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At least 1,135 records · Page 63Linked to original sources
PubMed2001

[Transcriptome analysis in cancerology: bioinformatics aspects].

Recent technological advances (e.g. various DNA arrays and chips) allow the measurement of expression level (mRNA abundance) for thousand of genes simultaneously, over multiple conditions or time. Initially developed and tested on model systems such as yeast or in vitro cell line cultures, these techniques have recently begun to be applied to the analysis of human cancers. Initial results are promising, and large-scale gene expression profiling is now expected to become a clinical tool for better tumour identification, prognosis, and optimal treatment design. It is thus important that clinicians become familiar with the theoretical principles underlying the interpretation of gene expression profiles as used in three different contexts: gene discovery, tumour class prediction, and molecular diagnosis. This is the purpose of the present article.

Forecasting↗
PubMed2001

A mechanism for stop codon recognition by the ribosome: a bioinformatic approach.

Protein synthesis in ribosomes requires two kinds of tRNAs: initiation and elongation. The former initiates the process (formylmethionine tRNA in prokaryotes and special methionine tRNA in eukaryotes). The latter participates in the synthesis proper, recognizing the sense codons. Synthesis is also assisted by special proteins: initiation, elongation, and termination factors. The termination factors are necessary to recognize stop codons (UAG, UGA, and UAA) and to release the complete protein chain from the elongation tRNA preceding a stop codon. No termination tRNA capable of recognizing stop codons by their anticodons is known. The termination factors are thought to do this. In the large ribosomal RNA, we found two sites that, like tRNAs, contain the anticodon hairpin but with triplets complementary to stop codons. One site is hairpin 69 from domain IV; the other site is hairpin 89, domain V. By analogy, we call them termination tRNAs: Ter-tRNA1 and Ter-tRNA2, respectively, even though they transport no amino acids, and suggest that they directly pair to stop codons. The termination factors only aid in this recognition, making it specific and reliable. A strong argument in favor of our hypothesis comes from vertebrate mitochondria. They are known to acquire two new stop codons, AGA and AGG. In the standard code, these are two out of six arginine codons. We revealed that the corresponding anticodons, UCU and CCU, have evolved in Ter-tRNA1 of these mitochondria.

Base Sequence↗
PubMed2002

RADARS, a bioinformatics solution that automates proteome mass spectral analysis, optimises protein identification, and archives data in a relational database.

RADARS, a rapid, automated, data archiving and retrieval software system for high-throughput proteomic mass spectral data processing and storage, is described. The majority of mass spectrometer data files are compatible with RADARS, for consistent processing. The system automatically takes unprocessed data files, identifies proteins via in silico database searching, then stores the processed data and search results in a relational database suitable for customized reporting. The system is robust, used in 24/7 operation, accessible to multiple users of an intranet through a web browser, may be monitored by Virtual Private Network, and is secure. RADARS is scalable for use on one or many computers, and is suited to multiple processor systems. It can incorporate any local database in FASTA format, and can search protein and DNA databases online. A key feature is a suite of visualisation tools (many available gratis), allowing facile manipulation of spectra, by hand annotation, reanalysis, and access to all procedures. We also described the use of Sonar MS/MS, a novel, rapid search engine requiring 40 MB RAM per process for searches against a genomic or EST database translated in all six reading frames. RADARS reduces the cost of analysis by its efficient algorithms: Sonar MS/MS can identifiy proteins without accurate knowledge of the parent ion mass and without protein tags. Statistical scoring methods provide close-to-expert accuracy and brings robust data analysis to the non-expert user.

Amino Acid Sequence↗
PubMed2002

[An introduction to the computer-aided structure-based drug design--applications of bioinformatics to drug discovery].

Computer-aided drug design methods are effective tools for drug discoveries. It is only small number of compounds that are required to be synthesized in practice, if the computer-aided drug design methods are used to predict the activities of the compounds. The methods are based on the interaction theory between drugs and their target proteins. Steric, electrostatic and hydrophobic complementarities are important in the interaction between the drug and the target protein. When three-dimensional structures of target proteins are known, the method is called as a structure-based drug design, while in case that the structures are unknown, a ligand-based drug design approach is employed for the computer-aided rational drug design. In the computer-aided structure-based drug design, it is important to build up the three-dimensional structure of drug-protein complex and to calculate a binding affinity of the drug to the protein. A molecular dynamics/free energy calculation is one of the most powerful tools to predict the binding affinity of a ligand molecule, when the three-dimensional structure of the drug-protein complex is available. The molecular dynamics/free energy calculation has been able to evaluate the binding affinities of a lot of ligand molecules to the target proteins successfully.

Computational Biology↗
PubMed2002

Bioinformatics of large-scale protein interaction networks.

We survey recent techniques for construction and prediction of large-scale protein interaction networks, focusing on computational processing steps. Special emphasis is placed on critical assessment of data completeness and reliability of the various approaches. Once built, protein interaction networks can be used for functional annotation or to generate higher-level biological hypotheses on pathways.

Bacterial Proteins↗
PubMed2000

Cloning of Human Myelin Protein Zero-like Genes by Bioinformatics Strategy.

To clone novel myelin protein related genes, two human ESTs, which shared significant similarity with the human myelin protein zero gene, were found by the comparison of homologue between the cDNA coding region sequences of MPZ gene and the EST database of NCBI. An 801 bp EST contig was assembled, which was 100% identical with a 128 kb genomic sequence, mapped to 1q24. A 435 bp open reading frame (ORF) within the 801 bp contig was shown by computer analysis. Two primers designed according to the sequence of the contig, were coupled with the primers(lambdagt10-5 and gt10-5) on the sequences flanking cloning site of the cDNA library vector to amplify the cDNA library sequences by nested PCR. New primers, designed based on novel cDNA sequences, were used for the PCR amplification with lambdagt10-5 and gt10-5 in the same way as above. Finally, the human myelin protein zero like gene isoform I and II (MPZL1a, MPZL1b GenBank AF095727, AF092424) were cloned. Comparison of gene and protein structures between MPZL1 and MPZ revealed that MPZL1 is the second member of MPZ family. Mutation analysis of MPZL1 gene was performed in 24 Charcot-Marie-Tooth disease (CMT) families and 26 nonsyndrome deafness families, but no mutation was found.

Journal Article↗
PubMed2002

Bioinformatic analyses of the tRNA: (guanine 26, N2,N2)-dimethyltransferase (Trm1) family.

Functional analyses of the tRNA:(guanine 26, N2,N2)-dimethyltransferase (Trm1) have been hampered by a lack of structural information about the enzyme and by low sequence similarity to better studied methyltransferases. Here we used computational methods to detect novel homologs of Trm1, infer the evolutionary relationships of the family, and predict the structure of the Trm1 methyltransferase. The N-terminal region of the protein is predicted to form an S-adenosylmethionine-binding domain, which harbors the active site. The C-terminal region is rich in predicted alpha-helices and, in analogy to other nucleic acid methyltransferases, may constitute the target recognition domain of the enzyme. Interposing these two domains, most Trm1 homologs possess a highly variable inserted sequence that is delimited by a Cys4 cluster, likely forming a Zn-finger structure. The residues of Trm1 predicted to participate in cofactor binding, target recognition, and catalysis, were mapped onto a preliminary structural model, providing a platform for designing new experiments to better understand the molecular functions of this protein family. In addition, identification of novel, atypical Trm1 homologs suggests candidates for cloning and biochemical characterization.

Amino Acid Sequence↗
PubMed2002

Structural criteria of biologically active RGD-sites for analysis of protein cellular function - a bioinformatics study.

BACKGROUND: Cell adhesion involves interactions of integrins and extracellular proteins, often facilitated by the RGD motif. Only presence of the RGD in a sequence of a protein may be not sufficient for the biological activity (binding to an integrin) and additional biochemical and/or structural studies are essential. MATERIAL/METHODS: Structural criteria that would allow identification biologically active RGD-sites on the base of a spatial structure may assist analysis of function of a protein in the cell. For the first time, computational analysis of RGD-sites in a large non-redundant set of protein structures was done. RESULTS: Out of 3819 protein chains sequences of about 100 contained RGDs. Analysis of the structures of the RGD-'native' proteins has allowed establishing main determinants of the biologically active conformations of the RGD sites: surface accessibility of the whole RGD-sequence and the secondary structure. The criteria, applied to the remaining proteins of the set, identify 23 proteins ( approximately 25%) with potentially active RGD-sites. The results strongly suggest that RGD has a high propensity for being involved in protein-protein interactions and this may explain occurrence of RGDs in intracellular proteins. Results of the analysis suggest (in some cases, confirm) novel integrin-related activities for 7 membrane/extracellular proteins, as well as confirm RGD-facilitated cell attachment for 5 viral proteins. CONCLUSIONS: Only presence of RGD in a sequence is not sufficient to propose biological activity of this site. The results also suggest that the method can be used on large scale: for example, for identifying potential integrin-interacting proteins in an animal genome.

Amino Acid Sequence↗