Hidden Markov models-based system (HMMSPECTR) for detecting structural homologies on the basis of sequential information

HMMSPECTR is a tool for finding putative structural homologs for proteins with known primary sequences. HMMSPECTR contains four major components: a data warehouse with the hidden Markov models (HMM) and alignment libraries; a search program which compares the initial protein sequences with the libraries of HMMs; a secondary structure prediction and comparison program; and a dominant protein selection program that prepares the set of 10-15 "best" proteins from the chosen HMMs. The data warehouse contains four libraries of HMMs. The first two libraries were constructed using different HHM preparation options of the HAMMER program. The third library contains parts ("partial HMM") of initial alignments. The fourth library contains trained HMMs. We tested our program against all of the protein targets proposed in the CASP4 competition. The data warehouse included libraries of structural alignments and HMMs constructed on the basis of proteins publicly available in the Protein Data Bank before the CASP4 meeting. The newest fully automated versions of HMMSPECTR 1.02 and 1.02ss produced better results than the best result reported at CASP4 either by r.m.s.d. or by length (or both) in 64% (HMMSPECTR 1.02) and 79% (HMMSPECTR 1.02ss) of the cases. The improvement is most notable for the targets with complexity 4 (difficult fold recognition cases).     

Database of structural motifs in proteins

SUMMARY: The database of structural motifs in proteins (DSMP) contains data relevant to helices, beta-turns, gamma-turns, beta-hairpins, psi-loops, beta-alpha-beta motifs, beta-sheets, beta-strands and disulphide bridges extracted from all proteins in the Protein Data Bank primarily using the PROMOTIF program and implemented as a web-based network service using the SRS. The data corresponding to the structural motifs includes; sequence, position in polypeptide chain, geometry, type, unique code, keywords and resolution of crystal structure. This data is available for a representative data set of 1028 protein chains and also for all 10 213 proteins in the Protein Data Bank. The three-dimensional coordinates for all structural motifs (except sheet and disulphide bridge) are also available for the representative data set. Using features in SRS, DSMP can be queried to extract information from one or more structural motifs that may be useful for sequence-structure analysis, prediction, modelling or design. AVAILABILITY: http://www. cdfd.org.in/dsmp.html     

HERA--a program to draw schematic diagrams of protein secondary structures

A program is described which generates hydrogen bonding diagrams of protein structures and optionally helical wheels and helical nets. The program can also beta-strands beta-strands and to automatically extract simple structural motifs such as hairpins or Greek keys. The program greatly reduces the effort required to produce these diagrams and offers considerable flexibility in the information which can be represented. The usefulness of the program is illustrated by several examples including comparing homologous families, correlating protein structure with attributes of individual residues, and extracting all examples of the psi-loop motif from the Brookhaven Data Bank.     

PDB-REPRDB: a database of representative protein chains from the Protein Data Bank (PDB)

PDB-REPRDB is a database of representative protein chains from the Protein Data Bank (PDB). The previous version of PDB-REPRDB provided 48 representative sets, whose similarity criteria were predetermined, on the WWW. The current version is designed so that the user may obtain a quick selection of representative chains from PDB. The selection of representative chains can be dynamically configured according to the user's requirement. The WWW interface provides a large degree of freedom in setting parameters, such as cut-off scores of sequence and structural similarity. One can obtain a representative list and classification data of protein chains from the system. The current database includes 20 457 protein chains from PDB entries (August 6, 2000). The system for PDB-REPRDB is available at the Parallel Protein Information Analysis system (PAPIA) WWW server (http://www.rwcp.or.jp/papia/).     

Sequence search algorithm assessment and testing toolkit (SAT)

MOTIVATION: The Sequence Search Algorithm Assessment and Testing Toolkit (SAT) aims to be a complete package for the comparison of different protein homology search algorithms. The structural classification of proteins can provide us with a clear criterion for judgment in homology detection. There have been several assessments based on structural sequences with classifications but a good deal of similar work is now being repeated with locally developed procedures and programs. The SAT will provide developers with a complete package which will save time and produce more comparable performance assessments for search algorithms. The package is complete in the sense that it provides a non-redundant large sequence resource database, a well-characterized query database of proteins domains, all the parsers and some previous results from PSI-BLAST and a hidden markov model algorithm. RESULTS: An analysis on two different data sets was carried out using the SAT package. It compared the performance of a full protein sequence database (RSDB100) with a non-redundant representative sequence database derived from it (RSDB50). The performance measurement indicated that the full database is sub-optimal for a homology search. This result justifies the use of much smaller and faster RSDB50 than RSDB100 for the SAT. AVAILABILITY: A web site is up. The whole packa ge is accessible via www and ftp. ftp://ftp.ebi.ac.uk/pub/contrib/jong/SAT http://cyrah.ebi.ac.uk:1111/Proj/Bio/SAT http://www.mrc-lmb.cam.ac.uk/genomes/SAT In the package, some previous assessment results produced by the package can also be found for reference. CONTACT: jong@ebi.ac.uk     

BioMagResBank (BMRB) as a partner in the Worldwide Protein Data Bank (wwPDB): new policies affecting biomolecular NMR depositions

We describe the role of the BioMagResBank (BMRB) within the Worldwide Protein Data Bank (wwPDB) and recent policies affecting the deposition of biomolecular NMR data. All PDB depositions of structures based on NMR data must now be accompanied by experimental restraints. A scheme has been devised that allows depositors to specify a representative structure and to define residues within that structure found experimentally to be largely unstructured. The BMRB now accepts coordinate sets representing three-dimensional structural models based on experimental NMR data of molecules of biological interest that fall outside the guidelines of the Protein Data Bank (i.e., the molecule is a peptide with 23 or fewer residues, a polynucleotide with 3 or fewer residues, a polysaccharide with 3 or fewer sugar residues, or a natural product), provided that the coordinates are accompanied by representation of the covalent structure of the molecule (atom connectivity), assigned NMR chemical shifts, and the structural restraints used in generating model. The BMRB now contains an archive of NMR data for metabolites and other small molecules found in biological systems.     

Site fidelity and movements of humpback whales (Megaptera novaeangliae) on the Brazilian breeding ground,southwestern Atlantic

Site fidelity and movements were studied for humpback whales photo-identified from 1989 to 2006 in the Abrolhos Bank, southwestern Atlantic, Brazil. A total of 2,612 individuals were identified, 374 of which were observed on more than one occasion. The cumulative number of identified whales has increased since 1989. Recapture rate was low and varied among different years. A total of 33 whales was observed using the Abrolhos Bank for longer than 10 yr, up to a maximum of 16 yr. Our data suggest that different whales show distinct movement rates. Some whales used a large extent of the Abrolhos Bank region. Opportunistic photo-identification data (on the scale of the Brazilian coast from 4° to 23°S) revealed important information about stock identity. The longest distance between within-season resightings was over 600 km, while one whale was observed in two locations separated by more than 1,400 km in different years. Long-range movements within and between seasons support the single stock hypothesis for humpback whales wintering off the Brazilian coast.     

A set of programs for analysis of kinetic and equilibrium data

A program package that can be used for analysis of a wide rangeof kinetic and equilibrium data is described. The four programswere written in Turbo Pascal and run on PC, XT, AT and compatibles.The first of the programs allows the user to fit data with 16predefined and one user-defined function, using two differentnon-linear least-squares procedures. Two additional programsare used to test both the evaluation of model functions andthe least-squares fits. One of these programs uses two simpleprocedures to generate a Gaussian-distributed random variablethat is used to simulate the experimental error of measurements.The last program simulates kinetics described by differentialequations that cannot be solved analytically, using numericalintegration. This program helps the user to judge the validityof steady-state assumptions or treatment of kinetic measurementsas relaxations. Received on September 19, 1989; accepted on March 16, 1990     

Protein Circular Dichroism Data Bank (PCDDB): data bank and website design

The Protein Circular Dichroism Data Bank (PCDDB) is a new deposition data bank for validated circular dichroism spectra of biomacromolecules. Its aim is to be a resource for the structural biology and bioinformatics communities, providing open access and archiving facilities for circular dichroism and synchrotron radiation circular dichroism spectra. It is named in parallel with the Protein Data Bank (PDB), a long-existing valuable reference data bank for protein crystal and NMR structures. In this article, we discuss the design of the data bank structure and the deposition website located at http://pcddb.cryst.bbk.ac.uk. Our aim is to produce a flexible and comprehensive archive, which enables user-friendly spectral deposition and searching. In the case of a protein whose crystal structure and sequence are known, the PCDDB entry will be linked to the appropriate PDB and sequence data bank files, respectively. It is anticipated that the PCDDB will provide a readily accessible biophysical catalogue of information on folded proteins that may be of value in structural genomics programs, for quality control and archiving in industrial and academic labs, as a resource for programs developing spectroscopic structural analysis methods, and in bioinformatics studies.     

Protein structure prediction using sparse dipolar coupling data

Residual dipolar coupling (RDC) represents one of the most exciting emerging NMR techniques for protein structure studies. However, solving a protein structure using RDC data alone is still a highly challenging problem. We report here a computer program, RDC-PROSPECT, for protein structure prediction based on a structural homolog or analog of the target protein in the Protein Data Bank (PDB), which best aligns with the ¹⁵N–¹H RDC data of the protein recorded in a single ordering medium. Since RDC-PROSPECT uses only RDC data and predicted secondary structure information, its performance is virtually independent of sequence similarity between a target protein and its structural homolog/analog, making it applicable to protein targets beyond the scope of current protein threading techniques. We have tested RDC-PROSPECT on all ¹⁵N–¹H RDC data (representing 43 proteins) deposited in the BioMagResBank (BMRB) database. The program correctly identified structural folds for 83.7% of the target proteins, and achieved an average alignment accuracy of 98.1% residues within a four-residue shift.     

SOMAP: a novel interactive approach to multiple protein sequences alignment

A novel interactive method for generating multiple protein sequencealignments is described. The program has no internal limit tothe number or length of sequences it can handle and is designedfor use with DEC VAX processors running the VMS operating system.The approach used is essentially one of manual sequence manipulation,aided by built-in symbolic displays of identities and similarities,and strict and ‘fuzzy’ (ambiguous) pattern-matchingfacilities. Additional flexibility is provided by means of aninterface to a publicly available automatic alignment systemand to a comprehensive sequence analysis package. Received on August 28, 1990; accepted on November 20, 1990     

Analysis of topological and nontopological structural similarities in the PDB: New examples with old structures

We have developed a new method and program, SARF2, for fast comparison of protein structures, which can detect topological as well as nontopological similarities. The method searches for large ensembles of secondary structure elements, which are mutually compatible in two proteins. These ensembles consist of small fragments of C^α-trace, similarly arranged in three-dimensional space in two proteins, but not necessarily equally-ordered along the polypeptide chains. The program SARF2 is available for everyone through the World-Wide Web (WWW). We have performed an exhaustive pairwise comparison of all the entries from a recent issue of the Protein Data Bank (PDB) and report here on the results of an automated hierarchical cluster analysis. In addition, we report on several new cases of significant structural resemblance between proteins. To this end, a new definition of the significance of structural similarity is introduced, which effectively distinguishes the biologically meaningful equivalences from those occurring by chance. Analyzing the distribution of sequence similarity in significant structural matches, we show that sequence similarity as low as 20% in structurally-prealigned proteins can be a strong indication for the biological relevance of structural similarity. © 1996 Wiley-Liss, Inc.     

An integrated family of amino acid sequence analysis programs

During the last years abundant sequence data has become availabledue to the rapid progress in protein and DNA sequencing techniques.The exact three-dimensional structures, however, are availableonly for a fraction of proteins with known sequences. For manypurposes the primary amino acid sequence of a protein can bedirectly used to predict important structural parameters. However,mathematical presentation of the calculated values often makesinterpretation difficult, especially if many proteins must beanalysed and compared. Here we introduce a broad-based, user-definedanalysis of amino acid sequence information. The program packageis based on published algorithms and is designed to access standardprotein data bases, calculate hydropathy, surface probabilityand flexibility values and perform secondary structure predictions.The data output is in an ‘easy-to-read’ graphicformat and several parameters can be superimposed within a singleplot in order to simplify data interpretations. Additionally,this package includes a novel algorithm for the prediction ofpotential antigenic sites. Thus the software package presentedhere offers a powerful means of analysing an amino acid sequencefor the purpose of structure/function studies as well as antigenicsite analyses. These algorithms were written to function incontext with the UWGCG (University of Wisconsin Genetics ComputerGroup) program collection, and are now distributed within thatpackage. Received on March 20, 1987; accepted on September 4, 1987     

Iris: Interactive all‐in‐one graphical validation of 3D protein model iterations

Iris validation is a Python package created to represent comprehensive per‐residue validation metrics for entire protein chains in a compact, readable and interactive view. These metrics can either be calculated by Iris, or by a third‐party program such as MolProbity. We show that those parts of a protein model requiring attention may generate ripples across the metrics on the diagram, immediately catching the modeler's attention. Iris can run as a standalone tool, or be plugged into existing structural biology software to display per‐chain model quality at a glance, with a particular emphasis on evaluating incremental changes resulting from the iterative nature of model building and refinement. Finally, the integration of Iris into the CCP4i2 graphical user interface is provided as a showcase of its pluggable design.     

Automated search of natively folded protein fragments for high-throughput structure determination in structural genomics

Structural genomic projects envision almost routine protein structure determinations, which are currently imaginable only for small proteins with molecular weights below 25,000 Da. For larger proteins, structural insight can be obtained by breaking them into small segments of amino acid sequences that can fold into native structures, even when isolated from the rest of the protein. Such segments are autonomously folding units (AFU) and have sizes suitable for fast structural analyses. Here, we propose to expand an intuitive procedure often employed for identifying biologically important domains to an automatic method for detecting putative folded protein fragments. The procedure is based on the recognition that large proteins can be regarded as a combination of independent domains conserved among diverse organisms. We thus have developed a program that reorganizes the output of BLAST searches and detects regions with a large number of similar sequences. To automate the detection process, it is reduced to a simple geometrical problem of recognizing rectangular shaped elevations in a graph that plots the number of similar sequences at each residue of a query sequence. We used our program to quantitatively corroborate the premise that segments with conserved sequences correspond to domains that fold into native structures. We applied our program to a test data set composed of 99 amino acid sequences containing 150 segments with structures listed in the Protein Data Bank, and thus known to fold into native structures. Overall, the fragments identified by our program have an almost 50% probability of forming a native structure, and comparable results are observed with sequences containing domain linkers classified in SCOP. Furthermore, we verified that our program identifies AFU in libraries from various organisms, and we found a significant number of AFU candidates for structural analysis, covering an estimated 5 to 20% of the genomic databases. Altogether, these results argue that methods based on sequence similarity can be useful for dissecting large proteins into small autonomously folding domains, and such methods may provide an efficient support to structural genomics projects.     

MAMMOTH (matching molecular models obtained from theory): an automated method for model comparison

Advances in structural genomics and protein structure prediction require the design of automatic, fast, objective, and well benchmarked methods capable of comparing and assessing the similarity of low-resolution three-dimensional structures, via experimental or theoretical approaches. Here, a new method for sequence-independent structural alignment is presented that allows comparison of an experimental protein structure with an arbitrary low-resolution protein tertiary model. The heuristic algorithm is given and then used to show that it can describe random structural alignments of proteins with different folds with good accuracy by an extreme value distribution. From this observation, a structural similarity score between two proteins or two different conformations of the same protein is derived from the likelihood of obtaining a given structural alignment by chance. The performance of the derived score is then compared with well established, consensus manual-based scores and data sets. We found that the new approach correlates better than other tools with the gold standard provided by a human evaluator. Timings indicate that the algorithm is fast enough for routine use with large databases of protein models. Overall, our results indicate that the new program (MAMMOTH) will be a good tool for protein structure comparisons in structural genomics applications. MAMMOTH is available from our web site at http://physbio.mssm.edu/~ortizg/.     

Consensus Data Mining (CDM) Protein Secondary Structure Prediction Server: combining GOR V and Fragment Database Mining (FDM)

One of the challenges in protein secondary structure prediction is to overcome the cross-validated 80% prediction accuracy barrier. Here, we propose a novel approach to surpass this barrier. Instead of using a single algorithm that relies on a limited data set for training, we combine two complementary methods having different strengths: Fragment Database Mining (FDM) and GOR V. FDM harnesses the availability of the known protein structures in the Protein Data Bank and provides highly accurate secondary structure predictions when sequentially similar structural fragments are identified. In contrast, the GOR V algorithm is based on information theory, Bayesian statistics, and PSI-BLAST multiple sequence alignments to predict the secondary structure of residues inside a sliding window along a protein chain. A combination of these two different methods benefits from the large number of structures in the PDB and significantly improves the secondary structure prediction accuracy, resulting in Q3 ranging from 67.5 to 93.2%, depending on the availability of highly similar fragments in the Protein Data Bank.     

Structure‐based barcoding of proteins

A reduced representation in the format of a barcode has been developed to provide an overview of the topological nature of a given protein structure from 3D coordinate file. The molecular structure of a protein coordinate file from Protein Data Bank is first expressed in terms of an alpha‐numero code and further converted to a barcode image. The barcode representation can be used to compare and contrast different proteins based on their structure. The utility of this method has been exemplified by comparing structural barcodes of proteins that belong to same fold family, and across different folds. In addition to this, we have attempted to provide an illustration to (i) the structural changes often seen in a given protein molecule upon interaction with ligands and (ii) Modifications in overall topology of a given protein during evolution. The program is fully downloadable from the website http://www.iitg.ac.in/probar/ .     

TargetDB: a target registration database for structural genomics projects

TargetDB is a centralized target registration database that includes protein target data from the NIH structural genomics centers and a number of international sites. TargetDB, which is hosted by the Protein Data Bank (RCSB PDB), provides status information on target sequences and tracks their progress through the various stages of protein production and structure determination. A simple search form permits queries based on contributing site, target ID, protein name, sequence, status and other data. The progress of individual targets or entire structural genomics projects may be tracked over time, and target data from all contributing centers may also be downloaded in the XML format. AVAILABILITY: TargetDB is available at http://targetdb.pdb.org/