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A simple extension of the Needleman and Wunsch algorithm for aligning pairs of protein sequences allows it to be used for the efficient generation of very large multiple-sequence alignments whose members are similar. This technique could have applications in a broad range of high-volume genomics projects.
Modeling the inherent flexibility of the protein backbone as part of computational protein design is necessary to capture the behavior of real proteins and is a prerequisite for the accurate exploration of protein sequence space. We present the results of a broad exploration of sequence space, with backbone flexibility, through a novel approach: large-scale protein design to structural ensembles. A distributed computing architecture has allowed us to generate hundreds of thousands of diverse sequences for a set of 253 naturally occurring proteins, allowing exciting insights into the nature of protein sequence space. Designing to a structural ensemble produces a much greater diversity of sequences than previous studies have reported, and homology searches using profiles derived from the designed sequences against the Protein Data Bank show that the relevance and quality of the sequences is not diminished. The designed sequences have greater overall diversity than corresponding natural sequence alignments, and no direct correlations are seen between the diversity of natural sequence alignments and the diversity of the corresponding designed sequences. For structures in the same fold, the sequence entropies of the designed sequences cluster together tightly. This tight clustering of sequence entropies within a fold and the separation of sequence entropy distributions for different folds suggest that the diversity of designed sequences is primarily determined by a structure's overall fold, and that the designability principle postulated from studies of simple models holds in real proteins. This has important implications for experimental protein design and engineering, as well as providing insight into protein evolution.
A statistical method of comparative sequence analysis that combines horizontal and vertical correlations among aligned sequences is introduced. It is based on the analysis mainly of quartet combinations of sequences considered as geometric configurations in sequence space. Numerical invariants related to relative internal segment lengths are assigned to each such configuration and statistical averages of these invariants are established. They are used for internal calibration of the topology of divergence and for quantitative determination of the noise level. Comparison of computer simulations with experimental data reveals the high sensitivity of assignment of basic topologies even if much randomized. In addition, these procedures are checked by vertical analysis of the aligned sequences to allow the study of divergences with positionally varying substitution probabilities.
MOTIVATION: JOY is a program to annotate protein sequence alignments with three-dimensional (3D) structural features. It was developed to display 3D structural information in a sequence alignment and to help understand the conservation of amino acids in their specific local environments. RESULTS: : The JOY representation now constitutes an essential part of the two databases of protein structure alignments: HOMSTRAD (http://www-cryst.bioc.cam.ac.uk/homstrad ) and CAMPASS (http://www-cryst.bioc.cam.ac. uk/campass). It has also been successfully used for identifying distant evolutionary relationships. AVAILABILITY: The program can be obtained via anonymous ftp from torsa.bioc.cam.ac.uk from the directory /pub/joy/. The address for the JOY server is http://www-cryst.bioc.cam.ac.uk/cgi-bin/joy.cgi. CONTACT: kenji@cryst.bioc.cam.ac.uk
Three major improvements to a previously described method for automatic protein structure comparison are described. First, a limit to translations for the rigid-body superposition is now assigned according to the dimensions of the structures being compared. Second, examination of the effect of the gap penalty on the derivation of a sequence alignment corresponding to a given structure superposition has led to a method to evaluate alternative structure-based sequence alignments. Third, the pairwise procedure has been generalized to multiple structure alignment. This implementation of rigid-body superposition can recognize well documented distant relationships which hitherto have required consideration of additional features and properties as well as those relationships between proteins of different sizes. A much larger common scaffold or framework between six globins can be extracted than that obtained using a standard algorithm for multiple structure superposition.
Protein blocks consist of multiply aligned sequence segments that correspond to the most highly conserved regions of protein families. Typically, a set of related proteins has more than one region in common and their relationship can be represented as a series of ungapped blocks separated by unaligned regions. Blockmaker is an automated system available by electronic mail (blockmaker@howard.fhcrc.org) and the World Wide Web (http://www.blocks.fhcrc.org4) that finds blocks in a group of related protein sequences submitted by the user. It adapts and extends existing algorithms to make them useful to biologists looking for conserved regions in a group of related proteins sequences. Two sets of blocks are returned, one in which candidate blocks are detected using the MOTIF algorithm and the other using a Gibbs sampler algorithm that has been adapted for full automation. This use of two block-finding methods based on completely different principles provides a 'reality check,' whereby a block detected by both methods is considered to be correct. Resulting blocks can be displayed using the information-based 'sequence logo' method, adapted to incorporate sequence weights, which provides an intuitive visual description of both the residue and the conservation information at each position. Blocks generated by this system are useful in diverse applications, such as searching databases and designing degenerate PCR primers. As an example, blocks made from amino acid sequences related to Caenorhabditis elegans Tc1 transposase were used to search GenBank, revealing that several fish and amphibian genomic sequences harbor previously unreported Tc1 homologs.
BACKGROUND: Structure-dependent substitution matrices increase the accuracy of sequence alignments when the 3D structure of one sequence is known, and are successful e.g. in fold recognition. We propose a new automated method, EvDTree, based on a decision tree algorithm, for automatic derivation of amino acid substitution probabilities from a set of sequence-structure alignments. The main advantage over other approaches is an unbiased automatic selection of the most informative structural descriptors and associated values or thresholds. This feature allows automatic derivation of structure-dependent substitution scores for any specific set of structures, without the need to empirically determine best descriptors and parameters. RESULTS: Decision trees for residue substitutions were constructed for each residue type from sequence-structure alignments extracted from the HOMSTRAD database. For each tree cluster, environment-dependent substitution profiles were derived. The resulting structure-dependent substitution scores were assessed using a criterion based on the mean ranking of observed substitution among all possible substitutions and in sequence-structure alignments. The automatically built EvDTree substitution scores provide significantly better results than conventional matrices and similar or slightly better results than other structure-dependent matrices. EvDTree has been applied to small disulfide-rich proteins as a test case to automatically derive specific substitutions scores providing better results than non-specific substitution scores. Analyses of the decision tree classifications provide useful information on the relative importance of different structural descriptors. CONCLUSIONS: We propose a fully automatic method for the classification of structural environments and inference of structure-dependent substitution profiles. We show that this approach is more accurate than existing methods for various applications. The easy adaptation of EvDTree to any specific data set opens the way for class-specific structure-dependent substitution scores which can be used in threading-based remote homology searches.
Members of the C-type lectin/C-type lectin-like domain (CTL/CTLD) superfamily share a common fold and are involved in a variety of functions, such as generalized defense mechanisms against foreign agents, discrimination between healthy and pathogen-infected cells, and endocytosis and blood coagulation. In this work we used ConSurf, a computer program recently developed in our lab, to perform an evolutionary analysis of this superfamily in order to further identify characteristics of all or part of its members. Given a set of homologous proteins in the form of multiple sequence alignment (MSA) and an inferred phylogenetic tree, ConSurf calculates the conservation score in every alignment position, taking into account the relationships between the sequences and the physicochemical similarity between the amino acids. The scores are then color-coded onto the three-dimensional structure of one of the homologous proteins. We provide here and at http://ashtoret.tau.ac.il/ approximately sharon a detailed analysis of the conservation pattern obtained for the entire superfamily and for two subgroups of proteins: (a) 21 CTLs and (b) 11 heterodimeric CTLD toxins. We show that, in general, proteins of the superfamily have one face that is constructed mostly of conserved residues and another that is not, and we suggest that the former face is involved in binding to other proteins or domains. In the CTLs examined we detected a region of highly conserved residues, corresponding to the known calcium- and carbohydrate-binding site of the family, which is not conserved throughout the entire superfamily, and in the CTLD toxins we found a patch of highly conserved residues, corresponding to the known dimerization region of these proteins. Our analysis also detected patches of conserved residues with yet unknown function(s).
Understanding the molecular determinants of protein thermostability is of theoretical and practical importance. While numerous determinants have been suggested, no molecular feature has been judged of paramount importance, with the possible exception of ion-pair networks. The difficulty in identifying the main determinants may have been the limited structural information available on the thermostable proteins. Recently the complete genomes for mesophilic, thermophilic and hyperthermophilic organisms have been sequenced, vastly improving the potential for uncovering general trends in sequence and structure evolution related to thermostability and, thus, for isolating the more important determinants. From a comparative analysis of 20 complete genomes, we find a trend towards shortened thermophilic proteins relative to their mesophilic homologs. Moreover, sequence alignments to proteins of known structure indicate that thermophilic sequences are more likely than their mesophilic homologs to have deletions in exposed loop regions. The new genomes offer enough comparable sequences to compute meaningful statistics that point to loop deletion as a general evolutionary strategy for increasing thermostability.
Large-scale random cDNA sequencing projects have been started for several organisms and are a valuable tool for the analysis of quantitative and qualitative aspects of gene expression. However, the reliability of the obtained data is limited as most of the clones are only partially analysed on one strand. As a consequence the sequence entries derived from random cDNA sequencing projects usually comprise incomplete open reading frames. They nevertheless define complete and reliable coding sequences, if two prerequisites are fulfilled: (i) the clones encode very small proteins, and (ii) the clones have a high frequency in the cDNA-banks. The present study describes the use of cDNA databases for the identification of homologues of three low-molecular-weight subunits of the mitochondrial bc1 complex, termed the QCR6, QCR9 and QCR10 proteins. These polypeptides are only characterized for a small number of organisms, have a scarcely defined function and exhibit a low degree of structural conservation if compared between different species. Several clones were identified for each polypeptide by searches with TBLASTN using the known sequences as probes. Most of the database entries contain complete open reading frames and sequencing queries could be excluded due to the abundancy of the clones. Multiple sequence alignments are presented for all three polypeptides and consensus sequences are given which may provide a basis for the investigation of the proteins by site-directed mutagenesis.
For a sequence of colors independently evolving on a tree under a simple Markov model, we consider conditions under which the tree can be uniquely recovered from the "sequence spectrum"-the expected frequencies of the various leaf colorations. This is relevant for phylogenetic analysis (where colors represent nucleotides or amino acids; leaves represent extant taxa) as the sequence spectrum is estimated directly from a collection of aligned sequences. Allowing the rate of the evolutionary process to vary across sites is an important extension over most previous studies-we show that, given suitable restrictions on the rate distribution, the true tree (up to the placement of its root) is uniquely identified by its sequence spectrum. However, if the rate distribution is unknown and arbitrary, then, for simple models, it is possible for every tree to produce the same sequence spectrum. Hence there is a logical barrier to accurate, consistent phylogenetic inference for these models when assumptions about the rate distribution are not made. This result exploits a novel theorem on the action of polynomials with non-negative coefficients on sequences.
MOTIVATION: Most of the existing methods for genetic sequence classification are based on a computer search for homologies in nucleotide or amino acid sequences. The standard sequence alignment programs scale very poorly as the number of sequences increases or the degree of sequence identity is <30%. Some new computationally inexpensive methods based on nucleotide or amino acid compositional analysis have been proposed, but prediction results are still unsatisfactory and depend on the features chosen to represent the sequences. RESULTS: In this paper, a feature selection method based on the Gamma (or near-neighbour) test is proposed. If there is a continuous or smooth map from feature space to the classification target values, the Gamma test gives an estimate for the mean-squared error of the classification, despite the fact that one has no a priori knowledge of the smooth mapping. We can search a large space of possible feature combinations for a combination which gives a smallest estimated mean-squared error using a genetic algorithm. The method was used for feature selection and classification of the large subunits of rRNA according to RDP (Ribosomal Database Project) phylogenetic classes. The sequences were represented by dinucleotide frequency distribution. The nearest-neighbour criterion has been used to estimate the predictive accuracy of the classification based on the selected features. For examples discussed, we found that the classification according to the first nearest neighbour is correct for 80% of the test samples. If we consider the set of the 10 nearest neighbours, then 94% of the test samples are classified correctly. AVAILABILITY: The principal novel component of this method is the Gamma test and this can be downloaded compiled for Unix Sun 4, Windows 95 and MS-DOS from http://www.cs.cf.ac.uk/ec/ CONTACT: s.margetts@cs.cf.ac.uk
We herein present and discuss the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server is operational around the clock and provides access to a variety of methods that have been published by the group's members and collaborators. The available tools correspond to applications ranging from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences and the interactive annotation of amino acid sequences. Additionally, annotations for more than 70 archaeal, bacterial, eukaryotic and viral genomes are available on-line and can be searched interactively. The tools and code bundles can be accessed beginning at http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/.
A comparison has been made between the homology and hydrophobicity profiles of six interleukin amino acid sequences and that of the human interleukin 1 beta (IL-1 beta) for which a crystal structure exists. The resulting sequence alignment was used to build model structures for the sequences for three IL-1 alpha, two IL-1 beta and an interleukin receptor antagonist. Analysis of these structures demonstrates that the interleukin molecule has a strong electric dipole which is generated by the topological position of the amino acids in the sequence. Electrostatic surface calculations implicate a particular residues (Lys145) as being fundamental to interleukin activity and this supports site-directed mutation evidence that this residue is required for activity.
Intrusion detection systems (IDS) attempt to address the vulnerability of computer-based systems for abuse by insiders and to penetration by outsiders. An IDS is required to examine an enormous amount of data generated by computer networks to assist in the abuse detection process. Thus, there is a need to develop automated tools that address these requirements to assist system operators in the detection of violations of existing security policies. In this research, an automated IDS is proposed for insider threats in a distributed system. The proposed IDS functions as an anomaly detector for insider system operations based on the analysis of the system's log files. The approach integrates dynamic programming and adaptive resonance theory (ART1) clustering. The integrated approach aligns sequences of log events with prototypical sequences of events for performing tasks and classifies the aligned sequences for intrusion detection. The system examined for this research is a Boots System for controlling the movement of boots from one place to another under specific security restrictions related to the boot orders. We present the proposed model, the results achieved and the analysis of an implemented prototype.
Multiple sequence alignment among 12 complete SARS coronavirus (SARS-CoV) sequences reveals that the major parts of 29708 b of the genomes have 99.82% identical bases. Forty two nucleotide mismatches were found in addition to the five and six gaps in two genomes. Among them, 28 mismatches result in changes of amino acid in the encoded proteins. Analysis of the changes implies possible effect on the Spike and Membrane protein of the virus, while most of the other changes seem not very significant to alter the structure and function of the proteins. These results have been released on the anti-sars web site maintained by the Centre of Bioinformatics, Peking University (antisars.cbi.pku.edu.cn) and may be of help for further experimental study.
A new method for the de novo prediction of protein structures at low resolution has been developed. Starting from a multiple sequence alignment, protein secondary structure is predicted, and only those topological elements with high reliability are selected. Then, the multiple sequence alignment and the secondary structure prediction are combined to predict side chain contacts. Such contact map prediction is carried out in two stages. First, an analysis of correlated mutations is carried out to identify pairs of topological elements of secondary structure which are in contact. Then, inverse folding is used to select compatible fragments in contact, thereby enriching the number and identity of predicted side chain contacts. The final outcome of the procedure is a set of noisy secondary and tertiary restraints. These are used as a restrained potential in a Monte Carlo simulation of simplified protein models driven by statistical potentials. Low energy structures are then searched for by using simulated annealing techniques. Implementation of the restraints is carried out so as to take into account of their low resolution. Using this procedure, it has been possible to predict de novo the structure of three very different protein topologies: an alpha/beta protein, the bovine pancreatic trypsin inhibitor (6pti), an alpha-helical protein, calbindin (3icb), and an all beta- protein, the SH3 domain of spectrin (1shg). In all cases, low resolution folds have been obtained with a root mean square deviation (RMSD) of 4.5-5.5 A with respect to the native structure. Some misfolded topologies appear in the simulations, but it is possible to select the native one on energetic grounds. Thus, it is demonstrated that the methodology is general for all protein motifs. Work is in progress in order to test the methodology on a larger set of protein structures.
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. CKAAPs may be important in protein folding and structural stability and function, and hence useful for protein engineering studies. This paper provides an update to the initial report of CKAAPs DB [Li et al. (2001) Nucleic Acids Res., 29, 329-331]. CKAAPs DB contains CKAAPs for the representative set of polypeptide chains derived from the CE and FSSP databases, as well as subdomains (conserved regions of the order of 100 residues within a domain) identified by CE. The new version now offers different perspectives on the CKAAPs. First, CKAAPs are mapped onto their respective Protein Data Bank (PDB) structures rendered by Molscript, providing a spatial context for the CKAAPs. Secondly, CKAAPs may be highlighted within a structure-based sequence alignment, as well as secondary structure alignment. Thirdly, the resulting sequence homologs from the structure alignment may be viewed in alignments colorized based on identities and property groups using Mview. New search capabilities have also been provided for searching by keyword combinations, PDB IDs, EC numbers, GI numbers, LocusLink ID, taxonomy, gene ontology and pathways. A new custom CKAAPs analysis interface has been implemented where a user may change the criteria for inclusion of chains, initiate CKAAPs analysis and retrieve results. CKAAPs DB is accessible through the web at http://ckaaps.sdsc.edu/. Plain text analysis results are available by FTP at ftp://ftp.sdsc.edu/pub/sdsc/biology/ckaap.