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PubMed2005

DNA, diseases and databases: disastrously deficient.

Recent progress in disease genetics and genome-related medicine has been substantial, with vast amounts of data being generated. However, this progress has not been matched by adequate database projects that gather and organize these data to enable their useful exploitation. This research area is complex, entailing core databases, locus-specific databases, national mutation databases, genotype-phenotype databases and patient databases--and much work is required to develop and properly integrate these various resources. To promote this, we present a timely overview of the field, emphasize its over-riding importance and discuss the disastrously deficient progress made so far. Many factors contribute to this slow progress (e.g. technological hurdles, publication requirements, the short-sighted and popularist research system). A lack of targeted funding is arguably the most fundamental problem, but one that can be solved.

Databases, Factual↗
PubMed2005

Bioinformatic "Harvester": a search engine for genome-wide human, mouse, and rat protein resources.

Harvester is a meta search engine for gene and protein information. It searches 16 major databases and prediction servers and combines the results on pregenerated HTML pages. In this way Harvester can provide comprehensive gene-protein information from different servers in a convenient and fast manner. The Harvester search engine works similar to Google, offering genome-wide ranked results at very high speed. Here we describe how to use this bioinformatic tool along with selected examples.

Animals↗
PubMed2002

CLiBE: a database of computed ligand binding energy for ligand-receptor complexes.

Consideration of binding competitiveness of a drug candidate against natural ligands and other drugs that bind to the same receptor site may facilitate the rational development of a candidate into a potent drug. A strategy that can be applied to computer-aided drug design is to evaluate ligand-receptor interaction energy or other scoring functions of a designed drug with that of the relevant ligands known to bind to the same binding site. As a tool to facilitate such a strategy, a database of ligand-receptor interaction energy is developed from known ligand-receptor 3D structural entries in the Protein Databank (PDB). The Energy is computed based on a molecular mechanics force field that has been used in the prediction of therapeutic and toxicity targets of drugs. This database also contains information about ligand function and other properties and it can be accessed at http://xin.cz3.nus.edu.sg/group/CLiBE.asp. The computed energy components may facilitate the probing of the mode of action and other profiles of binding. A number of computed energies of some PDB ligand-receptor complexes in this database are studied and compared to experimental binding affinity. A certain degree of correlation between the computed energy and experimental binding affinity is found, which suggests that the computed energy may be useful in facilitating a qualitative analysis of drug binding competitiveness.

Binding, Competitive↗
PubMed2002

IMGT, the international ImMunoGeneTics database: a high-quality information system for comparative immunogenetics and immunology.

IMGT, the international ImMunoGeneTics database (http://imgt.cines.fr), is a high quality integrated information system specializing in Immunoglobulins (IG), T cell Receptors (TR) and Major Histocompatibility Complex (MHC) of human and other vertebrates, created in 1989, by LIGM, at the Université Montpellier II, CNRS, Montpellier, France. IMGT provides a common access to standardized data, which include nucleotide and protein sequences, oligonucleotide primers, gene maps, genetic polymorphisms, specificities, 2D and 3D structures. IMGT includes several databases (IMGT/LIGM-DB, IMGT/HLA-DB, IMGT/3Dstructure-DB), Web resources ('IMGT Marie-Paule page') which comprise IMGT Scientific Chart, IMGT Repertoire, IMGT Bloc-notes, IMGT Education, IMGT Aide-mémoire and IMGT Index, and interactive tools (IMGT/V-QUEST, IMGT/JunctionAnalysis). These expertly annotated data on the genome, proteome, genetics and structure of the IG, TR and MHC are of high value for comparative genome evolution studies of the adaptative immune response.

Animals↗
PubMed2003

From biological databases to platforms for biomedical discovery.

The use of high-throughput DNA sequencing and proteomic methods has led to an unprecedented increase in the amount of genomic and proteomic data. Application of computing technologies and development of computational tools to analyze and present these data has not kept pace with the accumulation of information. Here, we discuss the use of different database systems to store biological information and mention some of the key emerging computing technologies that are likely to have a key role in the future of bioinformatics.

Algorithms↗
PubMedDate not supplied

Variable selection and interpretation in structure-affinity correlation modeling of estrogen receptor binders.

A computational approach for the identification and investigation of correlations between a chemical structure and a selected biological property is described. It is based on a set of 132 compounds of known chemical structures, which were tested for their binding affinities to the estrogen receptor. Different multivariate modeling methods, i.e., partial least-squares regression, counterpropagation neural network, and error-back-propagation neural network, were applied, and the prediction ability of each model was tested in order to compare the results of the obtained models. To reduce the extensive set of calculated structural descriptors, two types of variable selection methods were applied, depending on the modeling approach used. In particular, the final partial least-squares regression model was built using the "variable importance in projection" variable selection method, while genetic algorithms were applied in neural network modeling to select the optimal set of descriptors. A thorough statistical study of the variables selected by genetic algorithms is shown. The results were assessed with the aim to get insight to the mechanisms involved in the binding of estrogenic compounds to the receptor. The variable selection on the basis of genetic algorithm was controlled with the test set of compounds, extracted from the data set available. To compare the predictive ability of all the optimized models, a leave-one-out cross-validation procedure was applied, the best model being the nonlinear neural network model based on error back-propagation algorithm, which resulted in R2= 92.2% and Q2= 70.8%.

Algorithms↗
PubMed2005

Interaction profiles of protein kinase-inhibitor complexes and their application to virtual screening.

A major challenge facing structure-based drug discovery efforts is how to leverage the massive amount of experimental (X-ray and NMR) and virtual structural information generated from drug discovery projects. Many important drug targets have large numbers of protein-inhibitor complexes, necessitating tools to compare and contrast their similarities and differences. This information would be valuable for understanding potency and selectivity of inhibitors and could be used to define target constraints to assist virtual screening. We describe a profile-based approach that enables us to capture the conservation of interactions between a set of protein-ligand receptor complexes. The use of profiles provides a sensitive means to compare multiple inhibitors binding to a drug target. We demonstrate the utility of profile-based analysis of small molecule complexes from the protein-kinase family to identify similarities and differences in binding of ATP, p38, and CDK2 compounds to kinases and how these profiles can be applied to differentiate the selectivity of these inhibitors. Importantly, our virtual screening results demonstrate superior enrichment of kinase inhibitors using profile-based methods relative to traditional scoring functions. Interaction-based analysis should provide a valuable tool for understanding inhibitor binding to other important drug targets.

Adenosine Triphosphate↗
PubMed2006

In silico-guided target identification of a scaffold-focused library: 1,3,5-triazepan-2,6-diones as novel phospholipase A2 inhibitors.

A collection of 2150 druggable active sites from the Protein Data Bank was screened by high-throughput docking to identify putative targets for five representative molecules of a combinatorial library sharing a 1,3,5-triazepan-2,6-dione scaffold. Five targets were prioritized for experimental evaluation by computing enrichment in individual protein entries among the top 2% scoring targets. Out of the five proposed proteins, secreted phospholipase A2 (sPLA2) was shown to be a true target for a panel of 1,3,5-triazepan-2,6-diones which exhibited micromolar affinities toward two human sPLA2 members.

Azepines↗
PubMedDate not supplied

Identification of class II HLA-DRB1*03-bound measles virus peptides by 2D-liquid chromatography tandem mass spectrometry.

Two-dimensional liquid chromatography (2D-LC), combined with gas phase fractionation tandem mass spectrometry, was used to identify 13 naturally processed peptides originating from measles virus that were presented by HLA-DRB1*03 class II molecules. The peptides are from three of the six measles structural proteins: phosphoprotein, nucleocapsid, and hemagglutinin. These peptides provide an important first step toward understanding the mechanism of immune response to measles virus and development of a new generation of peptide-based vaccines.

Amino Acid Sequence↗
PubMedDate not supplied

VEMS 3.0: algorithms and computational tools for tandem mass spectrometry based identification of post-translational modifications in proteins.

Protein and peptide mass analysis and amino acid sequencing by mass spectrometry is widely used for identification and annotation of post-translational modifications (PTMs) in proteins. Modification-specific mass increments, neutral losses or diagnostic fragment ions in peptide mass spectra provide direct evidence for the presence of post-translational modifications, such as phosphorylation, acetylation, methylation or glycosylation. However, the commonly used database search engines are not always practical for exhaustive searches for multiple modifications and concomitant missed proteolytic cleavage sites in large-scale proteomic datasets, since the search space is dramatically expanded. We present a formal definition of the problem of searching databases with tandem mass spectra of peptides that are partially (sub-stoichiometrically) modified. In addition, an improved search algorithm and peptide scoring scheme that includes modification specific ion information from MS/MS spectra was implemented and tested using the Virtual Expert Mass Spectrometrist (VEMS) software. A set of 2825 peptide MS/MS spectra were searched with 16 variable modifications and 6 missed cleavages. The scoring scheme returned a large set of post-translationally modified peptides including precise information on modification type and position. The scoring scheme was able to extract and distinguish the near-isobaric modifications of trimethylation and acetylation of lysine residues based on the presence and absence of diagnostic neutral losses and immonium ions. In addition, the VEMS software contains a range of new features for analysis of mass spectrometry data obtained in large-scale proteomic experiments. Windows binaries are available at http://www.yass.sdu.dk/.

Algorithms↗
PubMed1998

We're off to see the genome.

We discuss some societal and legal ramifications of the human genetics revolution. Our reflections were stimulated by discussions among scientists, citizens and legal experts at a large public symposium. We outline key issues regarding oversight of genetic research on human subjects, banking of DNA data by governments and corporations, the potential impact of behavioural genetics and effects upon racial and racist thinking. We contend that, in some cases, well-intentioned but naive efforts to protect the rights of individuals and groups may hurt everyone by blocking the progress of useful research.

Databases, Factual↗