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A E Todd

Publications and source records attributed to A E Todd.

11 recordsLinked to original sources

Evolution of function in protein superfamilies, from a structural perspective.

The recent growth in protein databases has revealed the functional diversity of many protein superfamilies. We have assessed the functional variation of homologous enzyme superfamilies containing two or more enzymes, as defined by the CATH protein structure classification, by way of the Enzyme Commission (EC) scheme. Combining sequence and structure information to identify relatives, the majority of superfamilies display variation in enzyme function, with 25 % of superfamilies in the PDB having members of different enzyme types. We determined the extent of functional similarity at different levels of sequence identity for 486,000 homologous pairs (enzyme/enzyme and enzyme/non-enzyme), with structural and sequence relatives included. For single and multi-domain proteins, variation in EC number is rare above 40 % sequence identity, and above 30 %, the first three digits may be predicted with an accuracy of at least 90 %. For more distantly related proteins sharing less than 30 % sequence identity, functional variation is significant, and below this threshold, structural data are essential for understanding the molecular basis of observed functional differences. To explore the mechanisms for generating functional diversity during evolution, we have studied in detail 31 diverse structural enzyme superfamilies for which structural data are available. A large number of variations and peculiarities are observed, at the atomic level through to gross structural rearrangements. Almost all superfamilies exhibit functional diversity generated by local sequence variation and domain shuffling. Commonly, substrate specificity is diverse across a superfamily, whilst the reaction chemistry is maintained. In many superfamilies, the position of catalytic residues may vary despite playing equivalent functional roles in related proteins. The implications of functional diversity within supefamilies for the structural genomics projects are discussed. More detailed information on these superfamilies is available at http://www.biochem.ucl.ac.uk/bsm/FAM-EC/.

Binding Sites↗

A rapid classification protocol for the CATH Domain Database to support structural genomics.

In order to support the structural genomic initiatives, both by rapidly classifying newly determined structures and by suggesting suitable targets for structure determination, we have recently developed several new protocols for classifying structures in the CATH domain database (http://www.biochem.ucl.ac.uk/bsm/cath). These aim to increase the speed of classification of new structures using fast algorithms for structure comparison (GRATH) and to improve the sensitivity in recognising distant structural relatives by incorporating sequence information from relatives in the genomes (DomainFinder). In order to ensure the integrity of the database given the expected increase in data, the CATH Protein Family Database (CATH-PFDB), which currently includes 25,320 structural domains and a further 160,000 sequence relatives has now been installed in a relational ORACLE database. This was essential for developing more rigorous validation procedures and for allowing efficient querying of the database, particularly for genome analysis. The associated Dictionary of Homologous Superfamilies [Bray,J.E., Todd,A.E., Pearl,F.M.G., Thornton,J.M. and Orengo,C.A. (2000) Protein Eng., 13, 153-165], which provides multiple structural alignments and functional information to assist in assigning new relatives, has also been expanded recently and now includes information for 903 homologous superfamilies. In order to improve coverage of known structures, preliminary classification levels are now provided for new structures at interim stages in the classification protocol. Since a large proportion of new structures can be rapidly classified using profile-based sequence analysis [e.g. PSI-BLAST: Altschul,S.F., Madden,T.L., Schaffer,A.A., Zhang,J., Zhang,Z., Miller,W. and Lipman,D.J. (1997) Nucleic Acids Res., 25, 3389-3402], this provides preliminary classification for easily recognisable homologues, which in the latest release of CATH (version 1.7) represented nearly three-quarters of the non-identical structures.

Computational Biology↗

Assigning genomic sequences to CATH.

We report the latest release (version 1.6) of the CATH protein domains database (http://www.biochem.ucl. ac.uk/bsm/cath ). This is a hierarchical classification of 18 577 domains into evolutionary families and structural groupings. We have identified 1028 homo-logous superfamilies in which the proteins have both structural, and sequence or functional similarity. These can be further clustered into 672 fold groups and 35 distinct architectures. Recent developments of the database include the generation of 3D templates for recognising structural relatives in each fold group, which has led to significant improvements in the speed and accuracy of updating the database and also means that less manual validation is required. We also report the establishment of the CATH-PFDB (Protein Family Database), which associates 1D sequences with the 3D homologous superfamilies. Sequences showing identifiable homology to entries in CATH have been extracted from GenBank using PSI-BLAST. A CATH-PSIBLAST server has been established, which allows you to scan a new sequence against the database. The CATH Dictionary of Homologous Superfamilies (DHS), which contains validated multiple structural alignments annotated with consensus functional information for evolutionary protein superfamilies, has been updated to include annotations associated with sequence relatives identified in GenBank. The DHS is a powerful tool for considering the variation of functional properties within a given CATH superfamily and in deciding what functional properties may be reliably inherited by a newly identified relative.

Amino Acid Sequence↗

From structure to function: approaches and limitations.

This review presents a summary of current approaches to extract functional information from structural data on proteins and their complexes. While structural homologs may reveal possible biochemical functions (which may be hidden at the sequence level), elucidating the exact biological role of a protein in vivo will only be possible by including other results, such as data on expression and localization.

Binding Sites↗

Using the CATH domain database to assign structures and functions to the genome sequences.

The CATH database of protein structures contains approximately 18000 domains organized according to their (C)lass, (A)rchitecture, (T)opology and (H)omologous superfamily. Relationships between evolutionary related structures (homologues) within the database have been used to test the sensitivity of various sequence search methods in order to identify relatives in Genbank and other sequence databases. Subsequent application of the most sensitive and efficient algorithms, gapped blast and the profile based method, Position Specific Iterated Basic Local Alignment Tool (PSI-BLAST), could be used to assign structural data to between 22 and 36 % of microbial genomes in order to improve functional annotation and enhance understanding of biological mechanism. However, on a cautionary note, an analysis of functional conservation within fold groups and homologous superfamilies in the CATH database, revealed that whilst function was conserved in nearly 55% of enzyme families, function had diverged considerably, in some highly populated families. In these families, functional properties should be inherited far more cautiously and the probable effects of substitutions in key functional residues carefully assessed.

Algorithms↗

The CATH Dictionary of Homologous Superfamilies (DHS): a consensus approach for identifying distant structural homologues.

A consensus approach has been developed for identifying distant structural homologues. This is based on the CATH Dictionary of Homologous Superfamilies (DHS), a database of validated multiple structural alignments annotated with consensus functional information for evolutionary protein superfamilies (URL: http://www. biochem.ucl.ac.uk/bsm/dhs). Multiple structural alignments have been generated for 362 well-populated superfamilies in the CATH structural domain database and annotated with secondary structure, physicochemical properties, functional sequence patterns and protein-ligand interaction data. Consensus functional information for each superfamily includes descriptions and keywords extracted from SWISS-PROT and the ENZYME database. The Dictionary provides a powerful resource to validate, examine and visualize key structural and functional features of each homologous superfamily. The value of the DHS, for assessing functional variability and identifying distant evolutionary relationships, is illustrated using the pyridoxal-5'-phosphate (PLP) binding aspartate aminotransferase superfamily. The DHS also provides a tool for examining sequence-structure relationships for proteins within each fold group.

Amino Acid Sequence↗

Protein folds, functions and evolution.

The evolution of proteins and their functions is reviewed from a structural perspective in the light of the current database. Protein domain families segregate unequally between the three major classes, the 32 different architectures and almost 700 folds observed to date. We find that the number of new topologies is still increasing, although 25 new structures are now determined for each new topology. The corresponding analysis and classification of function is only just beginning, fuelled by the genome data. The structural data revealed unexpected conservations and divergence of function both within and between families. The next five years will see the compilation of a definitive dictionary of protein families and their related functions, based on structural data which reveals relationships hidden at the sequence level. Such information will provide the foundation to build a better understanding of the molecular basis of biological complexity and hopefully to facilitate rational molecular design.

Animals↗

The CATH Database provides insights into protein structure/function relationships.

We report the latest release (version 1.4) of the CATH protein domains database (http://www.biochem.ucl.ac.uk/bsm/cath). This is a hierarchical classification of 13 359 protein domain structures into evolutionary families and structural groupings. We currently identify 827 homologous families in which the proteins have both structual similarity and sequence and/or functional similarity. These can be further clustered into 593 fold groups and 32 distinct architectures. Using our structural classification and associated data on protein functions, stored in the database (EC identifiers, SWISS-PROT keywords and information from the Enzyme database and literature) we have been able to analyse the correlation between the 3D structure and function. More than 96% of folds in the PDB are associated with a single homologous family. However, within the superfolds, three or more different functions are observed. Considering enzyme functions, more than 95% of clearly homologous families exhibit either single or closely related functions, as demonstrated by the EC identifiers of their relatives. Our analysis supports the view that determining structures, for example as part of a 'structural genomics' initiative, will make a major contribution to interpreting genome data.

Algorithms↗

From protein structure to function.

Several databases of protein structural families now exist-organised according to both evolutionary relationships and common folding arrangements. Although these lag behind sequence databases in size, the prospect of structural genomics initiatives means that they may soon include representatives of many of the sequence families. To some extent, functional information can be derived from structural similarity. For some structural families, their function is highly conserved, whereas, for others, it can only be inherited or derived on the basis of additional information (e.g. sequence patterns, common residue clusters and characteristic surface properties).

Computational Biology↗

Evolution of protein function, from a structural perspective.

The recent growth in structural data, and ensuing analyses, have revealed the structural and functional versatility of protein families. With respect to enzymes, local active-site mutations, variations in surface loops and recruitment of additional domains accommodate the diverse substrate specificities and catalytic activities observed within several superfamilies. Conversely, some functions have more than one structural solution, having evolved independently several times during evolution. Combined with the existence of multi-functional genes, which have arisen by gene recruitment, these phenomena must be considered in the process of genome annotation.

Animals↗

DOMPLOT: a program to generate schematic diagrams of the structural domain organization within proteins, annotated by ligand contacts.

A program is described for automatically generating schematic linear representations of protein chains in terms of their structural domains. The program requires the co-ordinates of the chain, the domain assignment, PROSITE information and a file listing all intermolecular interactions in the protein structure. The output is a PostScript file in which each protein is represented by a set of linked boxes, each box corresponding to all or part of a structural domain. PROSITE motifs and residues involved in ligand interactions are highlighted. The diagrams allow immediate visualization of the domain arrangement within a protein chain, and by providing information on sequence motifs, and metal ion, ligand and DNA binding at the domain level, the program facilitates detection of remote evolutionary relationships between proteins.

Adenosine Diphosphate↗