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At least 685 records · Page 38Linked to original sources
PubMed2004

RELIC--a bioinformatics server for combinatorial peptide analysis and identification of protein-ligand interaction sites.

Phage display technology provides a versatile tool for exploring the interactions between proteins, peptides and small molecule ligands. Quantitative analysis of peptide population sequence diversity and bias patterns has the power to significantly enhance the impact of these methods [1, 2]. We have developed a suite of computational tools for the analysis of peptide populations and made them accessible by integrating fifteen software programs for the analysis of combinatorial peptide sequences into the REceptor LIgand Contacts (RELIC) relational database and web-server. These programs have been developed for the analysis of statistical properties of peptide populations; identification of weak consensus sequences within these populations; and the comparison of these peptide sequences to those of naturally occurring proteins. RELIC is particularly suited to the analysis of peptide populations affinity selected with a small molecule ligand such as a drug or metabolite. Within this functional context, the ability to identify potential small molecule binding proteins using combinatorial peptide screening will accelerate as more ligands are screened and more genome sequences become available. The broader impact of this work is the addition of a novel means of analyzing peptide populations to the phage display community.

Algorithms↗
PubMed2004

Molecular classification of liver cirrhosis in a rat model by proteomics and bioinformatics.

Liver cirrhosis is a worldwide health problem. Reliable, noninvasive methods for early detection of liver cirrhosis are not available. Using a three-step approach, we classified sera from rats with liver cirrhosis following different treatment insults. The approach consisted of: (i) protein profiling using surface-enhanced laser desorption/ionization (SELDI) technology; (ii) selection of a statistically significant serum biomarker set using machine learning algorithms; and (iii) identification of selected serum biomarkers by peptide sequencing. We generated serum protein profiles from three groups of rats: (i) normal (n=8), (ii) thioacetamide-induced liver cirrhosis (n=22), and (iii) bile duct ligation-induced liver fibrosis (n=5) using a weak cation exchanger surface. Profiling data were further analyzed by a recursive support vector machine algorithm to select a panel of statistically significant biomarkers for class prediction. Sensitivity and specificity of classification using the selected protein marker set were higher than 92%. A consistently down-regulated 3495 Da protein in cirrhosis samples was one of the selected significant biomarkers. This 3495 Da protein was purified on-chip and trypsin digested. Further structural characterization of this biomarkers candidate was done by using cross-platform matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) peptide mass fingerprinting (PMF) and matrix-assisted laser desorption/ionization time of flight/time of flight (MALDI-TOF/TOF) tandem mass spectrometry (MS/MS). Combined data from PMF and MS/MS spectra of two tryptic peptides suggested that this 3495 Da protein shared homology to a histidine-rich glycoprotein. These results demonstrated a novel approach to discovery of new biomarkers for early detection of liver cirrhosis and classification of liver diseases.

Algorithms↗
PubMed2006

Proteomic and bioinformatic analysis of iron- and sulfur-oxidizing Acidithiobacillus ferrooxidans using immobilized pH gradients and mass spectrometry.

A comparative analysis of the protein composition of Acidithiobacillus ferrooxidans cells grown on elemental sulfur and ferrous iron was performed. A newly developed protocol involving immobilized pH gradients, improved protein reduction, mass spectrometry protein identification and full genome sequence information was applied. This approach resulted in more than 1300 protein spots displayed in broad and basic pH ranges, the best A. ferrooxidans proteome resolution to date. A comparative image analysis revealed that the proteome was significantly influenced by the growth type, and allowed for the detection of many physiologically important proteins. Among them were sulfate adenylyltransferase and sulfide dehydrogenase, which are involved in sulfate assimilation and sulfide metabolism, respectively. Many other proteins were related to important processes like cell attachment and electron transport. Co-migration of phosphate and sulfate transport proteins was also observed.

Acidithiobacillus↗
PubMed2003

Helix propensities of short peptides: molecular dynamics versus bioinformatics.

Knowledge-based potential functions for protein structure prediction assume that the frequency of occurrence of a given structure or a contact in the protein database is a measure of its free energy. Here, we put this assumption to test by comparing the results obtained from sequence-structure cluster analysis with those obtained from long all-atom molecular dynamics simulations. Sixty-four eight-residue peptide sequences with varying degrees of similarity to the canonical sequence pattern for amphipathic helix were drawn from known protein structures, regardless of whether they were helical in the protein. Each was simulated using AMBER6.0 for at least 10 ns using explicit waters. The total simulation time was 1176 ns. The resulting trajectories were tested for reproducibility, and the helical content was measured. Natural peptides whose sequences matched the amphipathic helix motif with greater than 50% confidence were significantly more likely to form helix during the course of the simulation than peptides with lower confidence scores. The sequence pattern derived from the simulation data closely resembles the motif pattern derived from the database cluster analysis. The difficulties encountered in sampling conformational space and sequence space simultaneously are discussed.

Amino Acid Motifs↗
PubMed2002

The use of bioinformatics to identify the genomic structure of the gene that encodes neutrophil antigen NB1, CD177.

The gene encoding neutrophil alloantigen NB1, CD177, is highly homologous to a gene overexpressed in polycythemia vera neutrophils, polycythemia rubra vera-1 (PRV-1). The cDNAs of both genes have been cloned, but their genomic structure is unknown. The purpose of this study was to determine the intron-exon organization of NB1 and PRV-1 and discern if they are separate members of a homologous gene family or alleles of the same gene. GenBank's human genome sequences were probed in silico with PRV-1's 1605-nucleotide coding sequence. Searches identified two adjacent bacterial artificial chromosomes (BACs) on chromosome 19q13.2: BC338531 and BC52850. BC338531 contained sequences 100% homologous to the first 654 nucleotides of PRV-1. Comparison of coding and genomic sequences allowed us to separate this region into exons 1 through 5, interrupted by five introns. BC52850 contained sequences 95% homologous to nucleotides 413 through 1605 of PRV-1, organized into exons 4 through 9. However, the orientation of PRV-1-homologous in the first BAC was plus-plus and of the second was plus-minus, indicating they could not be portions of the same gene. The GenBank sequence of BC338531 was incomplete, creating a sequence gap in chromosome 19q13.2. Evaluation of BC338531's unfinished sequences in Joint Genome Institute public databases allowed us to complete the gap and revealed that BC338531 contained sequences 98% homologous to all nine PRV-1 exons followed by a second gene consisting of exons 9 through 4. Most likely, NB1 and PRV-1 are alleles of the same gene, CD177, and the duplication of exons 4 through 9 is a pseudo gene.

Amino Acid Sequence↗
PubMed2003

Bioinformatic principles underlying the information content of transcription factor binding sites.

Empirically, it has been observed in several cases that the information content of transcription factor binding site sequences (R(sequence)) approximately equals the information content of binding site positions (R(frequency)). A general framework for formal models of transcription factors and binding sites is developed to address this issue. Measures for information content in transcription factor binding sites are revisited and theoretic analyses are compared on this basis. These analyses do not lead to consistent results. A comparative review reveals that these inconsistent approaches do not include a transcription factor state space. Therefore, a state space for mathematically representing transcription factors with respect to their binding site recognition properties is introduced into the modelling framework. Analysis of the resulting comprehensive model shows that the structure of genome state space favours equality of R(sequence) and R(frequency) indeed, but the relation between the two information quantities also depends on the structure of the transcription factor state space. This might lead to significant deviations between R(sequence) and R(frequency). However, further investigation and biological arguments show that the effects of the structure of the transcription factor state space on the relation of R(sequence) and R(frequency) are strongly limited for systems which are autonomous in the sense that all DNA-binding proteins operating on the genome are encoded in the genome itself. This provides a theoretical explanation for the empirically observed equality.

Animals↗
PubMed2003

Bioinformatics.

Explore the source record for details and available documents.

Cells↗
PubMed1997

Detailed analysis of a 17q21 microdissection library by sequence bioinformatics and isolation of region-specific clones.

A region-specific microdissection library originating from human chromosome 17q21, was constructed using the MboI linker-adaptor microcloning technique. DNA sequencing of 241 microclones resulted in the identification of 74 novel coding sequences, paralogs of known genes, and known, but previously unmapped, genes or expressed sequence tags that were "virtually" mapped to chromosome 17q21. By pooling the microclones as multiplexed hybridization probes, and by virtue of their origin on 17q21, we were able to identify approximately 150 P1 clones from the human Reference Library Data Base P1 Library that potentially map to chromosome 17q21. Verification of the 17q21 location of 16 P1 clones was accomplished by PCR analysis with STS primer pairs to known 17q21 genes or by FISH. Our results demonstrate the substantial advantage of combining the sequence analysis of microclones with multiplex hybridization strategies for gene discovery and mapping specific gene rich regions of the genome.

Base Sequence↗