Biomedical subjects

Brian D O'Connor

Publications and source records attributed to Brian D O'Connor.

3 recordsLinked to original sources

PubMed2005

The genomics of disulfide bonding and protein stabilization in thermophiles.

Thermophilic organisms flourish in varied high-temperature environmental niches that are deadly to other organisms. Recently, genomic evidence has implicated a critical role for disulfide bonds in the structural stabilization of intracellular proteins from certain of these organisms, contrary to the conventional view that structural disulfide bonds are exclusively extracellular. Here both computational and structural data are presented to explore the occurrence of disulfide bonds as a protein-stabilization method across many thermophilic prokaryotes. Based on computational studies, disulfide-bond richness is found to be widespread, with thermophiles containing the highest levels. Interestingly, only a distinct subset of thermophiles exhibit this property. A computational search for proteins matching this target phylogenetic profile singles out a specific protein, known as protein disulfide oxidoreductase, as a potential key player in thermophilic intracellular disulfide-bond formation. Finally, biochemical support in the form of a new crystal structure of a thermophilic protein with three disulfide bonds is presented together with a survey of known structures from the literature. Together, the results provide insight into biochemical specialization and the diversity of methods employed by organisms to stabilize their proteins in exotic environments. The findings also motivate continued efforts to sequence genomes from divergent organisms.

Amino Acid Sequence↗

PubMed2005

Utilizing logical relationships in genomic data to decipher cellular processes.

The wealth of available genomic data has spawned a corresponding interest in computational methods that can impart biological meaning and context to these experiments. Traditional computational methods have drawn relationships between pairs of proteins or genes based on notions of equality or similarity between their patterns of occurrence or behavior. For example, two genes displaying similar variation in expression, over a number of experiments, may be predicted to be functionally related. We have introduced a natural extension of these approaches, instead identifying logical relationships involving triplets of proteins. Triplets provide for various discrete kinds of logic relationships, leading to detailed inferences about biological associations. For instance, a protein C might be encoded within an organism if, and only if, two other proteins A and B are also both encoded within the organism, thus suggesting that gene C is functionally related to genes A and B. The method has been applied fruitfully to both phylogenetic and microarray expression data, and has been used to associate logical combinations of protein activity with disease state phenotypes, revealing previously unknown ternary relationships among proteins, and illustrating the inherent complexities that arise in biological data.

Algorithms↗

PubMed2004

GDAP: a web tool for genome-wide protein disulfide bond prediction.

The Genomic Disulfide Analysis Program (GDAP) provides web access to computationally predicted protein disulfide bonds for over one hundred microbial genomes, including both bacterial and achaeal species. In the GDAP process, sequences of unknown structure are mapped, when possible, to known homologous Protein Data Bank (PDB) structures, after which specific distance criteria are applied to predict disulfide bonds. GDAP also accepts user-supplied protein sequences and subsequently queries the PDB sequence database for the best matches, scans for possible disulfide bonds and returns the results to the client. These predictions are useful for a variety of applications and have previously been used to show a dramatic preference in certain thermophilic archaea and bacteria for disulfide bonds within intracellular proteins. Given the central role these stabilizing, covalent bonds play in such organisms, the predictions available from GDAP provide a rich data source for designing site-directed mutants with more stable thermal profiles. The GDAP web application is a gateway to this information and can be used to understand the role disulfide bonds play in protein stability both in these unusual organisms and in sequences of interest to the individual researcher. The prediction server can be accessed at http://www.doe-mbi.ucla.edu/Services/GDAP.

Archaeal Proteins↗