity was below 30%, a similar structure could be found for more sequences using PASSC than using any other procedure. PASH and PSI-BLAST gave the next best results.

Algorithms↗
PubMed1994

Use of amino acid environment-dependent substitution tables and conformational propensities in structure prediction from aligned sequences of homologous proteins. II. Secondary structures.

A three-step method is presented to predict secondary structures of proteins, by utilizing aligned sequences of homologous proteins. Mean propensities and amino acid substitution patterns at a given site in the aligned sequences are first evaluated for four conformational states (i.e. alpha-helix, beta-strand, buried coil and exposed coil). Capping rules are applied in order to define boundaries of the secondary-structure segments more precisely. In the second step beta-strand is predicted by searching regions predicted as coil for the two patterns characteristic of alternating and fully buried beta-strands. The complete sequences of the solvent-accessibility classes predicted by substitution tables and propensities are also searched using Fourier transform methods for alpha-helical periodicity. After applying capping rules, the alpha-helices and beta-strands predicted in the second step replace, where appropriate, the conformational states predicted in the first step. Finally, in the third step, if one of the four conformational states is assigned to the residues at an equivalent site of aligned sequences in more than a given fraction of the proteins, such a state is reassigned to all the residues at that site. The method is applied to 13 protein families, which contain four folding types, alpha, beta, alpha/beta and alpha + beta. The accuracy of the prediction ranges from 60 to 79% (mean percentage over the 13 families is 69%). For comparison the Garnier-Osguthorpe-Robson (GOR) method is also applied to them. Although the mean prediction accuracy for the GOR method, 58%, can be improved to 63% by applying the second and third steps in this method, there remain four families with less than 55% accuracy. The mean accuracy is relatively higher and poor predictions are reduced in this method.

Amino Acid Sequence↗