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Janet M Thornton

Publications and source records attributed to Janet M Thornton.

At least 37 records · Page 2Linked to original sources
PubMed2005

The complement of enzymatic sets in different species.

We present here a comprehensive analysis of the complement of enzymes in a large variety of species. As enzymes are a relatively conserved group there are several classification systems available that are common to all species and link a protein sequence to an enzymatic function. Enzymes are therefore an ideal functional group to study the relationship between sequence expansion, functional divergence and phenotypic changes. By using information retrieved from the well annotated SWISS-PROT database together with sequence information from a variety of fully sequenced genomes and information from the EC functional scheme we have aimed here to estimate the fraction of enzymes in genomes, to determine the extent of their functional redundancy in different domains of life and to identify functional innovations and lineage specific expansions in the metazoa lineage. We found that prokaryote and eukaryote species differ both in the fraction of enzymes in their genomes and in the pattern of expansion of their enzymatic sets. We observe an increase in functional redundancy accompanying an increase in species complexity. A quantitative assessment was performed in order to determine the degree of functional redundancy in different species. Finally, we report a massive expansion in the number of mammalian enzymes involved in signalling and degradation.

Animals↗
PubMed2005

Detecting DNA-binding helix-turn-helix structural motifs using sequence and structure information.

In this work, we analyse the potential for using structural knowledge to improve the detection of the DNA-binding helix-turn-helix (HTH) motif from sequence. Starting from a set of DNA-binding protein structures that include a functional HTH motif and have no apparent sequence similarity to each other, two different libraries of hidden Markov models (HMMs) were built. One library included sequence models of whole DNA-binding domains, which incorporate the HTH motif, the second library included shorter models of 'partial' domains, representing only the fraction of the domain that corresponds to the functionally relevant HTH motif itself. The libraries were scanned against a dataset of protein sequences, some containing the HTH motifs, others not. HMM predictions were compared with the results obtained from a previously published structure-based method and subsequently combined with it. The combined method proved more effective than either of the single-featured approaches, showing that information carried by motif sequences and motif structures are to some extent complementary and can successfully be used together for the detection of DNA-binding HTHs in proteins of unknown function.

Amino Acid Sequence↗
PubMed2005

Progress of structural genomics initiatives: an analysis of solved target structures.

The explosion in gene sequence data and technological breakthroughs in protein structure determination inspired the launch of structural genomics (SG) initiatives. An often stated goal of structural genomics is the high-throughput structural characterisation of all protein sequence families, with the long-term hope of significantly impacting on the life sciences, biotechnology and drug discovery. Here, we present a comprehensive analysis of solved SG targets to assess progress of these initiatives. Eleven consortia have contributed 316 non-redundant entries and 323 protein chains to the Protein Data Bank (PDB), and 459 and 393 domains to the CATH and SCOP structure classifications, respectively. The quality and size of these proteins are comparable to those solved in traditional structural biology and, despite huge scope for duplicated efforts, only 14% of targets have a close homologue (>/=30% sequence identity) solved by another consortium. Analysis of CATH and SCOP revealed the significant contribution that structural genomics is making to the coverage of superfamilies and folds. A total of 67% of SG domains in CATH are unique, lacking an already characterised close homologue in the PDB, whereas only 21% of non-SG domains are unique. For 29% of domains, structure determination revealed a remote evolutionary relationship not apparent from sequence, and 19% and 11% contributed new superfamilies and folds. The secondary structure class, fold and superfamily distributions of this dataset reflect those of the genomes. The domains fall into 172 different folds and 259 superfamilies in CATH but the distribution is highly skewed. The most populous of these are those that recur most frequently in the genomes. Whilst 11% of superfamilies are bacteria-specific, most are common to all three superkingdoms of life and together the 316 PDB entries have provided new and reliable homology models for 9287 non-redundant gene sequences in 206 completely sequenced genomes. From the perspective of this analysis, it appears that structural genomics is on track to be a success, and it is hoped that this work will inform future directions of the field.

Animals↗
PubMed2005

Using a library of structural templates to recognise catalytic sites and explore their evolution in homologous families.

Catalytic site structure is normally highly conserved between distantly related enzymes. As a consequence, templates representing catalytic sites have the potential to succeed at function prediction in cases where methods based on sequence or overall structure fail. There are many methods for searching protein structures for matches to structural templates, but few validated template libraries to use with these methods. We present a library of structural templates representing catalytic sites, based on information from the scientific literature. Furthermore, we analyse homologous template families to discover the diversity within families and the utility of templates for active site recognition. Templates representing the catalytic sites of homologous proteins mostly differ by less than 1A root mean square deviation, even when the sequence similarity between the two proteins is low. Within these sets of homologues there is usually no discernible relationship between catalytic site structure similarity and sequence similarity. Because of this structural conservation of catalytic sites, the templates can discriminate between matches to related proteins and random matches with over 85% sensitivity and predictive accuracy. Templates based on protein backbone positions are more discriminating than those based on side-chain atoms. These analyses show encouraging prospects for prediction of functional sites in structural genomics structures of unknown function, and will be of use in analyses of convergent evolution and exploring relationships between active site geometry and chemistry. The template library can be queried via a web server at and is available for download.

Algorithms↗
PubMed2005

A ligand-centric analysis of the diversity and evolution of protein-ligand relationships in E.coli.

As enzymes evolve and diverge from common ancestor sequences, they often keep their overall reaction chemistry but specialize in the binding of different cognate ligands. This study borrows methods for the computational assessment of 2D similarity of small molecules from the field of chemoinformatics, to examine the extent of structure conservation of cognate ligands binding to similar proteins. Proteins from 87 structural superfamilies from Escherichia coli form the core dataset, which is extended using homologues with functional assignments from any organism. We find that correlation of the substrate similarity with protein similarity (measured by either sequence-based or structure-based scores) can only be clearly established for very similar proteins. At low sequence identities, the superfamily to which a protein belongs can give helpful clues to its function, and more importantly, the confidence attached to such clues is superfamily-dependent. Our data indicate that only a few superfamilies show great substrate diversity, and that most exhibit conservation of at least part of the structural scaffold of the substrate.

Databases, Protein↗
PubMed2005

Real spherical harmonic expansion coefficients as 3D shape descriptors for protein binding pocket and ligand comparisons.

MOTIVATION: An increasing number of protein structures are being determined for which no biochemical characterization is available. The analysis of protein structure and function assignment is becoming an unexpected challenge and a major bottleneck towards the goal of well-annotated genomes. As shape plays a crucial role in biomolecular recognition and function, the examination and development of shape description and comparison techniques is likely to be of prime importance for understanding protein structure-function relationships. RESULTS: A novel technique is presented for the comparison of protein binding pockets. The method uses the coefficients of a real spherical harmonics expansion to describe the shape of a protein's binding pocket. Shape similarity is computed as the L2 distance in coefficient space. Such comparisons in several thousands per second can be carried out on a standard linux PC. Other properties such as the electrostatic potential fit seamlessly into the same framework. The method can also be used directly for describing the shape of proteins and other molecules. AVAILABILITY: A limited version of the software for the real spherical harmonics expansion of a set of points in PDB format is freely available upon request from the authors. Binding pocket comparisons and ligand prediction will be made available through the protein structure annotation pipeline Profunc (written by Roman Laskowski) which will be accessible from the EBI website shortly.

Algorithms↗
PubMed2005

PDBsum more: new summaries and analyses of the known 3D structures of proteins and nucleic acids.

PDBsum is a database of mainly pictorial summaries of the 3D structures of proteins and nucleic acids in the Protein Data Bank. Its pages aim to provide an at-a-glance view of the contents of every 3D structure, plus detailed structural analyses of each protein chain, DNA-RNA chain and any bound ligands and metals. In the past year, the database has been significantly improved, in terms of both appearance and new content. Moreover, it has moved to its new address at http://www.ebi.ac.uk/thornton-srv/databases/pdbsum.

Databases, Protein↗
PubMed2005

Morphological aspects of oligomeric protein structures.

Features of multimeric proteins are reviewed to shed light on the formation of protein assemblies from a structural perspective. The features comprise biochemical and geometric properties. They are compiled on new low-redundancy sets of crystal structures of homomeric proteins with different symmetry and subunit multiplicity, as well as on a set of heteromeric proteins. Crystal structures of likely monomers provide a control group.

Dimerization↗
PubMed2005

Predicting protein function from sequence and structural data.

When a protein's function cannot be experimentally determined, it can often be inferred from sequence similarity. Should this process fail, analysis of the protein structure can provide functional clues or confirm tentative functional assignments inferred from the sequence. Many structure-based approaches exist (e.g. fold similarity, three-dimensional templates), but as no single method can be expected to be successful in all cases, a more prudent approach involves combining multiple methods. Several automated servers that integrate evidence from multiple sources have been released this year and particular improvements have been seen with methods utilizing the Gene Ontology functional annotation schema.

Binding Sites↗
PubMed2005

Microeconomic principles explain an optimal genome size in bacteria.

Bacteria can clearly enhance their survival by expanding their genetic repertoire. However, the tight packing of the bacterial genome and the fact that the most evolved species do not necessarily have the biggest genomes suggest there are other evolutionary factors limiting their genome expansion. To clarify these restrictions on size, we studied those protein families contributing most significantly to bacterial-genome complexity. We found that all bacteria apply the same basic and ancestral 'molecular technology' to optimize their reproductive efficiency. The same microeconomics principles that define the optimum size in a factory can also explain the existence of a statistical optimum in bacterial genome size. This optimum is reached when the bacterial genome obtains the maximum metabolic complexity (revenue) for minimal regulatory genes (logistic cost).

Bacteria↗
PubMed2005

Protein families and their evolution-a structural perspective.

We can now assign about two thirds of the sequences from completed genomes to as few as 1400 domain families for which structures are known and thus more ancient evolutionary relationships established. About 200 of these domain families are common to all kingdoms of life and account for nearly 50% of domain structure annotations in the genomes. Some of these domain families have been very extensively duplicated within a genome and combined with different domain partners giving rise to different multidomain proteins. The ways in which these domain combinations evolve tend to be specific to the organism so that less than 15% of the protein families found within a genome appear to be common to all kingdoms of life. Recent analyses of completed genomes, exploiting the structural data, have revealed the extent to which duplication of these domains and modifications of their functions can expand the functional repertoire of the organism, contributing to increasing complexity.

Animals↗
PubMed2004

Toward the detection and validation of repeats in protein structure.

We present a method called DAVROS to detect, localize, and validate repeating motifs in protein structure allowing for insertions and deletions. DAVROS uses the score matrix from a structural alignment program (SAP) to search for repeating motifs using an algorithm based on concepts from signal processing and the statistical properties of the alignments. The method was tested against a nonredundant Protein Data Bank, and each chain was assigned a score. For the top 50 chains ranked by score, 70% contain repeating motifs detected without error. These represent 14 types of fold covering alpha, beta, and alphabeta protein classes. A second data set comprising protein chains in different sequence families for triosephosphate isomerase (TIM) barrel, leucine-rich repeat (LRR), trefoil, and alpha-alpha barrel folds was used to assess the ability of DAVROS to detect all motifs within a specific fold. For the second test set, the percentage of motifs detected was highest for the LRR chains (88.7%) and least for the TIM barrels (60%). This variability results from the regularity of the LRR motif compared to the alphabeta units of the TIM barrel, which generally have many more indels. These reduce the strength of the repeat signal in the SAP matrix, making repeat detection more difficult.

Amino Acid Motifs↗
PubMed2004

Computational analysis of alpha-helical membrane protein structure: implications for the prediction of 3D structural models.

Relatively little has been known about the structure of alpha-helical membrane proteins, since until recently few structures had been crystallized. These limited data have restricted structural analyses to the prediction of secondary structure, rather than tertiary folds. In order to address this, this paper describes an analysis of the 23 available membrane protein structures. A number of findings are made that are of particular relevance to transmembrane helix packing: (1) on average lipid-tail-accessible transmembrane residues are significantly more hydrophobic, less conserved and contain different residue types to buried residues; (2) charged residues are not always buried and, when accessible to membrane lipid tails, few are paired with another charge and instead they often interact with phospholipid head-groups or with other residue types; (3) a significant proportion of lipid-tail-accessible charged and polar residues form hydrogen bonds only with residues one turn away in the same helix (intra-helix); (4) pore-lining residues are usually hydrophobic and it is difficult to distinguish them from buried residues in terms of either residue type or conservation; and (5) information was gained about the proportion of helices that tend to contribute to lining a pore and the resulting pore diameter. These findings are discussed with relevance to the prediction of membrane protein 3D structure.

Databases, Protein↗
PubMed2004

Identifying DNA-binding proteins using structural motifs and the electrostatic potential.

Robust methods to detect DNA-binding proteins from structures of unknown function are important for structural biology. This paper describes a method for identifying such proteins that (i) have a solvent accessible structural motif necessary for DNA-binding and (ii) a positive electrostatic potential in the region of the binding region. We focus on three structural motifs: helix-turn-helix (HTH), helix-hairpin-helix (HhH) and helix-loop-helix (HLH). We find that the combination of these variables detect 78% of proteins with an HTH motif, which is a substantial improvement over previous work based purely on structural templates and is comparable to more complex methods of identifying DNA-binding proteins. Similar true positive fractions are achieved for the HhH and HLH motifs. We see evidence of wide evolutionary diversity for DNA-binding proteins with an HTH motif, and much smaller diversity for those with an HhH or HLH motif.

Amino Acid Motifs↗
PubMed2004

SCOPEC: a database of protein catalytic domains.

MOTIVATION: Domains are the units of protein structure, function and evolution. It is therefore essential to utilize knowledge of domains when studying the evolution of function, or when assigning function to genome sequence data. For this purpose, we have developed a database of catalytic domains, SCOPEC, by combining structural domain information from SCOP, full-length sequence information from Swiss-Prot, and verified functional information from the Enzyme Classification (EC) database. Two major problems need to be overcome to create a database of domain-function relationships; (1) for sequences, EC numbers are typically assigned to whole sequences rather than the functional unit, and (2) The Protein Data Bank (PDB) structures elucidated from a larger multi-domain protein will often have EC annotation although the relevant catalytic domain may lie elsewhere. RESULTS: SCOPEC entries have high quality enzyme assignments; having passed both computational and manual checks. SCOPEC currently contains entries for 75% of all EC annotations in the PDB. Overall, EC number is fairly well conserved within a superfamily, even when the proteins are distantly related. Initial analysis is encouraging; suggesting that there is a 50:50 chance of conserved function in distant homologues first detected by a third iteration PSI-BLAST search. Therefore, we envisage that a knowledge-based approach to function assignment using the domain-EC relationships in SCOPEC will gain a marked improvement over this base line. AVAILABILITY: The SCOPEC database is a valuable resource in the analysis and prediction of protein structure and function. It can be obtained or queried at our website http://www.enzome.com

Catalysis↗
PubMed2004

A practical and robust sequence search strategy for structural genomics target selection.

MOTIVATION: Target selection strategies for structural genomic projects must be able to prioritize gene regions on the basis of significant sequence similarity with proteins that have already been structurally determined. With the rapid development of protein comparison software a robust prioritization scheme should be independent of the choice of algorithm and be able to incorporate different sequence similarity thresholds. RESULTS: A robust target selection strategy has been developed that can assign a priority level to all genes in any genome. Structural assignments to genome sequences are calculated at two thresholds and six levels (1-6) describe the prioritization of all whole genes and partial gene regions. This simple two-threshold approach can be implemented with any fold recognition or homology detection algorithms. The results for 10 genomes are presented using the SSEARCH and PSI-BLAST programs. AVAILABILITY: Programs are available on request from the authors.

Algorithms↗
PubMed2004

Evolution of protein superfamilies and bacterial genome size.

We present the structural annotation of 56 different bacterial species based on the assignment of genes to 816 evolutionary superfamilies in the CATH domain structure database. These assignments have enabled us to analyse the recurrence of specific superfamilies within and across the genomes. We have selected the superfamilies that have a very broad representation and therefore appear to be universally distributed in a significant number of bacterial lineages. Occurrence profiles of these universally distributed superfamilies are compared with genome size in order to estimate the correlation between superfamily duplication and the increase in proteome size. This distinguishes between those size-dependent superfamilies where frequency of occurrence is highly correlated with increase in genome size, and size-independent superfamilies where no correlation is observed. Consideration of the size correlation and the ratio between the mean and the standard deviations for all the superfamily profiles allows more detailed subdivisions and classification of superfamilies. For example, within the size-independent superfamilies, we distinguished a group that are distributed evenly amongst all the genomes. Within the size-dependent superfamilies we differentiated two groups: linearly distributed and non-linearly distributed. Functional annotation using the COG database was performed for all superfamilies in each of these groups, and this revealed significant differences amongst the three sets of superfamilies. Evenly distributed, size-independent domains are shown to be involved primarily in protein translation and biosynthesis. For the size-dependent superfamilies, linearly distributed superfamilies are involved mainly in metabolism, and non-linearly distributed superfamily domains are involved principally in gene regulation.

Databases, Protein↗