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Biomedical subjects

J A Christopher

Publications and source records attributed to J A Christopher.

9 recordsLinked to original sources
PubMed2000

Determining protein structure from electron-density maps using pattern matching.

TEXTAL is an automated system for building protein structures from electron-density maps. It uses pattern recognition to select regions in a database of previously determined structures that are similar to regions in a map of unknown structure. Rotation-invariant numerical values, called features, of the electron density are extracted from spherical regions in an unknown map and compared with features extracted around regions in maps generated from a database of known structures. Those regions in the database that match best provide the local coordinates of atoms and these are accumulated to form a model of the unknown structure. Similarity between the regions in the database and an uninterpreted region is determined firstly by evaluating the numerical difference in feature values and secondly by calculating the electron-density correlation coefficient for those regions with similar feature values. TEXTAL has been successful at building protein structures for a wide range of test electron-density maps and can automatically model entire protein structures in a few hours on a workstation. Models built by TEXTAL from test electron-density maps of known protein structures were accurate to within 0.6-0.7 A root-mean-square deviation, assuming prior knowledge of C(alpha) positions. The system represents a new approach to protein structure determination and has the potential to greatly reduce the time required to interpret electron-density maps in order to build accurate protein models.

Algorithms↗
PubMed1999

Model of maltose-binding protein/chemoreceptor complex supports intrasubunit signaling mechanism.

The Tar protein of Escherichia coli is unique among known bacterial chemoreceptors in that it generates additive responses to two very disparate ligands, aspartate and maltose. Aspartate binds directly to the periplasmic (extracytoplasmic) domain of Tar. Maltose first binds to maltose-binding protein (MBP). MBP then assumes a closed conformation in which it can interact with the periplasmic domain of Tar. MBP residues critical for binding Tar were identified in a screen of mutations that cause specific defects in maltose chemotaxis. Mutations were introduced into a plasmid-borne malE gene that encodes a mutant form of MBP in which two engineered Cys residues spontaneously generate a disulfide bond in the oxidizing environment of the periplasmic space. This disulfide covalently crosslinks the NH3-terminal and COOH-terminal domains of MBP and locks the protein into a closed conformation. Double-Cys MBP confers a dominant-negative phenotype for maltose taxis, and we reasoned that third mutations that relieve this negative dominance probably alter residues that are important for the initial interaction of MBP with Tar. The published three-dimensional structures of MBP and the periplasmic domain of E. coli Tar were docked in a computer simulation that juxtaposed the residues in MBP identified in this way with residues in Tar that have been implicated in maltose taxis. The resulting model of the MBP-Tar complex exhibits good complementarity between the surfaces of the two proteins and supports the idea that aspartate and MBP may each initiate an attractant signal through Tar by inducing similar conformational changes in the chemoreceptor.

ATP-Binding Cassette Transporters↗
PubMed1999

TEXTAL: a pattern recognition system for interpreting electron density maps.

X-ray crystallography is the most widely used method for determining the three-dimensional structures of proteins and other macromolecules. One of the most difficult steps in crystallography is interpreting the electron density map to build the final model. This is often done manually by crystallographers and is very time-consuming and error-prone. In this paper, we introduce a new automated system called TEXTAL for interpreting electron density maps using pattern recognition. Given a map to be modeled, TEXTAL divides the map into small regions and then finds regions with a similar pattern of density in a database of maps for proteins whose structures have already been solved. When a match is found, the coordinates of atoms in the region are inferred by analogy. The key to making the database lookup efficient is to extract numeric features that represent the patterns in each region and to compare feature values using a weighted Euclidean distance metric. It is crucial that the features be rotation-invariant, since regions with similar patterns of density can be oriented in any arbitrary way. This pattern-recognition approach can take advantage of data accumulated in large crystallographic databases to effectively learn the association between electron density and molecular structure by example.

Algorithms↗
PubMed1996

Implications of N and C-terminal proximity for protein folding.

We have investigated the proximity of the N and C termini in protein structures, and developed a model to test the theoretical possibility that proteins fold with their termini closely associated. On average, the distance between the termini is not significantly different from what would be expected based on chance. However, the theoretical model indicated that it is possible to greatly decrease the N-to-C terminal distance by allowing small (approximately six amino acid residues) solvent-accessible terminal fragments to move. Subsequent to this distance minimization method, more than 90% of the proteins studied had smaller-than-expected N-to-C distances, but only minor structural modification.

Computer Simulation↗
PubMed1996

Algorithms for finding the axis of a helix: fast rotational and parametric least-squares methods.

Several methods for finding the axis of a helix are presented and compared. The most accurate determines the helix axis as the axis of rotation necessary to map point i to point i + 1 of the helix. The fastest method calculates the helix axis as the best-fit line through the coordinates by a three-dimensional parametric linear least-squares algorithm, taking advantage of the sequential nature of the data.

Algorithms↗
PubMed1995

Structure of bacterial luciferase.

The generation of light by living organisms such as fireflies, glow-worms, mushrooms, fish, or bacteria growing on decaying materials has been a subject of fascination throughout the ages, partly because it occurs without the need for high temperatures. The chemistry behind the numerous bioluminescent systems is quite varied, and the enzymes that catalyze the reactions, the luciferases, are a large and evolutionarily diverse group. The structure of the best understood of these intriguing enzymes, bacterial luciferase, has recently been determined, allowing discussion of features of the protein in structural terms for the first time.

Bacteria↗
PubMed1994

Sexual precocity: sex incidence and aetiology.

The aetiology of 197 girls and 16 boys presenting with sexual precocity was reviewed. Ninety one girls and four boys had central precocious puberty (M:F 23:1); a cause was identified in all the boys but in only six girls. All boys with precocious puberty need detailed investigation; in girls investigation should be based on clinical findings, particularly the consonance of puberty.

Adrenal Hyperplasia, Congenital↗