Biomedical subjects

Benjamin Bardiaux

Publications and source records attributed to Benjamin Bardiaux.

3 recordsLinked to original sources

PubMed2006

ARIA2: automated NOE assignment and data integration in NMR structure calculation.

UNLABELLED: Modern structural genomics projects demand for integrated methods for the interpretation and storage of nuclear magnetic resonance (NMR) data. Here we present version 2.1 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and NMR structure calculation. We report on recent developments, most notably a graphical user interface, and the incorporation of the object-oriented data model of the Collaborative Computing Project for NMR (CCPN). The CCPN data model defines a storage model for NMR data, which greatly facilitates the transfer of data between different NMR software packages. AVAILABILITY: A distribution with the source code of ARIA 2.1 is freely available at http://www.pasteur.fr/recherche/unites/Binfs/aria2.

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PubMed2006

Comparison of different torsion angle approaches for NMR structure determination.

A new procedure for NMR structure determination, based on the Internal Coordinate Molecular Dynamics (ICMD) approach, is presented. The method finds biopolymer conformations that satisfy usual NMR-derived restraints by using high temperature dynamics in torsion angle space. A variable target function algorithm gradually increases the number of NOE-based restraints applied, with the treatment of ambiguous and floating restraints included. This soft procedure allows combining artificially high temperature with a general purpose force-field including Coulombic and Lennard-Jones non-bonded interactions, which improves the quality of the ensemble of conformations obtained in the gas-phase. The new method is compared to existing algorithms by using the structures of eight ribosomal proteins earlier obtained with state-of-the-art procedures and included into the RECOORD database [Nederveen, A., Doreleijers, J., Vranken, W., Miller, Z., Spronk, C., Nabuurs, S., Guntert, P., Livny, M., Markley, M., Nilges, M., Ulrich, E., Kaptein, R. and Bonvin, A.M. (2005) Proteins, 59, 662-672]. For the majority of tested proteins, the ICMD algorithm shows similar convergence and somewhat better quality Z scores for the phi, psi distributions. The new method is more computationally demanding although the overall load is reasonable.

Algorithms↗

PubMed2004

Data mining techniques to study the disulfide-bonding state in proteins: signal peptide is a strong descriptor.

In the eucaryotic cell, the formation of disulfide bonds takes place in general inside the endoplasmic reticulum which provides a unique folding environment. The DisulfideDB database gathers information about this biological process with structural, evolutionary and neighborhood information on cysteines in proteins. Mining this information with an association rule discovery program permits to extract some strong rules for the prediction of the disulfide-bonding state of cysteines.

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