An anatomofunctional brain database

This study proposes a closer look at the neuropsychological method defined as the study of the neural bases of the behavioural and cognitive functions using an organisation-representation model for current data and knowledge of the brain, and the application of an anatomofunctional database. A Centre of Cognitive Anatomy (CAC) was set up for the collection and processing of neuronatomical, neuropsychological, and psycho-behavioural data for patients presenting sequels of focal brain damage. Such a system would allow concurrent treatment of anatomical and functional data. We would expect the results from such a model to produce stable 'anatomofunctional laws' that would be independent of all inter-individual variations in the functioning of the brain and could be checked against the entire database of information. A direct application would be the improvement of cognitive and/or behavioural rehabilitation of patients with brain damage.     

Identification of protein functions from a molecular surface database,eF-site

A bioinformatics method was developed to identify the protein surface around the functional site and to estimate the biochemical function, using a newly constructed molecular surface database named the eF-site (electrostatic surface of Functional site. Molecular surfaces of protein molecules were computed based on the atom coordinates, and the eF-site database was prepared by adding the physical properties on the constructed molecular surfaces. The electrostatic potential on each molecular surface was individually calculated solving the Poisson–Boltzmann equation numerically for the precise continuum model, and the hydrophobicity information of each residue was also included. The eF-site database is accessed by the internet (http://pi.protein.osaka-u.ac.jp/eF-site/). We have prepared four different databases, eF-site/antibody, eF-site/prosite, eF-site/P-site, and eF-site/ActiveSite, corresponding to the antigen binding sites of antibodies with the same orientations, the molecular surfaces for the individual motifs in PROSITE database, the phosphate binding sites, and the active site surfaces for the representatives of the individual protein family, respectively. An algorithm using the clique detection method as an applied graph theory was developed to search of the eF-site database, so as to recognize and discriminate the characteristic molecular surfaces of the proteins. The method identifies the active site having the similar function to those of the known proteins.     

Expanding the nitrogen regulatory protein superfamily: Homology detection at below random sequence identity

Nitrogen regulatory (PII) proteins are signal transduction molecules involved in controlling nitrogen metabolism in prokaryots. PII proteins integrate the signals of intracellular nitrogen and carbon status into the control of enzymes involved in nitrogen assimilation. Using elaborate sequence similarity detection schemes, we show that five clusters of orthologs (COGs) and several small divergent protein groups belong to the PII superfamily and predict their structure to be a (betaalphabeta)(2) ferredoxin-like fold. Proteins from the newly emerged PII superfamily are present in all major phylogenetic lineages. The PII homologs are quite diverse, with below random (as low as 1%) pairwise sequence identities between some members of distant groups. Despite this sequence diversity, evidence suggests that the different subfamilies retain the PII trimeric structure important for ligand-binding site formation and maintain a conservation of conservations at residue positions important for PII function. Because most of the orthologous groups within the PII superfamily are composed entirely of hypothetical proteins, our remote homology-based structure prediction provides the only information about them. Analogous to structural genomics efforts, such prediction gives clues to the biological roles of these proteins and allows us to hypothesize about locations of functional sites on model structures or rationalize about available experimental information. For instance, conserved residues in one of the families map in close proximity to each other on PII structure, allowing for a possible metal-binding site in the proteins coded by the locus known to affect sensitivity to divalent metal ions. Presented analysis pushes the limits of sequence similarity searches and exemplifies one of the extreme cases of reliable sequence-based structure prediction. In conjunction with structural genomics efforts to shed light on protein function, our strategies make it possible to detect homology between highly diverse sequences and are aimed at understanding the most remote evolutionary connections in the protein world.     

Pharmacophore-based molecular docking to account for ligand flexibility

Rapid computational mining of large 3D molecular databases is central to generating new drug leads. Accurate virtual screening of large 3D molecular databases requires consideration of the conformational flexibility of the ligand molecules. Ligand flexibility can be included without prohibitively increasing the search time by docking ensembles of precomputed conformers from a conformationally expanded database. A pharmacophore-based docking method whereby conformers of the same or different molecules are overlaid by their largest 3D pharmacophore and simultaneously docked by partial matches to that pharmacophore is presented. The method is implemented in DOCK 4.0.     

Multivariate exploratory tools for microarray data analysis

The ultimate success of microarray technology in basic and applied biological sciences depends critically on the development of statistical methods for gene expression data analysis. The most widely used tests for differential expression of genes are essentially univariate. Such tests disregard the multidimensional structure of microarray data. Multivariate methods are needed to utilize the information hidden in gene interactions and hence to provide more powerful and biologically meaningful methods for finding subsets of differentially expressed genes. The objective of this paper is to develop methods of multidimensional search for biologically significant genes, considering expression signals as mutually dependent random variables. To attain these ends, we consider the utility of a pertinent distance between random vectors and its empirical counterpart constructed from gene expression data. The distance furnishes exploratory procedures aimed at finding a target subset of differentially expressed genes. To determine the size of the target subset, we resort to successive elimination of smaller subsets resulting from each step of a random search algorithm based on maximization of the proposed distance. Different stopping rules associated with this procedure are evaluated. The usefulness of the proposed approach is illustrated with an application to the analysis of two sets of gene expression data.     

The cisproline(i - 1)-aromatic(i) interaction: folding of the Ala-cisPro-Tyr peptide characterized by NMR and theoretical approaches

Cisproline(i - 1)-aromatic(i) interactions have been detected in several short peptides in aqueous solution by analysis of anomalous chemical shifts measured by 1H-NMR spectroscopy. This formation of local structure is of importance for protein folding and binding properties. To obtain an atomic-detail characterisation of the cisproline(i - 1)-aromatic(i) interaction in terms of structure, energetics and dynamics, we studied the minimal peptide unit, blocked Ala-cisPro-Tyr, using computational and experimental techniques. Structural database analyses and a systematic search revealed two groups of conformations displaying a cisproline(i - 1)-aromatic(i) interaction. These conformations were taken as seeds for molecular dynamics simulations in explicit solvent at 278 K. During a total of 33.6 ns of simulation, all the 'folded' conformations and some 'unfolded' states were sampled. 1H- and 13C-chemical shifts and 3J-coupling constants were measured for the Ala-Pro-Tyr peptide. Excellent agreement was found between all the measured and computed NMR properties, showing the good quality of the force field. We find that under the experimental and simulation conditions, the Ala-cisPro-Tyr peptide is folded 90% of the time and displays two types of folded conformation which we denote 'a' and 'b'. The type a conformations are twice as populated as the type b conformations. The former have the tyrosine ring interacting with the alanine alpha proton and are enthalpically stabilised. The latter have the aromatic ring interacting with the proline side chain and are entropically stabilised. The combined and complementary use of computational and experimental techniques permitted derivation of a detailed scenario of the 'folding' of this peptide.     

Mining of assembled expressed sequence tag (EST) data for protein families: application to the G protein-coupled receptor superfamily

The availability of large expressed sequence tag (EST) databases has led to a revolution in the way new genes are identified. Mining of these databases using known protein sequences as queries is a powerful technique for discovering orthologous and paralogous genes. The scientist is often confronted, however, by an enormous amount of search output owing to the inherent redundancy of EST data. In addition, high search sensitivity often cannot be achieved using only a single member of a protein superfamily as a query. In this paper a technique for addressing both of these issues is described. Assembled EST databases are queried with every member of a protein superfamily, the results are integrated and false positives are pruned from the set. The result is a set of assemblies enriched in members of the protein superfamily under consideration. The technique is applied to the G protein-coupled receptor (GPCR) superfamily in the construction of a GPCR Resource. A novel full-length human GPCR identified from the GPCR Resource is presented, illustrating the utility of the method.     

The role of pattern databases in sequence analysis

In the wake of the numerous now-fruitful genome projects, we are entering an era rich in biological data. The field of bioinformatics is poised to exploit this information in increasingly powerful ways, but the abundance and growing complexity both of the data and of the tools and resources required to analyse them are threatening to overwhelm us. Databases and their search tools are now an essential part of the research environment. However, the rate of sequence generation and the haphazard proliferation of databases have made it difficult to keep pace with developments. In an age of information overload, researchers want rapid, easy-to-use, reliable tools for functional characterisation of newly determined sequences. But what are those tools? How do we access them? Which should we use? This review focuses on a particular type of database that is increasingly used in the task of routine sequence analysis--the so-called pattern database. The paper aims to provide an overview of the current status of pattern databases in common use, outlining the methods behind them and giving pointers on their diagnostic strengths and weaknesses.     

Distributed torsion angle grid search in high dimensions: A systematic approach to NMR structure determination

Two complementary approaches for systematic search in torsion angle space are described for the generation of all conformations of polypeptides which satisfy experimental NMR restraints, hard-sphere van der Waals radii, and rigid covalent geometry. The first procedure is based on a recursive, tree search algorithm for the examination of linear chains of torsion angles, and uses a novel treatment to propagate the search results to neighboring regions so that the structural consequences of the restraints are fully realized. The second procedure is based on a binary combination of torsion vector spaces for connected submolecules, and produces intermediate results in Cartesian space for a more robust restraint analysis. Restraints for NMR applications include bounds on torsion angles and internuclear distances, including relational and degenerate restraints involving equivalent and nonstereoassigned protons. To illustrate these methods, conformation search results are given for the tetrapeptide APGA restrained to an idealized -turn conformation, an alanine octapeptide restrained to a right-handed helical conformation, and the structured region of the peptide SYPFDV.