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PubMed2002

[Bioinformatics].

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Computational Biology↗
PubMed2000

Bioinformatics: analysis of HLA sequence data.

High resolution HLA typing is a requirement for the selection of matched donors in hematopoietic cell transplantation. The high resolution typing method that provides the most accurate and complete identification of HLA genotypes is sequencing-based typing (SBT). For each sample being tested, SBT defines the exact nucleotide sequence of the coding regions of both alleles at a given HLA locus. Identification of the underlying genotype of the sample can then be made by computerized sequence comparison with all possible HLA allele combinations at that locus. The use of SBT to identify the complete nucleotide sequence of a given HLA gene also enables the direct detection of previously undefined alleles. Since different HLA alleles may differ by a single nucleotide, the accurate assignment of an HLA genotype by SBT is absolutely dependent on the correct identification of the nucleotide at each position for a given sample. However, automated sequence analysis of heterozygous samples may result in the ambiguous assignment of nucleotides at a given position. In addition, ambiguous assignments may result from the sequencing of two different samples that express different HLA alleles but whose sequence profiles appear exactly the same. Both of these ambiguous situations can be resolved by the application of the multi-sequence analysis (MSA) method described here.

Alleles↗
PubMed2002

"A system biology" approach to bioinformatics and functional genomics in complex human diseases: arthritis.

Human and other annotated genome sequences have facilitated generation of vast amounts of correlative data, from human/animal genetics, normal and disease-affected tissues from complex diseases such as arthritis using gene/protein chips and SNP analysis. These data sets include genes/proteins whose functions are partially known at the cellular level or may be completely unknown (e.g. ESTs). Thus, genomic research has transformed molecular biology from "data poor" to "data rich" science, allowing further division into subpopulations of subcellular fractions, which are often given an "-omic" suffix. These disciplines have to converge at a systemic level to examine the structure and dynamics of cellular and organismal function. The challenge of characterizing ESTs linked to complex diseases is like interpreting sharp images on a blurred background and therefore requires a multidimensional screen for functional genomics ("functionomics") in tissues, mice and zebra fish model, which intertwines various approaches and readouts to study development and homeostasis of a system. In summary, the post-genomic era of functionomics will facilitate to narrow the bridge between correlative data and causative data by quaint hypothesis-driven research using a system approach integrating "intercoms" of interacting and interdependent disciplines forming a unified whole as described in this review for Arthritis.

Animals↗
PubMed2003

Development under extreme conditions: forensic bioinformatics in the wake of the World Trade Center disaster.

The terrorist attacks of September 11, 2001 resulted in death and devastation in three locations, and extraordinary efforts have been exerted to identify the remains of all victims. As mass fatalities go, this one has been unusual at a policy level because the goal has been not merely to identify remains for every decedent, but to identify every bit of remains found so that even small pieces of tissue can be returned to families for burial. While the human impact at the Pentagon and Shanksville, PA was horrific, the World Trade Center site presented a particularly complex challenge for forensic DNA matching and data handling. A complete and definitive list of all those killed is still elusive, and human remains were crushed and co-mingled by the falling towers. Software tools had never been considered for a problem of this scale and scope. New data handling systems had to be created under extreme software development conditions characterized by incomplete requirements specifications, chaotically changing priorities, truly impossible deadlines and rapidly rolling production releases. Partly because of the company's experience with mtDNA tools built for the Armed Forces DNA Identification Lab starting in 1997, the New York City Office of Chief Medical Examiner [OCME] contacted Gene Codes Corporation in late September as existing data-handling tools began to fail. We began work on the project in mid-October, 2001. Our approach to the problem included: Extreme Programming [XP] methodology for functional software development, On-site time and motion analysis at the OCME for user interface design, Evidentiary references between STR, SNP and mtDNA analysis results, and Separate data Quality Control [QC] and software Quality Assurance [QA] initiatives. A substantial software suite was developed called M-FISys, an acronym for Mass-Fatality Identification System.

Computational Biology↗
PubMed2002

2D gels and bioinformatics--an eye to the future.

2-D Gel Technology has had profound impact on proteomic research over the years. Informatics support brought a new dimension to 2D gels and associated technologies. But with advent of new and emerging technologies, it will be interesting to observe the trends of 2D gel technology in the years to come. Here we review 2D gel technology and its applications besides looking at the future scope of 2D gels in the post genome era.

Computational Biology↗
PubMed2002

Prediction of food protein allergenicity: a bioinformatic learning systems approach.

Food hypersensitivity is constantly increasing in Western societies with a prevalence of about 1-2% in Europe and in the USA. Among children, the incidence is even higher. Because of the introduction of foods derived from genetically modified crops on the marketplace, the scientific community, regulatory bodies and international associations have intensified discussions on risk assessment procedures to identify potential food allergenicity of the newly introduced proteins. In this work, we present a novel biocomputational methodology for the classification of amino acid sequences with regard to food allergenicity and non-allergenicity. This method relies on a computerised learning system trained using selected excerpts of amino acid sequences. One example of such a successful learning system is presented which consists of feature extraction from sequence alignments performed with the FASTA3 algorithm (employing the BLOSUM50 substitution matrix) combined with the k-Nearest-Neighbour (kNN) classification algorithm. Briefly, the two features extracted are the alignment score and the alignment length and the kNN algorithm assigns the pair of extracted features from an unknown sequence to the prevalent class among its k nearest neighbours in the training (prototype) set available. 91 food allergens from several specialised public repositories of food allergy and the SWALL database were identified, pre-processed, and stored, yielding one of the most extensively characterised repositories of allergenic sequences known today. All allergenic sequences were classified using a standard one-leave-out cross validation procedure yielding about 81% correctly classified allergens and the classification of 367 non-allergens in an independent test set resulted in about 98% correct classifications. The biocomputational approach presented should be regarded as a significant extension and refinement of earlier attempts suggested for in silico food safety assessment. Our results show that the framework described here is powerful enough to become useful as part of a multiple-procedure test scheme that also depicts other evaluation approaches such as solid phase immunoassay and tests for stability to digestions.

Algorithms↗
PubMed2003

[Cloning, sequencing and bioinformatics analysis of a new tumor suppressor gene ndr2 from mouse].

BACKGROUND & OBJECTIVE: Ndr2 (N-myc down stream regulator) gene in human is a new gene cloned with the human adult whole brain cDNA as template in 1999, which accession number is AF159092 in GenBank. Locating backward position of the N-myc gene in human chromosome, this gene was named Ndr2 gene. The previous experimental results showed Ndr2 gene probably is a tumor suppressor gene. To research the function of Ndr2 gene, the authors cloned the genomic sequence of ndr2 from mouse. METHODS: To clone Ndr2 genomic sequence by reverse transcription-polymerase chain reaction(RT-PCR) with the mouse genome library as template; automatic sequencing was performed using 310 Genetic Analyzer; homogeneous analysis was made using GenBank BLAST; open reading fragment(ORF) analysis was made using PC Gene and ORF Finder; domain analysis was made using ProDom system. RESULTS: A fragment (about 3310bp,identified by agarose gel electrophoresis) was obtained using RT-PCR with the mouse genome library as template. The fragment was cloned in pMD18-T vector. BLAST analysis showed that the sequence was highly homogeneous (with the homogeneity rate of 91.4%) with Ndr2 gene in human and non-homogeneous with genomic sequence database in mouse. ORF analysis showed that there was a complete coding region in it, which including 8 extrons and 7 introns; it can interpret a protein containing about 200 amino acid residuals. ProDom analysis showed there was a domain like acyl carrier protein(ACP) in it. CONCLUSION: The authors cloned Ndr2 gene in mouse and proved that the sequence is a new genome sequence in mouse genomic sequence database. At present, the genome sequence has been submitted to GenBank(the accession number: AY151387).

Adaptor Proteins, Signal Transducing↗
PubMed2003

Targeting aurora2 kinase in oncogenesis: a structural bioinformatics approach to target validation and rational drug design.

The aurora kinases are a novel oncogenic family of mitotic serine/threonine kinases (S/T kinases) that are overexpressed in a number of solid tumors, including pancreas and colorectal cancer. A PSI-BLAST search [National Center for Biotechnology Information (NCBI)] with the sequence of the S/T kinase domain of human aurora1 kinase [also known as AUR1, ARK2, AIk2, AIM-1, and STK12] and human aurora2 kinase (also known as AUR2, ARK1, AIK, BTAK, and STK15) showed a high sequence similarity to the three-dimensional structures of bovine cAMP-dependent kinase [Brookhaven Protein Data Bank code 1CDK], murine cAMP-dependent kinase (1APM), and Caenorhabditis elegans twitchin kinase (1KOA). When the aurora1 or aurora2 sequence was input into the tertiary structure prediction programs THREADER and 3D-PSSM (three-dimensional position-sensitive scoring matrix), the top structural matches were 1CDK, 1APM, and 1KOA, confirming that these domains are structurally conserved. The structural models of aurora1 and aurora2 were built using 1CDK as the template structure. Molecular dynamics and docking simulations, targeting the ATP binding site of aurora2 with adenylyl imidodiphosphate (AMP-PNP), staurosporine, and six small molecular S/T kinase inhibitors, identified active-site residues that interact with these inhibitors differentially. The docked structures of the aurora2-AMP-PNP and aurora2-staurosporine complexes indicated that the adenine ring of AMP-PNP and the indolocarbazole moiety of staurosporine have similar positions and orientations and provided the basis for the docking of the other S/T kinase inhibitors. Inhibitors with isoquinoline and quinazoline moieties were recognized by aurora2 in which H-89 and 6,7-dimethoxyquinazoline compounds exhibited high binding energies compared with that of staurosporine. The calculated binding energies for the docked small-molecule inhibitors were qualitatively consistent with the IC(50) values generated using an in vitro kinase assay. The aurora2 structural model provides a rational basis for site-directed mutagenesis of the active site; design of novel H-89, staurosporine, and quinazoline analogues; and the screening of the available chemical database for the identification of other novel, small-molecular entities.

Amino Acid Sequence↗
PubMed2002

Bioinformatics classification and functional analysis of PhoH homologs.

PhoH protein is a putative ATPase belonging to the phosphate regulon in Escherichia coli. EC-PhoH homologs are present in different organisms, but it is not clear if they are functionally related, besides nothing is known about their regulation. To distinguish true functional orthologs of EC-PhoH in different classes of bacteria and to identify their functional role in bacterial metabolic network we performed phylogenetic analysis of these proteins and comparative study of position and regulation of the related genes. Three groups of proteins were identified. Proteins of the first group (BS-PhoH orthologs) are present in most of bacteria and are proposed to be functionally linked to phospholipid metabolism and RNA modification. Proteins of the second group (BS-YlaK orthologs) are present in most of aerobes and Actinobacterial YlaK orthologs are shown to be members of a fatty acid beta-oxidation regulons. EC-PhoH orthologs are classified in a third group, specific for Enterobacteria. Functional role of PhoH homologs in the lipid and RNA metabolism and proposed interrelation of PhoH paralogs in one organism are discussed.

Bacteria↗