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Janet M Thornton

Publications and source records attributed to Janet M Thornton.

70 records · Page 4Linked to original sources
PubMed2003

From protein structure to biochemical function?

Here we describe various methods currently under development aimed at identifying a protein's function from its three-dimensional structure. We are combining a number of these methods to create a pipeline of applications, called ProFunc, which will take a given 3D structure, run all the applications on it and compile and summarise the results obtained. The aim is to provide a best guess as to the protein's function from the evidence provided by the different methods. Here we present three examples, using structures solved by the Midwest Center for Structural Genomics consortium, illustrating the strengths and weaknesses of current approaches.

Amino Acid Sequence↗
PubMed2002

Analysis of catalytic residues in enzyme active sites.

We present an analysis of the residues directly involved in catalysis in 178 enzyme active sites. Specific criteria were derived to define a catalytic residue, and used to create a catalytic residue dataset, which was then analysed in terms of properties including secondary structure, solvent accessibility, flexibility, conservation, quaternary structure and function. The results indicate the dominance of a small set of amino acid residues in catalysis and give a picture of a general active site environment. It is hoped that this information will provide a better understanding of the molecular mechanisms involved in catalysis and a heuristic basis for predicting catalytic residues in enzymes of unknown function.

Amino Acid Sequence↗
PubMed2002

One fold with many functions: the evolutionary relationships between TIM barrel families based on their sequences, structures and functions.

The eightfold (betaalpha) barrel structure, first observed in triose-phosphate isomerase, occurs ubiquitously in nature. It is nearly always an enzyme and most often involved in molecular or energy metabolism within the cell. In this review we bring together data on the sequence, structure and function of the proteins known to adopt this fold. We highlight the sequence and functional diversity in the 21 homologous superfamilies, which include 76 different sequence families. In many structures, the barrels are "mixed and matched" with other domains generating additional variety. Global and local structure-based alignments are used to explore the distribution of the associated functional residues on this common structural scaffold. Many of the substrates/co-factors include a phosphate moiety, which is usually but not always bound towards the C-terminal end of the sequence. Some, but not all, of these structures, exhibit a structurally conserved "phosphate binding motif". In contrast metal-ligating residues and catalytic residues are distributed along the sequence. However, we also found striking structural superposition of some of these residues. Lastly we consider the possible evolutionary relationships between these proteins, whose sequences are so diverse that even the most powerful approaches find few relationships, yet whose active sites all cluster at one end of the barrel. This extreme example of the "one fold-many functions" paradigm illustrates the difficulty of assigning function through a structural genomics approach for some folds.

Aldose-Ketose Isomerases↗
PubMed2002

Toward predicting protein topology: an approach to identifying beta hairpins.

Although secondary structure prediction methods have recently improved, progress from secondary to tertiary structure prediction has been limited. A promising but largely unexplored route to this goal is to predict structure motifs from secondary structure knowledge. Here we present a novel method for the recognition of beta hairpins that combines secondary structure predictions and threading methods by using a database search and a neural network approach. The method successfully predicts 48 and 77%, respectively, of all of hairpin and nonhairpin beta-coil-beta motifs in a protein database. We find that the main contributors to motif recognition are predicted accessibility and turn propensities.

Databases, Factual↗
PubMed2002

Prediction of strand pairing in antiparallel and parallel beta-sheets using information theory.

An information theory approach was developed to predict the alignment of interacting antiparallel and parallel beta-strands. Information scores were derived for the preference of a residue on a beta-strand to be opposite a sequence of residues on an adjacent beta-strand. These scores were used to predict the interstrand register of interacting beta-strands from 10 alternative offset positions either side of the experimentally observed beta-sheet register. The amino acid sequence of an internal beta-strand can be correctly aligned with two beta-strands in a fixed position either side of the strand in 45% of antiparallel and 48% of parallel arrangements. For comparison, when another beta-strand from a nonhomologous protein substitutes the internal beta-strand, the same register is predicted for only 24 and 36% of antiparallel and parallel arrangements. As expected, alignment of a single fixed strand with just a second beta-strand sequence was more difficult, and gave a correct register in 31 and 37% of antiparallel and parallel beta-pairs, respectively. These scores are 10% higher than for two randomly selected beta-strand sequences. In general, prediction accuracy was not improved by information tables that distinguished hydrogen-bonding patterns or beta-strand order. These results will contribute to predicting the arrangement of beta-strands in beta-pleated sheets and protein topology.

Amino Acid Sequence↗
PubMed2002

Protein-DNA interactions: amino acid conservation and the effects of mutations on binding specificity.

We investigate the conservation of amino acid residue sequences in 21 DNA-binding protein families and study the effects that mutations have on DNA-sequence recognition. The observations are best understood by assigning each protein family to one of three classes: (i) non-specific, where binding is independent of DNA sequence; (ii) highly specific, where binding is specific and all members of the family target the same DNA sequence; and (iii) multi-specific, where binding is also specific, but individual family members target different DNA sequences. Overall, protein residues in contact with the DNA are better conserved than the rest of the protein surface, but there is a complex underlying trend of conservation for individual residue positions. Amino acid residues that interact with the DNA backbone are well conserved across all protein families and provide a core of stabilising contacts for homologous protein-DNA complexes. In contrast, amino acid residues that interact with DNA bases have variable levels of conservation depending on the family classification. In non-specific families, base-contacting residues are well conserved and interactions are always found in the minor groove where there is little discrimination between base types. In highly specific families, base-contacting residues are highly conserved and allow member proteins to recognise the same target sequence. In multi-specific families, base-contacting residues undergo frequent mutations and enable different proteins to recognise distinct target sequences. Finally, we report that interactions with bases in the target sequence often follow (though not always) a universal code of amino acid-base recognition and the effects of amino acid mutations can be most easily understood for these interactions.

Amino Acid Sequence↗
PubMed2002

Homology, pathway distance and chromosomal localization of the small molecule metabolism enzymes in Escherichia coli.

Here, we analyse Escherichia coli enzymes involved in small molecule metabolism (SMM). We introduce the concept of pathway distance as a measure of the number of distinct metabolic steps separating two SMM enzymes, and we consider protein homology (as determined by assigning enzymes to structural and sequence families) and gene interval (the number of genes separating two genes on the E. coli chromosome). The relationships between these three contexts (pathway distance, homology and chromosomal localisation) is investigated extensively. We make use of these relationships to suggest possible SMM evolution mechanisms. Homology between enzyme pairs close in the SMM was higher than expected by chance but was still rare. When observed, homologues usually conserved their reaction mechanism and/or co-factor binding rather than shared substrate binding. The correlation between pathway distance and gene intervals was clear. Enzymes catalysing nearby SMM reactions were usually encoded by genes close by on the E. coli chromosome. We found many co-regulated blocks of three to four genes (usually non-homologous) encoding enzymes occurring within four metabolic steps of one another; nearly all of these blocks formed part of known or predicted operons. The "inline reuse" of enzymes (i.e. the use of the same enzyme to catalyse two or more different steps of a metabolic pathway) is also discussed: of these enzymes, four were multifunctional (i.e. catalysed a different reaction in each instance), nine had multiple substrate specificity (i.e. catalysed the same reaction on different substrates in each instance) and one catalysed the same reaction on the same substrate but as part of two different complexes. We also identified 59 sets of isozymic proteins most commonly duplicated to function under different conditions, or with a different preferred substrate or minor substrate. In addition to transcriptional units, isozymes and inline reuse of enzymes provide mechanisms for controlling the SMM network. Our data suggest that several pathway evolution mechanisms may occur in concert, although chemistry-driven duplication/recruitment is favoured. SMM exploits regulatory strategies involving chromosomal location, isozymes and the reuse of enzymes.

Chromosomes, Bacterial↗
PubMed2002

Wavelet transforms for the characterization and detection of repeating motifs.

The role of repeating motifs in protein structures is thought to be as modular building blocks which allow an economic way of constructing complex proteins. In this work novel wavelet transform analysis techniques are used to detect and characterize repeating motifs in protein sequence and structure data, where the Kyte-Doolittle hydrophobicity scale (Eta Phi) and relative accessible surface area (rASA) data provide residue information about the protein sequence and structure, respectively. We analyze a variety of repeating protein motifs, TIM barrels, propellor blades, coiled coils and leucine-rich repeat structures. Detection and characterization of these motifs is performed using techniques based on the continuous wavelet transform (CWT). Results indicate that the wavelet transform techniques developed herein are a promising approach for the detection and characterization of repeating motifs for both structural and in some instances sequence data.

Algorithms↗
PubMed2002

Integrating mutation data and structural analysis of the TP53 tumor-suppressor protein.

TP53 encodes p53, which is a nuclear phosphoprotein with cancer-inhibiting properties. In response to DNA damage, p53 is activated and mediates a set of antiproliferative responses including cell-cycle arrest and apoptosis. Mutations in the TP53 gene are associated with more than 50% of human cancers, and 90% of these affect p53-DNA interactions, resulting in a partial or complete loss of transactivation functions. These mutations affect the structural integrity and/or p53-DNA interactions, leading to the partial or complete loss of the protein's function. We report here the results of a systematic automated analysis of the effects of p53 mutations on the structure of the core domain of the protein. We found that 304 of the 882 (34.4%) distinct mutations reported in the core domain can be explained in structural terms by their predicted effects on protein folding or on protein-DNA contacts. The proportion of "explained" mutations increased to 55.6% when substitutions of evolutionary conserved amino acids were included. The automated method of structural analysis developed here may be applied to other frequently mutated gene mutations such as dystrophin, BRCA1, and G6PD.

Amino Acid Substitution↗
PubMed2002

Pathway evolution, structurally speaking.

Small-molecule metabolism forms the core of the metabolic processes of all living organisms. As early as 1945, possible mechanisms for the evolution of such a complex metabolic system were considered. The problem is to explain the appearance and development of a highly regulated complex network of interacting proteins and substrates from a limited structural and functional repertoire. By permitting the co-analysis of phylogeny and metabolism, the combined exploitation of pathway and structural databases, as well as the use of multiple-sequence alignment search algorithms, sheds light on this problem. Much of the current research suggests a chemistry-driven 'patchwork' model of pathway evolution, but other mechanisms may play a role. In the future, as metabolic structure and sequence space are further explored, it should become easier to trace the finer details of pathway development and understand how complexity has evolved.

Amino Acid Sequence↗
PubMed2002

Plasticity of enzyme active sites.

The expectation is that any similarity in reaction chemistry shared by enzyme homologues is mediated by common functional groups conserved through evolution. However, detailed enzyme studies have revealed the flexibility of many active sites, in that different functional groups, unconserved with respect to position in the primary sequence, mediate the same mechanistic role. Nevertheless, the catalytic atoms might be spatially equivalent. More rarely, the active sites have completely different locations in the protein scaffold. This variability could result from: (1) the hopping of functional groups from one position to another to optimize catalysis; (2) the independent specialization of a low-activity primordial enzyme in different phylogenetic lineages; (3) functional convergence after evolutionary divergence; or (4) circular permutation events.

Amino Acid Sequence↗
PubMed2002

Sequence and structural differences between enzyme and nonenzyme homologs.

To improve our understanding of the evolution of novel functions, we performed a sequence, structural, and functional analysis of homologous enzymes and nonenzymes of known three-dimensional structure. In most examples identified, the nonenzyme is derived from an ancestral catalytic precursor (as opposed to the reverse evolutionary scenario, nonenzyme to enzyme), and the active site pocket has been disrupted in some way, owing to the substitution of critical catalytic residues and/or steric interactions that impede substrate binding and catalysis. Pairwise sequence identity is typically insignificant, and almost one-half of the enzyme and nonenzyme pairs do not share any similarity in function. Heterooligomeric enzymes comprising homologous subunits in which one chain is catalytically inactive and enzyme polypeptides that contain internal catalytic and noncatalytic duplications of an ancient enzyme domain are also discussed.

Biopolymers↗
PubMed2002

Gene3D: structural assignment for whole genes and genomes using the CATH domain structure database.

We present a novel web-based resource, Gene3D, of precalculated structural assignments to gene sequences and whole genomes. This resource assigns structural domains from the CATH database to whole genes and links these to their curated functional and structural annotations within the CATH domain structure database, the functional Dictionary of Homologous Superfamilies (DHS) and PDBsum. Currently Gene3D provides annotation for 36 complete genomes (two eukaryotes, six archaea, and 28 bacteria). On average, between 30% and 40% of the genes of a given genome can be structurally annotated. Matches to structural domains are found using the profile-based method (PSI-BLAST). and a novel protocol, DRange, is used to resolve conflicts in matches involving different homologous superfamilies.

Animals↗
PubMed2002

The CATH protein family database: a resource for structural and functional annotation of genomes.

Over the last decade, there have been huge increases in the numbers of protein sequences and structures determined. In parallel, many methods have been developed for recognising similarities between these proteins, arising from their common evolutionary background, and for clustering such relatives into protein families. Here we review some of the protein family resources available to the biologist and describe how these can be used to provide structural and functional annotations for newly determined sequences. In particular we describe recent developments to the CATH domain database of protein structural families which have facilitated genome annotation and which have also revealed important caveats that must be considered when transferring functional data between homologous proteins.

Databases, Protein↗
PubMedDate not supplied

Target selection and determination of function in structural genomics.

The first crucial step in any structural genomics project is the selection and prioritization of target proteins for structure determination. There may be a number of selection criteria to be satisfied, including that the proteins have novel folds, that they be representatives of large families for which no structure is known, and so on. The better the selection at this stage, the greater is the value of the structures obtained at the end of the experimental process. This value can be further enhanced once the protein structures have been solved if the functions of the given proteins can also be determined. Here we describe the methods used at either end of the experimental process: firstly, sensitive sequence comparison techniques for selecting a high-quality list of target proteins, and secondly the various computational methods that can be applied to the eventual 3D structures to determine the most likely biochemical function of the proteins in question.

Amino Acid Motifs↗