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Janet M Thornton

Publications and source records attributed to Janet M Thornton.

At least 55 records · Page 3Linked to original sources
PubMed2004

The Catalytic Site Atlas: a resource of catalytic sites and residues identified in enzymes using structural data.

The Catalytic Site Atlas (CSA) provides catalytic residue annotation for enzymes in the Protein Data Bank. It is available online at http://www.ebi.ac.uk/thornton-srv/databases/CSA. The database consists of two types of annotated site: an original hand-annotated set containing information extracted from the primary literature, using defined criteria to assign catalytic residues, and an additional homologous set, containing annotations inferred by PSI-BLAST and sequence alignment to one of the original set. The CSA can be queried via Swiss-Prot identifier and EC number, as well as by PDB code. CSA Version 1.0 contains 177 original hand- annotated entries and 2608 homologous entries, and covers approximately 30% of all EC numbers found in PDB. The CSA will be updated on a monthly basis to include homologous sites found in new PDBs, and new hand-annotated enzymes as and when their annotation is completed.

Animals↗
PubMed2004

Searching for functional sites in protein structures.

An ability to assign protein function from protein structure is important for structural genomics consortia. The complex relationship between protein fold and function highlights the necessity of looking beyond the global fold of a protein to specific functional sites. Many computational methods have been developed that address this issue. These include evolutionary trace methods, methods that involve the calculation and assessment of maximal superpositions, methods based on graph theory, and methods that apply machine learning techniques. Such function prediction techniques have been applied to the identification of enzyme catalytic triads and DNA-binding motifs.

Binding Sites↗
PubMed2004

Ligand selectivity and competition between enzymes in silico.

In a cell, there are many possibilities for cross interactions between enzymes and small molecules, arising from the similarities in the structures of the metabolites and the flexibility in binding of protein active sites. Despite this promiscuity, the cognate partners must be able to recognize each other in vivo, for the cell to function efficiently. This study examines the basis of this selectivity in recognition using standard docking calculations and finds significant improvement when proteins and ligands are cross-docked. We find that cognate molecules rarely form the most stable complexes and that specificity may be driven either by recognition of the substrate by the enzyme or the recognition of the enzyme by the substrate. Despite limitations of the in silico methods, especially the scoring functions, these calculations highlight the need to consider cross reactions in the cell and suggest that localization and compartmentalization must be important factors in the evolution of complex cells. However, the inherent promiscuity of these interactions can also benefit an organism, by facilitating the evolution of new functions from old ones. The results also suggest that high-throughput screening should involve not just a panel of small molecules, but also a panel of proteins to test for cross-reactivity.

Binding Sites↗
PubMed2003

Using electrostatic potentials to predict DNA-binding sites on DNA-binding proteins.

A method to detect DNA-binding sites on the surface of a protein structure is important for functional annotation. This work describes the analysis of residue patches on the surface of DNA-binding proteins and the development of a method of predicting DNA-binding sites using a single feature of these surface patches. Surface patches and the DNA-binding sites were initially analysed for accessibility, electrostatic potential, residue propensity, hydrophobicity and residue conservation. From this, it was observed that the DNA-binding sites were, in general, amongst the top 10% of patches with the largest positive electrostatic scores. This knowledge led to the development of a prediction method in which patches of surface residues were selected such that they excluded residues with negative electrostatic scores. This method was used to make predictions for a data set of 56 non-homologous DNA-binding proteins. Correct predictions made for 68% of the data set.

Binding Sites↗
PubMed2003

A structure-based anatomy of the E.coli metabolome.

The Escherichia coli metabolome has been characterised using the two-dimensional structures of 745 metabolites, obtained from the EcoCyc and KEGG databases. Physicochemical properties of the metabolome have been calculated to provide an overview of this set of cognate ligands. A library of fragments commonly found among these molecules has been employed to reveal the main constituents of metabolites, and to assist a broad classification of the metabolome into biochemically relevant classes. Fragment-based fingerprints reveal the metabolome as a continuum in the two-dimensional structural space, where clusters of molecules sharing similar scaffolds can be identified, but are generally overlapping. Nucleotide, carbohydrate and amino acid-like molecules are the most prominent, but at high levels of similarity, a more detailed classification is possible. Classification schemes for the metabolome are a promising tool for understanding the chemical diversity of the metabolome. When used in conjunction with existing classifications of the proteome, they can help to elucidate the binding preferences and promiscuity of proteins and their cognate substrates.

Computational Biology↗
PubMed2003

An algorithm for constraint-based structural template matching: application to 3D templates with statistical analysis.

MOTIVATION: Structural templates consisting of a few atoms in a specific geometric conformation provide a powerful tool for studying the relationship between protein structure and function. Current methods for template searching constrain template syntax and semantics by their design. Hence there is a need for a more flexible core algorithm upon which to build more sophisticated tools. Statistical analysis of structural similarity is still in its infancy when compared with its analogue in sequence alignment. In the context of template matching, there is an urgent need for normalization of scores so that results from templates with differing sensitivity may be compared directly. RESULTS: We introduce Jess, a fast and flexible algorithm for searching protein structures for small groups of atoms under arbitrary constraints on geometry and chemistry. We apply the algorithm to a set of manually derived enzyme active site templates, and derive an empirical measure for estimating the relative significance of hits encountered using differing templates.

Algorithms↗
PubMed2003

Catalysing new reactions during evolution: economy of residues and mechanism.

The diversity of function in some enzyme superfamilies shows that during evolution, enzymes have evolved to catalyse different reactions on the same structure scaffold. In this analysis, we examine in detail how enzymes can modify their chemistry, through a comparison of the catalytic residues and mechanisms in 27 pairs of homologous enzymes of totally different functions. We find that evolution is very economical. Enzymes retain structurally conserved residues to aid catalysis, including residues that bind catalytic metal ions and modulate cofactor chemistry. We examine the conservation of residue type and residue function in these structurally conserved residue pairs. Additionally, enzymes often retain common mechanistic steps catalyzed by structurally conserved residues. We have examined these steps in the context of their overall reactions.

Binding Sites↗
PubMed2003

A template search reveals mechanistic similarities and differences in beta-ketoacyl synthases (KAS) and related enzymes.

A detailed comparison of the active sites in beta-ketoacyl synthases (KAS) and related enzymes has been made. Using three-dimensional templates of the three catalytic residues to scan the protein structural database reveals differences in both the geometry and the catalytic role of equivalent residues in different members of the family. The template based on the catalytic cysteine and two histidines in the KAS I and II is totally specific for this family, with no false hits. However, the role of the histidines in catalysis is different between KAS I/II and thiolase on the one hand and KAS III/chalcone synthase on the other. In contrast, a template comprising only cysteine and one histidine is not specific with many hits including members of the KAS family, metal binding sites, other active sites in nonhomologous proteins, and some "random" nonactive sites.

3-Oxoacyl-(Acyl-Carrier-Protein) Synthase↗
PubMed2003

Using a neural network and spatial clustering to predict the location of active sites in enzymes.

Structural genomics projects aim to provide a sharp increase in the number of structures of functionally unannotated, and largely unstudied, proteins. Algorithms and tools capable of deriving information about the nature, and location, of functional sites within a structure are increasingly useful therefore. Here, a neural network is trained to identify the catalytic residues found in enzymes, based on an analysis of the structure and sequence. The neural network output, and spatial clustering of the highly scoring residues are then used to predict the location of the active site.A comparison of the performance of differently trained neural networks is presented that shows how information from sequence and structure come together to improve the prediction accuracy of the network. Spatial clustering of the network results provides a reliable way of finding likely active sites. In over 69% of the test cases the active site is correctly predicted, and a further 25% are partially correctly predicted. The failures are generally due to the poor quality of the automatically generated sequence alignments. We also present predictions identifying the active site, and potential functional residues in five recently solved enzyme structures, not used in developing the method. The method correctly identifies the putative active site in each case. In most cases the likely functional residues are identified correctly, as well as some potentially novel functional groups.

Algorithms↗
PubMed2003

Diversity of protein-protein interactions.

In this review, we discuss the structural and functional diversity of protein-protein interactions (PPIs) based primarily on protein families for which three-dimensional structural data are available. PPIs play diverse roles in biology and differ based on the composition, affinity and whether the association is permanent or transient. In vivo, the protomer's localization, concentration and local environment can affect the interaction between protomers and are vital to control the composition and oligomeric state of protein complexes. Since a change in quaternary state is often coupled with biological function or activity, transient PPIs are important biological regulators. Structural characteristics of different types of PPIs are discussed and related to their physiological function, specificity and evolution.

Animals↗
PubMed2003

Using structural motif templates to identify proteins with DNA binding function.

This work describes a method for predicting DNA binding function from structure using 3-dimensional templates. Proteins that bind DNA using small contiguous helix-turn-helix (HTH) motifs comprise a significant number of all DNA-binding proteins. A structural template library of seven HTH motifs has been created from non-homologous DNA-binding proteins in the Protein Data Bank. The templates were used to scan complete protein structures using an algorithm that calculated the root mean squared deviation (rmsd) for the optimal superposition of each template on each structure, based on C(alpha) backbone coordinates. Distributions of rmsd values for known HTH-containing proteins (true hits) and non-HTH proteins (false hits) were calculated. A threshold value of 1.6 A rmsd was selected that gave a true hit rate of 88.4% and a false positive rate of 0.7%. The false positive rate was further reduced to 0.5% by introducing an accessible surface area threshold value of 990 A2 per HTH motif. The template library and the validated thresholds were used to make predictions for target proteins from a structural genomics project.

Algorithms↗
PubMed2003

Integrating structure, bioinformatics, and enzymology to discover function: BioH, a new carboxylesterase from Escherichia coli.

Structural proteomics projects are generating three-dimensional structures of novel, uncharacterized proteins at an increasing rate. However, structure alone is often insufficient to deduce the specific biochemical function of a protein. Here we determined the function for a protein using a strategy that integrates structural and bioinformatics data with parallel experimental screening for enzymatic activity. BioH is involved in biotin biosynthesis in Escherichia coli and had no previously known biochemical function. The crystal structure of BioH was determined at 1.7 A resolution. An automated procedure was used to compare the structure of BioH with structural templates from a variety of different enzyme active sites. This screen identified a catalytic triad (Ser82, His235, and Asp207) with a configuration similar to that of the catalytic triad of hydrolases. Analysis of BioH with a panel of hydrolase assays revealed a carboxylesterase activity with a preference for short acyl chain substrates. The combined use of structural bioinformatics with experimental screens for detecting enzyme activity could greatly enhance the rate at which function is determined from structure.

Biotin↗
PubMed2003

A novel approach to the recognition of protein architecture from sequence using Fourier analysis and neural networks.

A novel method is presented for the prediction of protein architecture from sequence using neural networks. The method involves the preprocessing of protein sequence data by numerically encoding it and then applying a Fourier transform. The encoded and transformed data are then used to train a neural network to recognize a number of different protein architectures. The method proved significantly better than comparable alternative strategies such as percentage dipeptide frequency, but is still limited by the size of the data set and the input demands of a neural network. Its main potential is as a complement to existing fold recognition techniques, with its ability to identify global symmetries within protein structures its greatest strength.

Algorithms↗
PubMed2003

Structural characterisation and functional significance of transient protein-protein interactions.

Protein-protein complexes that dissociate and associate readily, often depending on the physiological condition or environment, play an important role in many biological processes. In order to characterise these "transient" protein-protein interactions, two sets of complexes were collected and analysed. The first set consists of 16 experimentally validated "weak" transient homodimers, which are known to exist as monomers and dimers at physiological concentration, with dissociation constants in the micromolar range. A set of 23 functionally validated transient (i.e. intracellular signalling) heterodimers comprise the second set. This set includes complexes that are more stable, with nanomolar binding affinities, and require a molecular trigger to form and break the interaction. In comparison to more stable homodimeric complexes, the weak homodimers demonstrate smaller contact areas between protomers and the interfaces are more planar and polar on average. The physicochemical and geometrical properties of these weak homodimers more closely resemble those of non-obligate hetero-oligomeric complexes, whose components can exist either as monomers or as complexes in vivo. In contrast to the weak transient dimers, "strong" transient dimers often undergo large conformational changes upon association/dissociation and are characterised with larger, less planar and sometimes more hydrophobic interfaces. From sequence alignments we find that the interface residues of the weak transient homodimers are generally more conserved than surface residues, consistent with being constrained to maintain the protein-protein interaction during evolution. Protein families that include members with different oligomeric states or structures are identified, and found to exhibit a lower sequence conservation at the interface. The results are discussed in terms of the physiological function and evolution of protein-protein interactions.

Animals↗
PubMed2003

Gene3D: structural assignments for the biologist and bioinformaticist alike.

The Gene3D database (http://www.biochem.ucl.ac.uk/bsm/cath_new/Gene3D/) provides structural assignments for genes within complete genomes. These are available via the internet from either the World Wide Web or FTP. Assignments are made using PSI-BLAST and subsequently processed using the DRange protocol. The DRange protocol is an empirically benchmarked method for assessing the validity of structural assignments made using sequence searching methods where appropriate assignment statistics are collected and made available. Gene3D links assignments to their appropriate entries in relevent structural and classification resources (PDBsum, CATH database and the Dictionary of Homologous Superfamilies). Release 2.0 of Gene3D includes 62 genomes, 2 eukaryotes, 10 archaea and 40 bacteria. Currently, structural assignments can be made for between 30 and 40 percent of any given genome. In any genome, around half of those genes assigned a structural domain are assigned a single domain and the other half of the genes are assigned multiple structural domains. Gene3D is linked to the CATH database and is updated with each new update of CATH.

Animals↗
PubMed2003

Analysis of metabolic networks using a pathway distance metric through linear programming.

The solution of the shortest path problem in biochemical systems constitutes an important step for studies of their evolution. In this paper, a linear programming (LP) algorithm for calculating minimal pathway distances in metabolic networks is studied. Minimal pathway distances are identified as the smallest number of metabolic steps separating two enzymes in metabolic pathways. The algorithm deals effectively with circularity and reaction directionality. The applicability of the algorithm is illustrated by calculating the minimal pathway distances for Escherichia coli small molecule metabolism enzymes, and then considering their correlations with genome distance (distance separating two genes on a chromosome) and enzyme function (as characterised by enzyme commission number). The results illustrate the effectiveness of the LP model. In addition, the data confirm that propinquity of genes on the genome implies similarity in function (as determined by co-involvement in the same region of the metabolic network), but suggest that no correlation exists between pathway distance and enzyme function. These findings offer insight into the probable mechanism of pathway evolution.

Algorithms↗