Search PubMed⌕ Search

Biomedical subjects

Jaap Heringa

Publications and source records attributed to Jaap Heringa.

15 recordsLinked to original sources

Sequence comparison by sequence harmony identifies subtype-specific functional sites.

Multiple sequence alignments are often used to reveal functionally important residues within a protein family. They can be particularly useful for the identification of key residues that determine functional differences between protein subfamilies. We present a new entropy-based method, Sequence Harmony (SH) that accurately detects subfamily-specific positions from a multiple sequence alignment. The SH algorithm implements a novel formula, able to score compositional differences between subfamilies, without imposing conservation, in a simple manner on an intuitive scale. We compare our method with the most important published methods, i.e. AMAS, TreeDet and SDP-pred, using three well-studied protein families: the receptor-binding domain (MH2) of the Smad family of transcription factors, the Ras-superfamily of small GTPases and the MIP-family of integral membrane transporters. We demonstrate that SH accurately selects known functional sites with higher coverage than the other methods for these test-cases. This shows that compositional differences between protein subfamilies provide sufficient basis for identification of functional sites. In addition, SH selects a number of sites of unknown function that could be interesting candidates for further experimental investigation.

Algorithms↗

Global multiple-sequence alignment with repeats.

Repeating fragments in biological sequences are often essential for structure and function. Over the years, many methods have been developed to recognize repeats or to multiply align protein sequences. However, the integration of these two methodologies has been largely unexplored to date. Here, we present a new method capable of globally aligning multiple input sequences under the constraints of a given repeat analysis. The method supports different stringency modes to adapt to various levels of detail and reliability of the repeat information available.

Amino Acid Sequence↗

AuberGene--a sensitive genome alignment tool.

MOTIVATION: The accumulation of genome sequences will only accelerate in the coming years. We aim to use this abundance of data to improve the quality of genomic alignments and devise a method which is capable of detecting regions evolving under weak or no evolutionary constraints. RESULTS: We describe a genome alignment program AuberGene, which explores the idea of transitivity of local alignments. Assessment of the program was done based on a 2 Mbp genomic region containing the CFTR gene of 13 species. In this region, we can identify 53% of human sequence sharing common ancestry with mouse, as compared with 44% found using the usual pairwise alignment. Between human and tetraodon 93 orthologous exons are found, as compared with 77 detected by the pairwise human-tetraodon comparison. AuberGene allows the user to (1) identify distant, previously undetected, conserved orthogonal regions such as ORFs or regulatory regions; (2) identify neutrally evolving regions in related species which are often overlooked by other alignment programs; (3) recognize false orthologous genomic regions. The increased sensitivity of the method is not obtained at the cost of reduced specificity. Our results suggest that, over the CFTR region, human shares 10% more sequence with mouse than previously thought ( approximately 50%, instead of 40% found with the pairwise alignment).

Algorithms↗

Scooby-domain: prediction of globular domains in protein sequence.

Scooby-domain (sequence hydrophobicity predicts domains) is a fast and simple method to identify globular domains in protein sequence, based on the observed lengths and hydrophobicities of domains from proteins with known tertiary structure. The prediction method successfully identifies sequence regions that will form a globular structure and those that are likely to be unstructured. The method does not rely on homology searches and, therefore, can identify previously unknown domains for structural elucidation. Scooby-domain is available as a Java applet at http://ibivu.cs.vu.nl/programs/scoobywww. It may be used to visualize local properties within a protein sequence, such as average hydrophobicity, secondary structure propensity and domain boundaries, as well as being a method for fast domain assignment of large sequence sets.

Hydrophobic and Hydrophilic Interactions↗

A simple and fast secondary structure prediction method using hidden neural networks.

MOTIVATION: In this paper, we present a secondary structure prediction method YASPIN that unlike the current state-of-the-art methods utilizes a single neural network for predicting the secondary structure elements in a 7-state local structure scheme and then optimizes the output using a hidden Markov model, which results in providing more information for the prediction. RESULTS: YASPIN was compared with the current top-performing secondary structure prediction methods, such as PHDpsi, PROFsec, SSPro2, JNET and PSIPRED. The overall prediction accuracy on the independent EVA5 sequence set is comparable with that of the top performers, according to the Q3, SOV and Matthew's correlations accuracy measures. YASPIN shows the highest accuracy in terms of Q3 and SOV scores for strand prediction. AVAILABILITY: YASPIN is available on-line at the Centre for Integrative Bioinformatics website (http://ibivu.cs.vu.nl/programs/yaspinwww/) at the Vrije University in Amsterdam and will soon be mirrored on the Mathematical Biology website (http://www.mathbio.nimr.mrc.ac.uk) at the NIMR in London. CONTACT: kxlin@nimr.mrc.ac.uk

Algorithms↗

Tracking repeats using significance and transitivity.

MOTIVATION: Internal repeats in coding sequences correspond to structural and functional units of proteins. Moreover, duplication of fragments of coding sequences is known to be a mechanism to facilitate evolution. Identification of repeats is crucial to shed light on the function and structure of proteins, and explain their evolutionary past. The task is difficult because during the course of evolution many repeats diverged beyond recognition. RESULTS: We introduce a new method TRUST, for ab initio determination of internal repeats in proteins. It provides an improvement in prediction quality as compared to alternative state-of-the-art methods. The increased sensitivity and accuracy of the method is achieved by exploiting the concept of transitivity of alignments. Starting from significant local suboptimal alignments, the application of transitivity allows us to (1) identify distant repeat homologues for which no alignments were found; (2) gain confidence about consistently well-aligned regions; and (3) recognize and reduce the contribution of non-homologous repeats. This re-assessment step enables us to derive a virtually noise-free profile representing a generalized repeat with high fidelity. We also obtained superior specificity by employing rigid statistical testing for self-sequence and profile-sequence alignments. Assessment was done using a database of repeat annotations based on structural superpositioning. The results show that TRUST is a useful and reliable tool for mining tandem and non-tandem repeats in protein sequence databases, capable of predicting multiple repeat types with varying intervening segments within a single sequence. AVAILABILITY: The TRUST server (together with the source code) is available at http://ibivu.cs.vu.nl/programs/trustwww

Algorithms↗

Contact-based sequence alignment.

This paper introduces the novel method of contact-based protein sequence alignment, where structural information in the form of contact mutation probabilities is incorporated into an alignment routine using contact-mutation matrices (CAO: Contact Accepted mutatiOn). The contact-based alignment routine optimizes the score of matched contacts, which involves four (two per contact) instead of two residues per match in pairwise alignments. The first contact refers to a real side-chain contact in a template sequence with known structure, and the second contact is the equivalent putative contact of a homologous query sequence with unknown structure. An algorithm has been devised to perform a pairwise sequence alignment based on contact information. The contact scores were combined with PAM-type (Point Accepted Mutation) substitution scores after parameterization of gap penalties and score weights by means of a genetic algorithm. We show that owing to the structural information contained in the CAO matrices, significantly improved alignments of distantly related sequences can be obtained. This has allowed us to annotate eight putative Drosophila IGF sequences. Contact-based sequence alignment should therefore prove useful in comparative modelling and fold recognition.

Algorithms↗

Testing homology with Contact Accepted mutatiOn (CAO): a contact-based Markov model of protein evolution.

Point Accepted Mutation (PAM) is the Markov model of amino acid replacements in proteins introduced by Dayhoff and her co-workers (Dayhoff et al., 1978). The PAM matrices and other matrices based on the PAM model have been widely accepted as the standard scoring system of protein sequence similarity in protein sequence alignment tools. Here, we present Contact Accepted mutatiOn (CAO), a Markov model of protein residue contact mutations. The CAO model simulates the interchanging of structurally defined side-chain contacts, and introduces additional structural information into protein sequence alignments. Therefore, similarities between structurally conserved sequences can be detected even without apparent sequence similarity. CAO has been benchmarked on the HOMSTRAD database and a subset of the CATH database, by comparing sequence alignments with reference alignments derived from structural superposition. CAO yields scores that reflect coherently the structural quality of sequence alignments, which has implications particularly for homology modelling and threading techniques.

Amino Acid Sequence↗

Protein domain identification and improved sequence similarity searching using PSI-BLAST.

Protein sequences containing more than one structural domain are problematic when used in homology searches where they can either stop an iterative database search prematurely or cause an explosion of a search to common domains. We describe a method, DOMAINATION, that infers domains and their boundaries in a query sequence from local gapped alignments generated using PSI-BLAST. Through a new technique to recognize domain insertions and permutations, DOMAINATION submits delineated domains as successive database queries in further iterative steps. Assessed over a set of 452 multidomain proteins, the method predicts structural domain boundaries with an overall accuracy of 50% and improves finding distant homologies by 14% compared with PSI-BLAST. DOMAINATION is available as a web based tool at http://mathbio.nimr.mrc.ac.uk, and the source code is available from the authors upon request.

Animals↗

SnapDRAGON: a method to delineate protein structural domains from sequence data.

We describe a method to identify protein domain boundaries from sequence information alone based on the assumption that hydrophobic residues cluster together in space. SnapDRAGON is a suite of programs developed to predict domain boundaries based on the consistency observed in a set of alternative ab initio three-dimensional (3D) models generated for a given protein multiple sequence alignment. This is achieved by running a distance geometry-based folding technique in conjunction with a 3D-domain assignment algorithm. The overall accuracy of our method in predicting the number of domains for a non-redundant data set of 414 multiple alignments, representing 185 single and 231 multiple-domain proteins, is 72.4 %. Using domain linker regions observed in the tertiary structures associated with each query alignment as the standard of truth, inter-domain boundary positions are delineated with an accuracy of 63.9 % for proteins comprising continuous domains only, and 35.4 % for proteins with discontinuous domains. Overall, domain boundaries are delineated with an accuracy of 51.8 %. The prediction accuracy values are independent of the pair-wise sequence similarities within each of the alignments. These results demonstrate the capability of our method to delineate domains in protein sequences associated with a wide variety of structural domain organisation.

Algorithms↗

Local weighting schemes for protein multiple sequence alignment.

This paper describes three weighting schemes for improving the accuracy of progressive multiple sequence alignment methods: (1) global profile pre-processing, to capture for each sequence information about other sequences in a profile before the actual multiple alignment takes place; (2) local pre-processing; which incorporates a new protocol to only use non-overlapping local sequence regions to construct the pre-processed profiles; and (3) local-global alignment, a weighting scheme based on the double dynamic programming (DDP) technique to softly bias global alignment to local sequence motifs. The first two schemes allow the compilation of residue-specific multiple alignment reliability indices, which can be used in an iterative fashion. The schemes have been implemented with associated iterative modes in the PRALINE multiple sequence alignment method, and have been evaluated using the BAliBASE benchmark alignment database. These tests indicate that PRALINE is a toolbox able to build alignments with very high quality. We found that local profile pre-processing raises the alignment quality by 5.5% compared to PRALINE alignments generated under default conditions. Iteration enhances the quality by a further percentage point. The implications of multiple alignment scoring functions and iteration in relation to alignment quality and benchmarking are discussed.

Amino Acid Motifs↗

Parallelized multiple alignment.

UNLABELLED: Multiple sequence alignment is a frequently used technique for analyzing sequence relationships. Compilation of large alignments is computationally expensive, but processing time can be considerably reduced when the computational load is distributed over many processors. Parallel processing functionality in the form of single-instruction multiple-data (SIMD) technology was implemented into the multiple alignment program Praline by using 'message passing interface' (MPI) routines. Over the alignments tested here, the parallelized program performed up to ten times faster on 25 processors compared to the single processor version. AVAILABILITY: Example program code for parallelizing pairwise alignment loops is available from http://mathbio.nimr.mrc.ac.uk/~jkleinj/tools/mpicode. The 'message passing interface' package (MPICH) is available from http:/www.unix.mcs.anl.gov/mpi/mpich. CONTACT: jhering@nimr.mrc.ac.uk SUPPLEMENTARY INFORMATION: Praline is accessible at http://mathbio.nimr.mrc.ac.uk/praline.

Algorithms↗

An analysis of protein domain linkers: their classification and role in protein folding.

Recent advances in protein engineering have come from creating multi-functional chimeric proteins containing modules from various proteins. These modules are typically joined via an oligopeptide linker, the correct design of which is crucial for the desired function of the chimeric protein. Here we analyse the properties of naturally occurring inter-domain linkers with the aim to design linkers for domain fusion. Two main types of linker were identified; helical and non-helical. Helical linkers are thought to act as rigid spacers separating two domains. Non-helical linkers are rich in prolines, which also leads to structural rigidity and isolation of the linker from the attached domains. This means that both linker types are likely to act as a scaffold to prevent unfavourable interactions between folding domains. Based on these results we have constructed a linker database intended for the rational design of linkers for domain fusion, which can be accessed via the Internet at http://mathbio.nimr.mrc.ac.uk.

Chi-Square Distribution↗

A Fourier analysis of symmetry in protein structure.

The score matrix from a structure comparison program (SAP) was used to search for repeated structures using a Fourier analysis. When tested with artificial data, a simple Fourier transform of the smoothed matrix provided a clear signal of the repeat periodicity that could be used to extract the repeating units with the SAP program. The strength of the Fourier signal was calibrated against the signal from model proteins. The most useful of these was the novel random-walk approach employed to generate realistic 'fake' structures. On the basis of these it was possible to conclude that only a small proportion of protein structures have an unexpected degree of symmetry. Artificially generated 'ideal' folds provided an upper limit on the strength of signal that could be expected from a 'perfectly' repeating compact structure. Unexpectedly, some of the very regular beta-propellor folds attained the same strength but the majority of symmetric structures lay below this region. When native proteins were ranked by the power of their spectrum a wide variety of fold types were seen to score highly. In the betaalpha class, these included the globular betaalpha proteins and the more repetitive leucine-rich betaalpha folds. In the all-beta class; beta-propellors, beta-prisms and beta-helices were found as well as the more globular gamma-crystalin domains. When this ranked list was filtered to remove proteins that contained detectable internal sequence similarity (using the program REPRO), the list became exclusively composed of just globular betaalpha class proteins and in the top 50 re-ranked proteins, only a single 4-fold propellor structure remained.

Fourier Analysis↗