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J M Thornton

Publications and source records attributed to J M Thornton.

At least 163 records · Page 9Linked to original sources
PubMed1991

Modelling antibody combining sites: a review.

The combining site in an antibody is built up from six hypervariable loop regions, three from the light chain and three from the heavy chain. Three-dimensional structures have been elucidated by X-ray crystallographic studies for a variety of combining sites and for four protein-antibody complexes. Since sequence determination is relatively straightforward, whilst structure determination is often difficult and time consuming, it would be useful to be able to predict the structure of a combining site from its sequence. Knowledge of the structure would facilitate modifications of antibodies for specific aims. The structure of an antibody combining site for which only the sequence is known can be modelled on the basis of homology with a protein of known structure. The most demanding steps are modelling of the hypervariable loops and inclusion of the amino acid side chains. Final energy refinement of the model is achieved by conventional energy minimization techniques, but simulated annealing promises to be a powerful way of predicting side chain conformation. Four different groups have modelled antibody combining sites and compared their predictions with observed structures: for the main chain conformations resolutions of less than 1 A have been achieved. Future developments will increase the efficiency of the modelling procedures and permit accurate predictions of side chain conformations.

Binding Sites, Antibody↗
PubMed1991

Structure prediction and modelling.

Protein structure prediction from sequence remains a major goal in molecular biology. The methods described in this review concentrate on deriving structural information through the detection of similarities between a test sequence and a database of known structures. Such methods are often referred to as knowledge-based strategies reflecting the use of a structural database in the analyses. The past year has seen considerable advances in both the development of automated procedures and their application to protein sequences of outstanding biological interest.

Algorithms↗
PubMed1991

A novel method for the modelling of peptide ligands to their receptors.

A knowledge-based approach to the modelling of enzyme-peptide inhibitor complexes is described. Given the structure of an enzyme, and knowledge of its binding site, the method seeks to predict the binding geometry of a peptide ligand. This novel method involves using examples of side-chain packing derived from proteins of known three-dimensional structure to define possible packing arrangements of a peptide inhibitor group to its binding site. A suite of programs, GEMINI, was written and used to predict the packing of pairs of amino acid groups from three inhibitors complexed to their enzymes for which the X-ray structures were available. These included the Phe group of the inhibitor H142 bound to endothiapepsin, the Leu group of CLT complexed to thermolysin and the C-terminus of Gly-L-Tyr bound to carboxypeptidase A. A detailed comparison of the modelled and observed inhibitor coordinates was made. This approach may be extended to modelling other types of protein interactions.

Aspartic Acid Endopeptidases↗
PubMed1990

SIRIUS. An automated method for the analysis of the preferred packing arrangements between protein groups.

Automated methods have been developed to determine the preferred packing arrangement between interacting protein groups. A suite of FORTRAN programs, SIRIUS, is described for calculating and analysing the geometries of interacting protein groups using crystallographically derived atomic co-ordinates. The programs involved in calculating the geometries search for interacting pairs of protein groups using a distance criterion, and then calculate the spatial disposition and orientation of the pair. The second set of programs is devoted to analysis. This involves calculating the observed and expected distributions of the angles and assessing the statistical significance of the difference between the two. A database of the geometries of the 400 combinations of side-chain to side-chain interaction has been created. The approach used in analysing the geometrical information is illustrated here with specific examples of interactions between side-chains, peptide groups and particular types of atom. At the side-chain level, an analysis of aromatic-amino interactions, and the interactions of peptide carbonyl groups with arginine residues is presented. At the atomic level the analyses include the spatial disposition of oxygen atoms around tyrosine residues, and the frequency and type of contact between carbon, nitrogen and oxygen atoms. This information is currently being applied to the modelling of protein interactions.

Arginine↗
PubMed1990

HERA--a program to draw schematic diagrams of protein secondary structures.

A program is described which generates hydrogen bonding diagrams of protein structures and optionally helical wheels and helical nets. The program can also beta-strands beta-strands and to automatically extract simple structural motifs such as hairpins or Greek keys. The program greatly reduces the effort required to produce these diagrams and offers considerable flexibility in the information which can be represented. The usefulness of the program is illustrated by several examples including comparing homologous families, correlating protein structure with attributes of individual residues, and extracting all examples of the psi-loop motif from the Brookhaven Data Bank.

Amino Acid Sequence↗
PubMed1990

Beta-turns and their distortions: a proposed new nomenclature.

Using the new version of a Protein Structural Database, BIPED, beta-turns have been extracted from 58 non-identical proteins (resolution less than or equal to 2 A) using the standard criteria that the distance between C alpha i and C alpha i + 3 is less than 7 A and that the central residues are not helical. It has been shown that 42% of these do not fit into the eight conventional turn types (I, I', II, II', VIa, VIb and VIII) as defined by phi, psi limits for residues i + 1 and i + 2. Most of the unclassified turns are 'distortions' of the standard turn types, lying just outside the specified limits. Eleven per cent of the turns are not related to the standard types, and have completely different phi, psi combinations. Therefore, the conformational space available to a trans tetrapeptide has been explored to find all two-residue phi, psi combinations which satisfy the criteria for beta-turn formation. The conformations generated by the search are the conformations observed in the data. On the basis of these observations a new nomenclature is suggested for beta-turns based on a shorthand descriptor of populated regions of the phi, psi plot. For example, it is proposed that a type I turn should now be described as an alpha alpha turn, the descriptor indicating the phi, psi regions of the i + 1 and i + 2 positions of the turn. The use of descriptors, which convey information about the turn type conformation, should aid protein structural workers in turn classification and visualization. The sequence preferences for the alpha beta turn have been elucidated: Pro, Asp and Ser at i + 1; Asn and His at i + 2; Pro at i + 3. These preferences have been explained in terms of specific interactions involving the side-chains. The beta-turn prediction program, BTURN 1.0, has been further developed by alterations to the calculation of parameters, the removal of incompatible multiple turn predictions and the inclusion of the distorted types alpha alpha and beta p gamma data in the respective sets of parameters, to yield BTURN 2.0. A variation of this beta-turn prediction program, called GORBTURN 1.0, has been developed, which uses the directional parameters produced from work by Garrett et al., to eliminate potential helix and strand-forming residues from the beta-turn prediction.(ABSTRACT TRUNCATED AT 400 WORDS)

Amino Acid Sequence↗
PubMed1990

Influence of secondary structure on the hydration of serine, threonine and tyrosine residues in proteins.

Previous analysis of experimental data on the solvation of high resolution protein structures has shown that preferred interaction sites for water molecules exist around most amino acid side chains. We have extended this analysis to look in more detail at the distributions around serine, threonine and tyrosine. We find that for serine and threonine side chains the preferred interaction sites of solvent molecules with the hydroxyl group depends on secondary structure and the chi 1 torsion angle of the side chain. For tyrosine side chains the hydroxyl group is too far from the main chain to reflect secondary structure influences. Specific patterns of hydration are observed in which water molecules 'bridge' between the hydroxyl side-chain atom and another main chain or side-chain atom.

Amino Acids↗
PubMed1989

Conformation of beta-hairpins in protein structures. A systematic classification with applications to modelling by homology, electron density fitting and protein engineering.

A systematic classification of beta-hairpin structures which takes into account the polypeptide chain length and hydrogen bonding between the two antiparallel beta-strands is described. We have used this classification of beta-hairpin structures and their specific sequence pattern to derive rules which demonstrate its usefulness in assisting modelling beta-hairpins. These rules can be applied to comparative model building, modelling into electron density and in the prediction of conformation of beta-hairpins to aid protein engineering.

Aspartic Acid Endopeptidases↗
PubMed1989

Rebuilding flavodoxin from C alpha coordinates: a test study.

The tertiary structure of flavodoxin has been model built from only the X-ray crystallographic alpha-carbon coordinates. Main-chain atoms were generated from a dictionary of backbone structures. Side-chain conformations were initially set according to observed statistical distributions, clashes were resolved with reference to other knowledge-based parameters, and finally, energy minimization was applied. The RMSD of the model was 1.7 A across all atoms to the native structure. Regular secondary structural elements were modeled more accurately than other regions. About 40% of the chi 1 torsional angles were modeled correctly. Packing of side chains in the core was energetically stable but diverged significantly from the native structure in some regions. The modeling of protein structures is increasing in popularity but relatively few checks have been applied to determine the accuracy of the approach. In this work a variety of parameters have been examined. It was found that close contacts, and hydrogen-bonding patterns could identify poorly packed residues. These tests, however, did not indicate which residues had a conformation different from the native structure or how to move such residues to bring them into agreement. To assist in the modeling of interacting side chains a database of known interactions has been prepared.

Flavodoxin↗
PubMed1989

Protein motifs and data-base searching.

Protein structure and sequence motifs are now recognized for many different protein families and topologies. To aid identification and use of these motifs in modelling and prediction, it has become necessary to establish consistent data bases of protein structure, including not only coordinates, but also derived data such as secondary structure location and solvent accessibilities. This article describes first attempts to construct such data bases and explains how they can be used.

Amino Acid Sequence↗
PubMed1989

Amino acid sequence templates derived from recurrent turn motifs in proteins: critical evaluation of their predictive power.

Amino acid sequence patterns suggested to characterize specific recurrent turn conformation in protein are tested as to their predictive power in a database containing 75 proteins of known structure. Many of these patterns are found to be associated with local structures that differ from the motifs originally used to derive them. It is therefore concluded that, while they could be useful for improving predictions made by other methods, their stand-alone predictive power is poor. The issue of deriving and validating consensus sequence patterns for use in protein structure prediction is raised.

Amino Acid Sequence↗
PubMed1988

Analysis and prediction of the different types of beta-turn in proteins.

beta-Turns have been extracted from 59 non-identical proteins (resolution 2 A) using the standard criterion that the distance between C alpha (i) and C alpha (i + 3) is less than 7 A (1 A = 0.1 nm). The beta-turns have been classified, using phi, psi angles, into seven conventional turn types (I, I', II, II', IV, VIa, VIb) and a new class of beta-turn, designated type VIII, in which the central residues (i + 1, i + 2) adopt an alpha R beta conformation. Most beta-turn types are found in various topological environments, with the exception of I' and II' beta-turns, where 83% and 50%, respectively, are found in beta-hairpins. Sufficient data have been gathered to enable, for the first time, the separate statistical analysis of type I and II beta-turns. The two turn types have been shown to be strikingly different in their sequence preferences. Type I turns favour Asp, Asn, Ser and Cys at i; Asp, Ser, Thr and Pro at i + 1; Asp, Ser, Asn and Arg at i + 2; Gly, Trp and Met at i + 3, whilst type II turns prefer Pro at i + 1; Gly and Asn at i + 2; Gln and Arg at i + 3. These preferences have been explained by the specific side-chain interactions observed within the X-ray structures. The positional trends for type I and II beta-turns have been incorporated into the simple empirical predictive algorithm originally developed by P.N. Lewis et al. The program has improved the positional prediction of beta-turns, and has enhanced and extended the method by predicting the type of beta-turn. Since the observed preferences reflect local interactions these predictions are applicable not only to proteins, but also to peptides, many of which are thought to contain beta-turns.

Amino Acids↗
PubMed1988

Distributions of water around amino acid residues in proteins.

The atomic co-ordinates from 16 high-resolution (less than or equal to 1.7 A = 0.1 nm), non-homologous proteins have been used to study the distributions of water molecule sites around the 20 different amino acid residues. The proportion of residues whose main-chain atoms are in contact with water molecules was fairly constant (between 40% and 60%), irrespective of the nature of the side-chain. However, the proportion of residues whose side-chain atoms were in contact with water molecules showed a clear (inverse) correlation with the hydrophobicity of the residue, being as low as 14% for leucine and isoleucine but greater than 80% for asparagine and arginine. Despite the problems in determining accurate water molecule sites from X-ray diffraction data and the complexity of the protein surface, distinct non-random distributions of water molecules were found. These hydration patterns are consistent with the expected stereochemistry of the potential hydrogen-bonding sites on the polar side-chains. The water molecules around apolar side-chains lie predominantly at van der Waals' contact distances, but most of these have a primary, shorter contact with a neighbouring polar atom. Further analysis of these distributions, combined with energy minimization techniques, should lead to improved modelling of protein structures, including their primary shells of hydration.

Amino Acid Sequence↗
PubMed1988

Helix geometry in proteins.

In this report we describe a general survey of all helices found in 57 of the known protein crystal structures, together with a detailed analysis of 48 alpha-helices found in 16 of the structures that are determined to high resolution. The survey of all helices reveals a total of 291 alpha-helices, 71 3(10)-helices and no examples of pi-helices. The conformations of the observed helices are significantly different from the "ideal" linear structures. The mean phi, psi angles for the alpha- and 3(10)-helices found in proteins are, respectively, (-62 degrees, -41 degrees) and (-71 degrees, -18 degrees). A computer program, HBEND, is used to characterize and to quantify the different types of helix distortion. alpha-Helices are classified as regular or irregular, linear, curved or kinked. Of the 48 alpha-helices analysed, only 15% are considered to be linear; 17% are kinked, and 58% are curved. The curvature of helices is caused by differences in the peptide hydrogen bonding on opposite faces of the helix, reflecting carbonyl-solvent/side-chain interactions for the exposed residues, and packing constraints for residues involved in the hydrophobic core. Kinked helices arise either as a result of included proline residues, or because of conflicting requirements for the optimal packing of the helix side-chains. In alpha-helices where there are kinks caused by proline residues, we show that the angle of kink is relatively constant (approximately 26 degrees), and that there is minimal disruption of the helix hydrogen bonding. The proline residues responsible for the kinks are highly conserved, suggesting that these distortions may be structurally/functionally important.

Amino Acid Sequence↗