Publications by authors named "PE Bourne"

During the determination of macromolecular structures, scientists routinely use complex graphics software to display various representations of the molecule of interest. Once the structure determination is complete, coordinates are deposited in the Protein Data Bank (PDB), from where anyone with an Internet connection may download and view them or request them on CD-ROM. However, the currently available visualization software is such that causal users, whose expertise may not be in structure determination, often cannot obtain useful images of interesting molecules without expending considerable time and effort.

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We have developed a new algorithm for the alignment of multiple protein structures based on a Monte Carlo optimization technique. The algorithm uses pair-wise structural alignments as a starting point. Four different types of moves were designed to generate random changes in the alignment.

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An all-against-all protein structure comparison using the Combinatorial Extension (CE) algorithm applied to a representative set of PDB structures revealed a gallery of common substructures in proteins (http://cl.sdsc.edu/ce.

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The PDB has created systems for the processing, exchange, query, and distribution of data that will enable many aspects of high throughput structural genomics.

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Motivation: Crystallographers were motivated 10 years ago to develop a simple and consistent data representation for the exchange and archiving of data associated with the crystallographic experiment and the final structure. As this process evolved (and the data grew at near exponential rates) came the recognition that this representation should also facilitate the automated management of the data and, with the aid of additional software for verification and validation, provide improved consistency and accuracy and hence improved scientific inquiry. This realization led to a new Dictionary Definition Language (DDL) and an extensive dictionary based on this DDL for describing macromolecular structure.

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Comparisons of protein sequence via cyclic training of Hidden Markov Models (HMMs) in conjunction with alignments of three-dimensional structure, using the Combinatorial Extension (CE) algorithm, reveal two putative EF-hand metal binding domains in acetylcholinesterase. Based on sequence similarity, putative EF-hands are also predicted for the neuroligin family of cell surface proteins. These predictions are supported by experimental evidence.

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Comparing and subsequently classifying protein structures information has received significant attention concurrent with the increase in the number of experimentally derived 3-dimensional structures. Classification schemes have focused on biological function found within protein domains and on structure classification based on topology. Here an alternative view is presented that groups substructures.

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Motivation: Biological databases, with their rapidly expanding contents, are indispensable tools in the quest to understand more about biological function. However, a serious user of a database that comprises a large collection of data, collected over a long period, will likely be struck by the inconsistency in reporting individual items of data. This paper takes a critical look at the Protein Data Bank (PDB) to explore the seriousness of the problem in one particular data set and to explore the implications to those actively engaged in comparative analysis of these data.

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The Conserved Key Amino Acid Positions DataBase (CKAAPs DB) provides access to an analysis of structurally similar proteins with dissimilar sequences where key residues within a common fold are identified. The derivation and significance of CKAAPs starting from pairwise structure alignments is described fully in Reddy et al. [Reddy,B.

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The database reported here is derived using the Combinatorial Extension (CE) algorithm which compares pairs of protein polypeptide chains and provides a list of structurally similar proteins along with their structure alignments. Using CE, structure-structure alignments can provide insights into biological function. When a protein of known function is shown to be structurally similar to a protein of unknown function, a relationship might be inferred; a relationship not necessarily detectable from sequence comparison alone.

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The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules.

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Computer-based multimedia technology for distance learning and research has come of age--the price point is acceptable, domain experts using off-the-shelf software can prepare compelling materials, and the material can be efficiently delivered via the Internet to a large audience. While not presenting any new scientific results, this paper outlines experiences with a variety of commercial and free software tools and the associated protocols we have used to prepare protein documentaries and other multimedia presentations relevant to molecular biology. A protein documentary is defined here as a description of the relationship between structure and function in a single protein or in a related family of proteins.

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Databases containing macromolecular structure data provide a crystallographer with important tools for use in solving, refining and understanding the functional significance of their protein structures. Given this importance, this paper briefly summarizes past progress by outlining the features of the significant number of relevant databases developed to date. One recent database, PDB+, containing all current and obsolete structures deposited with the Protein Data Bank (PDB) is discussed in more detail.

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A new algorithm is reported which builds an alignment between two protein structures. The algorithm involves a combinatorial extension (CE) of an alignment path defined by aligned fragment pairs (AFPs) rather than the more conventional techniques using dynamic programming and Monte Carlo optimization. AFPs, as the name suggests, are pairs of fragments, one from each protein, which confer structure similarity.

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