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C Chothia

Publications and source records attributed to C Chothia.

At least 37 records · Page 2Linked to original sources
PubMed1999

The structure of a PKD domain from polycystin-1: implications for polycystic kidney disease.

Most cases of autosomal dominant polycystic kidney disease (ADPKD) are the result of mutations in the PKD1 gene. The PKD1 gene codes for a large cell-surface glycoprotein, polycystin-1, of unknown function, which, based on its predicted domain structure, may be involved in protein-protein and protein-carbohydrate interactions. Approximately 30% of polycystin-1 consists of 16 copies of a novel protein module called the PKD domain. Here we show that this domain has a beta-sandwich fold. Although this fold is common to a number of cell-surface modules, the PKD domain represents a distinct protein family. The tenth PKD domain of human and Fugu polycystin-1 show extensive conservation of surface residues suggesting that this region could be a ligand-binding site. This structure will allow the likely effects of missense mutations in a large part of the PKD1 gene to be determined.

Amino Acid Sequence↗
PubMed1999

SCOP: a Structural Classification of Proteins database.

The Structural Classification of Proteins (SCOP) database provides a detailed and comprehensive description of the relationships of all known proteins structures. The classification is on hierarchical levels: the first two levels, family and superfamily, describe near and far evolutionary relationships; the third, fold, describes geometrical relationships. The distinction between evolutionary relationships and those that arise from the physics and chemistry of proteins is a feature that is unique to this database, so far. The database can be used as a source of data to calibrate sequence search algorithms and for the generation of population statistics on protein structures. The database and its associated files are freely accessible from a number of WWW sites mirrored from URL http://scop. mrc-lmb.cam.ac.uk/scop/

Algorithms↗
PubMed1999

Advances in structural genomics.

New computational techniques have allowed protein folds to be assigned to all or parts of between a quarter (Caenorhabditis elegans) and a half (Mycoplasma genitalium) of the individual protein sequences in different genomes. These assignments give a new perspective on domain structures, gene duplications, protein families and protein folds in genome sequences.

Animals↗
PubMed1998

Sequence comparisons using multiple sequences detect three times as many remote homologues as pairwise methods.

The sequences of related proteins can diverge beyond the point where their relationship can be recognised by pairwise sequence comparisons. In attempts to overcome this limitation, methods have been developed that use as a query, not a single sequence, but sets of related sequences or a representation of the characteristics shared by related sequences. Here we describe an assessment of three of these methods: the SAM-T98 implementation of a hidden Markov model procedure; PSI-BLAST; and the intermediate sequence search (ISS) procedure. We determined the extent to which these procedures can detect evolutionary relationships between the members of the sequence database PDBD40-J. This database, derived from the structural classification of proteins (SCOP), contains the sequences of proteins of known structure whose sequence identities with each other are 40% or less. The evolutionary relationships that exist between those that have low sequence identities were found by the examination of their structural details and, in many cases, their functional features. For nine false positive predictions out of a possible 432,680, i.e. at a false positive rate of about 1/50,000, SAM-T98 found 35% of the true homologous relationships in PDBD40-J, whilst PSI-BLAST found 30% and ISS found 25%. Overall, this is about twice the number of PDBD40-J relations that can be detected by the pairwise comparison procedures FASTA (17%) and GAP-BLAST (15%). For distantly related sequences in PDBD40-J, those pairs whose sequence identity is less than 30%, SAM-T98 and PSI-BLAST detect three times the number of relationships found by the pairwise methods.

Databases, Factual↗
PubMed1998

Structural assignments to the Mycoplasma genitalium proteins show extensive gene duplications and domain rearrangements.

The parasitic bacterium Mycoplasma genitalium has a small, reduced genome with close to a basic set of genes. As a first step toward determining the families of protein domains that form the products of these genes, we have used the multiple sequence programs PSI-BLAST and GEANFAMMER to match the sequences of the 467 gene products of M. genitalium to the sequences of the domains that form proteins of known structure [Protein Data Bank (PDB) sequences]. PDB sequences (274) match all of 106 M. genitalium sequences and some parts of another 85; thus, 41% of its total sequences are matched in all or part. The evolutionary relationships of the PDB domains that match M. genitalium are described in the structural classification of proteins (SCOP) database. Using this information, we show that the domains in the matched M. genitalium sequences come from 114 superfamilies and that 58% of them have arisen by gene duplication. This level of duplication is more than twice that found by using pairwise sequence comparisons. The PDB domain matches also describe the domain structure of the matched sequences: just over a quarter contain one domain and the rest have combinations of two or more domains.

Bacterial Proteins↗
PubMed1998

SCOP, Structural Classification of Proteins database: applications to evaluation of the effectiveness of sequence alignment methods and statistics of protein structural data.

The Structural Classification of Proteins (SCOP) database provides a detailed and comprehensive description of the relationships of all known protein structures. The classification is on hierarchical levels: the first two levels, family and superfamily, describe near and far evolutionary relationships; the third, fold, describes geometrical relationships. The distinction between evolutionary relationships and those that arise from the physics and chemistry of proteins is a feature that is unique to this database, so far. The database can be used as a source of data to calibrate sequence search algorithms and for the generation of population statistics on protein structures. The database and its associated files are freely accessible from a number of WWW sites mirrored from URL http://scop. mrc-lmb.cam.ac.uk/scop/.

Algorithms↗
PubMed1998

Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships.

Pairwise sequence comparison methods have been assessed using proteins whose relationships are known reliably from their structures and functions, as described in the SCOP database [Murzin, A. G., Brenner, S. E., Hubbard, T. & Chothia C. (1995) J. Mol. Biol. 247, 536-540]. The evaluation tested the programs BLAST [Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. (1990). J. Mol. Biol. 215, 403-410], WU-BLAST2 [Altschul, S. F. & Gish, W. (1996) Methods Enzymol. 266, 460-480], FASTA [Pearson, W. R. & Lipman, D. J. (1988) Proc. Natl. Acad. Sci. USA 85, 2444-2448], and SSEARCH [Smith, T. F. & Waterman, M. S. (1981) J. Mol. Biol. 147, 195-197] and their scoring schemes. The error rate of all algorithms is greatly reduced by using statistical scores to evaluate matches rather than percentage identity or raw scores. The E-value statistical scores of SSEARCH and FASTA are reliable: the number of false positives found in our tests agrees well with the scores reported. However, the P-values reported by BLAST and WU-BLAST2 exaggerate significance by orders of magnitude. SSEARCH, FASTA ktup = 1, and WU-BLAST2 perform best, and they are capable of detecting almost all relationships between proteins whose sequence identities are >30%. For more distantly related proteins, they do much less well; only one-half of the relationships between proteins with 20-30% identity are found. Because many homologs have low sequence similarity, most distant relationships cannot be detected by any pairwise comparison method; however, those which are identified may be used with confidence.

Algorithms↗
PubMed1998

Structural determinants in the sequences of immunoglobulin variable domain.

To determine the general relation between the sequence and structure of variable domains of immunoglobulins we have carried out an analysis of their atomic structures, some 5300 different expressed sequences and the human germline gene segments. Variable domains are formed by two beta-sheets, packed face to face, and the inter-strand turns. Comparison of the different known structures shows that they have a core of 76 residues which has the same main-chain conformation in all structures. This common core contains almost all of the beta-sheet structure and three inter-strand turns. The regions that differ in conformation are the three hypervariable regions, three other inter-strand turns and a few adjacent residues. The 5300 expressed sequences currently known for variable domains were examined to determine the residues that occur at the 76 sites. Ignoring site conservations that occur for functional reasons, there are eight sites that have the same residue in almost all sequences; 12 that have one of a small group of very similar residues, and 52 where the chemical character of the residues is strongly conserved but not their volume. The role of residues at each site in the core was determined from the examination of their accessible surface areas, contacts, packing and buried side-chain hydrogen bonds. The most strongly conserved sites form the "deep" structure of the domain at the centre of the interface between the beta-sheets. It includes eight invariant sites and 11 sites that have one of a set of very similar residues. Around the deep structure there are buried hydrophobic residues that, in different variable domains, can differ greatly in volume. These differences in volume are accommodated by conformational changes in turn regions that are outside the common core. On the surface nearly all residues not involved in function or turn conformations strongly conserve hydrophilic or neutral residues. The implications of these results for the general relations between the sequence and structure of proteins are discussed.

CD2 Antigens↗
PubMed1998

Conformations of the third hypervariable region in the VH domain of immunoglobulins.

Antigen-combining sites of antibodies are constructed from six loops from VL and VH domains. The third hypervariable region of the heavy chain is far more variable than the others in length, sequence and structure, and was not included in the canonical-structure description of the conformational repertoire of the three hypervariable regions of V kappa chains and the first two of VH chains. Here we present an analysis of the conformations of the third hypervariable region of VH domains (the H3 regions) in antibodies of known structure. We define the H3 region as comprising the residues between 92Cys and 104Gly. We divide it into a torso comprising residues proximal to the framework, four residues from the N terminus and six residues from the C terminus, and a head. There are two major classes of H3 structures that have more than ten residues between 92Cys and 104Gly: (1) the conformation of the torso has a beta-bulge at residue 101, and (2) the torso does not contain a bulge, but continues the regular hydrogen-bonding pattern of the beta-sheet hairpin. The choice of bulged versus non-bulged torso conformation is dictated primarily by the sequence, through the formation of a salt bridge between the side-chains of an Arg or Lys at position 94 and an Asp at position 101. Thus the torso region appears to have a limited repertoire of conformations, as in the canonical structure model of other antigen-binding loops. The heads or apices of the loops have a very wide variety of conformations. In shorter H3 regions, and in those containing the non-bulged torso conformation, the heads follow the rules relating sequence to structure in short hairpins. We surveyed the heads of longer H3 regions, finding that those with bulged torsos present many very different conformations of the head. We recognize that H3, unlike the other five antigen-binding loops, has a conformation that depends strongly on the environment, and we have analysed the interactions of H3 with residues elsewhere in the VH domain, in the VL domain, and with ligands, and their effects on the conformation of H3. We tested these results by attempts to predict the conformations of H3 regions in antibody structures solved after the results were derived. The general conclusion of this work is that the conformation of H3 shows some regularities, from which rules relating sequence to conformation can be stated, but to a less complete degree than for the other five antigen-binding loops. Accurate prediction of the torso conformation is possible in most cases; predictions of the conformation of the head is possible in some cases. However, our understanding of the sequence-structure relationships has reduced the uncertainty to no more than a few residues at the apex of the H3 region.

Amino Acid Sequence↗
PubMed1997

Standard conformations for the canonical structures of immunoglobulins.

A comparative analysis of the main-chain conformation of the L1, L2, L3, H1 and H2 hypervariable regions in 17 immunoglobulin structures that have been accurately determined at high resolution is described. This involves 79 hypervariable regions in all. We also analysed a part of the H3 region in 12 of the 15 VH domains considered here. On the basis of the residues at key sites the 79 hypervariable regions can be assigned to one of 18 different canonical structures. We show that 71 of these hypervariable regions have a conformation that is very close to what can be defined as a "standard" conformation of each canonical structure. These standard conformations are described in detail. The other eight hypervariable regions have small deviations from the standard conformations that, in six cases, involve only the rotation of a single peptide group. Most H3 hypervariable regions have the same conformation in the part that is close to the framework and the details of this conformation are also described here.

Binding Sites↗
PubMed1997

Intermediate sequences increase the detection of homology between sequences.

Two homologous sequences, which have diverged beyond the point where their homology can be recognised by a simple direct comparison, can be related through a third sequence that is suitably intermediate between the two. High scores, for a sequence match between the first and third sequences and between the second and the third sequences, imply that the first and second sequences are related even though their own match score is low. We have tested the usefulness of this idea using a database that contains the sequences of 971 protein domains whose structures are known and whose residue identities with each other are some 40% or less (PDB40D). On the basis of sequence and structural information, 2143 pairs of these sequences are known to have an evolutionary relationship. FASTA, in an all-against-all comparison of the sequences in the database, detected 320 (15%) of these relationships as well as three false positive (i.e. 1% error rate). Using intermediate sequences found by FASTA matches of PDB40D sequences to those in the large non-redundant OWL database we could detect 550 evolutionary relationships with an error rate of 1%. This means the intermediate sequence procedure increases the ability to recognise the evolutionary relationships amongst the PDB40D sequences by 70%.

Amino Acid Sequence↗
PubMed1997

SCOP: a structural classification of proteins database.

The Structural Classification of Proteins (SCOP) database provides a detailed and comprehensive description of the relationships of all known proteins structures. The classification is on hierarchical levels: the first two levels, family and superfamily, describe near and far evolutionary relationships; the third, fold, describes geometrical relationships. The distinction between evolutionary relationships and those that arise from the physics and chemistry of proteins is a feature that is unique to this database, so far. SCOP also provides for each structure links to atomic co-ordinates, images of the structures, interactive viewers, sequence data, data on any conformational changes related to function and literature references. The database is freely accessible on the World Wide Web (WWW) with an entry point at URL http://scop.mrc-lmb.cam.ac.uk/scop/

Amino Acid Sequence↗
PubMed1997

Antibody structure, prediction and redesign.

So far the difficulty to predict the structure of the third hypervariable loop of the heavy chain of antibodies has represented the main limitation in modelling the complete antigen binding site. We carefully analysed all available structures of immunoglobulins searching for rules relating the loop conformation to its amino acid sequence. Here, we analyse the conformation of this loop and show that we are able to predict the conformation of the ten residues proximal to the framework. The conformation of the remaining residues of loops longer than 10 residues can also be predicted in many cases. This, combined with the previously defined canonical structures for the other five hypervariable loops, is an important step toward the prediction of the complete immunoglobulin antigen-binding site. We exemplify our prediction protocol using three known immunoglobulin structures as test cases.

Amino Acid Sequence↗
PubMed1997

Population statistics of protein structures: lessons from structural classifications.

Structural classifications aid the interpretation of proteins by describing degrees of structural and evolutionary relatedness. They have also recently revealed strikingly skewed distributions at all levels; for example, a small number of folds are far more common than others, and just a few superfamilies are known to have diverged widely. The classifications also provide an indication of the total number of superfamilies in nature.

Binding Sites↗
PubMed1997

Comparative analysis of the polycystic kidney disease 1 (PKD1) gene reveals an integral membrane glycoprotein with multiple evolutionary conserved domains.

PKD1 is the major locus of the common genetic disorder autosomal dominant polycystic kidney disease (ADPKD). Analysis of the predicted protein sequence of the human PKD1 gene, polycystin, shows a large molecule with a unique arrangement of extracellular domains and multiple putative transmembrane regions. The precise function of polycystin remains unclear with a paucity of mutations to define key structural and functional domains. To refine the structure of this protein we have cloned the genomic region encoding the Fugu PKD1 gene. Fugu PKD1 spans 36 kb of genomic DNA and has greater complexity with 54 exons compared with 46 in man. Comparative analysis of the predicted protein sequences shows a lower level of homology than in similar studies with identity of 40 and 59% similarity. However key structural motifs including leucine rich repeats (LRR), a C-type lectin and LDL-A like domains and 16 PKD repeats are maintained. A region of homology with the sea urchin REJ protein was also confirmed in Fugu but found to extend over 1000 amino acids. Several highly conserved intra- and extra-cellular regions, with no known sequence homologies, that are likely to be of functional importance were detected. The likely structure of the membrane associated region has been refined with similarity to the PKD2 protein and voltage gated Ca2+ and Na+ channels highlighted over part of this area. The overall protein structure has therefore been clarified and this comparative analysis derived structure will form the basis for the functional study of polycystin and its individual domains.

Amino Acid Sequence↗
PubMed1997

The molecular structure of cell adhesion molecules.

Considerable advances have been made in our knowledge of the molecular structure of cell adhesion molecules, their binding sites, and adhesion complexes. For the cadherins, protein zero, and CD2, additional experimental data support the insights obtained from structural analysis of their domains and molecular models of their adhesion complexes. For neural cell adhesion molecules, L1, fibronectin, tenascin-C, integrins, and vascular cell adhesion molecules, the molecular structure of domains, and in most cases their binding sites, have been elucidated. The substrate recognition sites in some of these molecules possess rate constants for association and dissociation that permit both rapid cell migration and, through avidity, high-affinity cell-cell interactions.

Animals↗
PubMed1997

Protein folds in the all-beta and all-alpha classes.

Analysis of the structures in the Protein Databank, released in June 1996, shows that the number of different protein folds, i.e. the number of different arrangements of major secondary structures and/or chain topologies, is 327. Of these folds, approximately 25% belong to the all-alpha class, 20% belong to the all-beta class, 30% belong to the alpha/beta class, and 25% belong to the alpha + beta class. We describe the types of folds now known for the all-beta and all-alpha classes, emphasizing those that have been discovered recently. Detailed theories for the physical determinants of the structures of most of these folds now exist, and these are reviewed.

Databases, Factual↗