The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
Michael Nilges - One of the best experts on this subject based on the ideXlab platform.
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ARIAweb: a server for automated NMR Structure Calculation
Nucleic Acids Research, 2020Co-Authors: Fabrice Allain, Michael Nilges, Fabien Mareuil, Hervé Ménager, Benjamin BardiauxAbstract:Nuclear magnetic resonance (NMR) spectroscopy is a method of choice to study the dynamics and de- termine the atomic Structure of macromolecules in solution. The standalone program ARIA (Ambigu- ous Restraints for Iterative Assignment) for auto- mated assignment of nuclear Overhauser enhance- ment (NOE) data and Structure Calculation is well es- tablished in the NMR community. To ultimately pro- vide a perfectly transparent and easy to use service, we designed an online user interface to ARIA with additional functionalities. Data conversion, Structure Calculation setup and execution, followed by inter- active visualization of the generated 3D Structures are all integrated in ARIAweb and freely accessible at https://ariaweb.pasteur.fr.
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Improved reliability, accuracy and quality in automated NMR Structure Calculation with ARIA.
Journal of Biomolecular NMR, 2015Co-Authors: Fabien Mareuil, Therese E Malliavin, Michael Nilges, Benjamin BardiauxAbstract:In biological NMR, assignment of NOE cross-peaks and Calculation of atomic conformations are critical steps in the determination of reliable high-resolution Structures. ARIA is an automated approach that performs NOE assignment and Structure Calculation in a concomitant manner in an iterative procedure. The log-harmonic shape for distance restraint potential and the Bayesian weighting of distance restraints, recently introduced in ARIA, were shown to significantly improve the quality and the accuracy of determined Structures. In this paper, we propose two modifications of the ARIA protocol: (1) the softening of the force field together with adapted hydrogen radii, which is meaningful in the context of the log-harmonic potential with Bayesian weighting, (2) a procedure that automatically adjusts the violation tolerance used in the selection of active restraints, based on the fitting of the Structure to the input data sets. The new ARIA protocols were fine-tuned on a set of eight protein targets from the CASD–NMR initiative. As a result, the convergence problems previously observed for some targets was resolved and the obtained Structures exhibited better quality. In addition, the new ARIA protocols were applied for the Structure Calculation of ten new CASD–NMR targets in a blind fashion, i.e. without knowing the actual solution. Even though optimisation of parameters and pre-filtering of unrefined NOE peak lists were necessary for half of the targets, ARIA consistently and reliably determined very precise and highly accurate Structures for all cases. In the context of integrative structural biology, an increasing number of experimental methods are used that produce distance data for the determination of 3D Structures of macromolecules, stressing the importance of methods that successfully make use of ambiguous and noisy distance data. Keywords Nuclear magnetic resonance Á Automated NOE assignment Á Structure determination Á ARIA Á CASD–NMR
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eMagRes - Protein Structure Calculation using Ambiguous Restraints
Encyclopedia of Magnetic Resonance, 2010Co-Authors: Michael Nilges, Therese E Malliavin, Benjamin BardiauxAbstract:Distance information remains the most important information for Structure determination by liquid- and solid-state NMR. Ambiguity in this distance information is a major bottleneck. The ambiguous distance restraint (ADR) offers a straightforward way to include ambiguous distance information in a Structure Calculation. It can also help in identifying and suppressing erroneous distance information. Ambiguous distance restraints are not limited to expressing ambiguities in NOEs but can be used to incorporate as geometric restraints an increasing number of experimental data types or theoretical considerations. Keywords: automated assignment; distance restraints; nuclear Overhauser effect; interface mapping; hydrogen bonds
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isd a software package for bayesian nmr Structure Calculation
Bioinformatics, 2008Co-Authors: Wolfgang Rieping, Michael Nilges, Michael HabeckAbstract:The conventional approach to calculating biomolecular Structures from nuclear magnetic resonance (NMR) data is often viewed as subjective due to its dependence on rules of thumb for deriving geometric constraints and suitable values for theory parameters from noisy experimental data. As a result, it can be difficult to judge the precision of an NMR Structure in an objective manner. The inferential Structure determination (ISD) framework, which has been introduced recently, addresses this problem by using Bayesian inference to derive a probability distribution that represents both the unknown Structure and its uncertainty. It also determines additional unknowns, such as theory parameters, that normally need to be chosen empirically. Here we give an overview of the ISD software package, which implements this methodology. Availability: http://www.bioc.cam.ac.uk/isd Contact: wolfgang.rieping@bioc.cam.ac.uk, michael.habeck@tuebingen.mpg.de.
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Probabilistic Structure Calculation
Comptes Rendus Chimie, 2008Co-Authors: Michael Nilges, Michael Habeck, Wolfgang RiepingAbstract:Abstract Molecular Structures are usually calculated from experimental data with some method of energy minimisation or non-linear optimisation. Key aims of a Structure Calculation are to estimate the coordinate uncertainty, and to provide a meaningful measure of the quality of the fit to the data. We discuss approaches to optimally combine prior information and experimental data and the connection to probability theory. We analyse the appropriate statistics for NOEs and NOE-derived distances, and the related question of restraint potentials. Finally, we will discuss approaches to determine the appropriate weight on the experimental evidence and to obtain in this way an estimate of the data quality from the Structure Calculation. Whereas objective estimates of coordinates and their uncertainties can only be obtained by a full Bayesian treatment of the problem, standard Structure Calculation methods continue to play an important role. To obtain the full benefit of these methods, they should be founded on a rigorous Bayesian analysis.
Peter Guntert - One of the best experts on this subject based on the ideXlab platform.
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NMR Structure Calculation for all small molecule ligands and non-standard residues from the PDB Chemical Component Dictionary
Journal of Biomolecular NMR, 2015Co-Authors: Emel Maden Yilmaz, Peter GuntertAbstract:An algorithm, CYLIB, is presented for converting molecular topology descriptions from the PDB Chemical Component Dictionary into CYANA residue library entries. The CYANA Structure Calculation algorithm uses torsion angle molecular dynamics for the efficient computation of three-dimensional Structures from NMR-derived restraints. For this, the molecules have to be represented in torsion angle space with rotations around covalent single bonds as the only degrees of freedom. The molecule must be given a tree Structure of torsion angles connecting rigid units composed of one or several atoms with fixed relative positions. Setting up CYANA residue library entries therefore involves, besides straightforward format conversion, the non-trivial step of defining a suitable tree Structure of torsion angles, and to re-order the atoms in a way that is compatible with this tree Structure. This can be done manually for small numbers of ligands but the process is time-consuming and error-prone. An automated method is necessary in order to handle the large number of different potential ligand molecules to be studied in drug design projects. Here, we present an algorithm for this purpose, and show that CYANA Structure Calculations can be performed with almost all small molecule ligands and non-standard amino acid residues in the PDB Chemical Component Dictionary.
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Combined automated NOE assignment and Structure Calculation with CYANA
Journal of Biomolecular NMR, 2015Co-Authors: Peter Guntert, Lena BuchnerAbstract:The automated assignment of NOESY cross peaks has become a fundamental technique for NMR protein Structure analysis. A widely used algorithm for this purpose is implemented in the program CYANA. It has been used for a large number of Structure determinations of proteins in solution but was so far not described in full detail. In this paper we present a complete description of the CYANA implementation of automated NOESY assignment, which differs extensively from its predecessor CANDID by the use of a consistent probabilistic treatment, and we discuss its performance in the second round of the critical assessment of Structure determination by NMR.
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Automated NMR Structure Calculation with CYANA.
Methods in molecular biology (Clifton N.J.), 2004Co-Authors: Peter GuntertAbstract:This chapter gives an introduction to automated nuclear magnetic resonance (NMR) Structure Calculation with the program CYANA. Given a sufficiently complete list of assigned chemical shifts and one or several lists of cross-peak positions and columns from two-, three-, or four-dimensional nuclear Overhauser effect spectroscopy (NOESY) spectra, the assignment of the NOESY cross-peaks and the three-dimensional Structure of the protein in solution can be calculated automatically with CYANA.
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torsion angle dynamics for nmr Structure Calculation with the new program dyana
Journal of Molecular Biology, 1997Co-Authors: Peter Guntert, Christian Mumenthaler, Kurt WuthrichAbstract:Abstract The new program D yana (DYnamics Algorithm for Nmr Applications) for efficient Calculation of three-dimensional protein and nucleic acid Structures from distance constraints and torsion angle constraints collected by nuclear magnetic resonance (NMR) experiments performs simulated annealing by molecular dynamics in torsion angle space and uses a fast recursive algorithm to integrate the equations of motions. Torsion angle dynamics can be more efficient than molecular dynamics in Cartesian coordinate space because of the reduced number of degrees of freedom and the concomitant absence of high-frequency bond and angle vibrations, which allows for the use of longer time-steps and/or higher temperatures in the Structure Calculation. It also represents a significant advance over the variable target function method in torsion angle space with the R edac strategy used by the predecessor program D iana . D yana computation times per accepted conformer in the “bundle” used to represent the NMR Structure compare favorably with those of other presently available Structure Calculation algorithms, and are of the order of 160 seconds for a protein of 165 amino acid residues when using a DEC Alpha 8400 5/300 computer. Test Calculations starting from conformers with random torsion angle values further showed that D yana is capable of efficient Calculation of high-quality protein Structures with up to 400 amino acid residues, and of nucleic acid Structures.
Benjamin Bardiaux - One of the best experts on this subject based on the ideXlab platform.
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ARIAweb: a server for automated NMR Structure Calculation
Nucleic Acids Research, 2020Co-Authors: Fabrice Allain, Michael Nilges, Fabien Mareuil, Hervé Ménager, Benjamin BardiauxAbstract:Nuclear magnetic resonance (NMR) spectroscopy is a method of choice to study the dynamics and de- termine the atomic Structure of macromolecules in solution. The standalone program ARIA (Ambigu- ous Restraints for Iterative Assignment) for auto- mated assignment of nuclear Overhauser enhance- ment (NOE) data and Structure Calculation is well es- tablished in the NMR community. To ultimately pro- vide a perfectly transparent and easy to use service, we designed an online user interface to ARIA with additional functionalities. Data conversion, Structure Calculation setup and execution, followed by inter- active visualization of the generated 3D Structures are all integrated in ARIAweb and freely accessible at https://ariaweb.pasteur.fr.
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Improved reliability, accuracy and quality in automated NMR Structure Calculation with ARIA.
Journal of Biomolecular NMR, 2015Co-Authors: Fabien Mareuil, Therese E Malliavin, Michael Nilges, Benjamin BardiauxAbstract:In biological NMR, assignment of NOE cross-peaks and Calculation of atomic conformations are critical steps in the determination of reliable high-resolution Structures. ARIA is an automated approach that performs NOE assignment and Structure Calculation in a concomitant manner in an iterative procedure. The log-harmonic shape for distance restraint potential and the Bayesian weighting of distance restraints, recently introduced in ARIA, were shown to significantly improve the quality and the accuracy of determined Structures. In this paper, we propose two modifications of the ARIA protocol: (1) the softening of the force field together with adapted hydrogen radii, which is meaningful in the context of the log-harmonic potential with Bayesian weighting, (2) a procedure that automatically adjusts the violation tolerance used in the selection of active restraints, based on the fitting of the Structure to the input data sets. The new ARIA protocols were fine-tuned on a set of eight protein targets from the CASD–NMR initiative. As a result, the convergence problems previously observed for some targets was resolved and the obtained Structures exhibited better quality. In addition, the new ARIA protocols were applied for the Structure Calculation of ten new CASD–NMR targets in a blind fashion, i.e. without knowing the actual solution. Even though optimisation of parameters and pre-filtering of unrefined NOE peak lists were necessary for half of the targets, ARIA consistently and reliably determined very precise and highly accurate Structures for all cases. In the context of integrative structural biology, an increasing number of experimental methods are used that produce distance data for the determination of 3D Structures of macromolecules, stressing the importance of methods that successfully make use of ambiguous and noisy distance data. Keywords Nuclear magnetic resonance Á Automated NOE assignment Á Structure determination Á ARIA Á CASD–NMR
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eMagRes - Protein Structure Calculation using Ambiguous Restraints
Encyclopedia of Magnetic Resonance, 2010Co-Authors: Michael Nilges, Therese E Malliavin, Benjamin BardiauxAbstract:Distance information remains the most important information for Structure determination by liquid- and solid-state NMR. Ambiguity in this distance information is a major bottleneck. The ambiguous distance restraint (ADR) offers a straightforward way to include ambiguous distance information in a Structure Calculation. It can also help in identifying and suppressing erroneous distance information. Ambiguous distance restraints are not limited to expressing ambiguities in NOEs but can be used to incorporate as geometric restraints an increasing number of experimental data types or theoretical considerations. Keywords: automated assignment; distance restraints; nuclear Overhauser effect; interface mapping; hydrogen bonds
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aria2 automated noe assignment and data integration in nmr Structure Calculation
Bioinformatics, 2007Co-Authors: Wolfgang Rieping, Therese E Malliavin, Benjamin Bardiaux, Michael Habeck, Aymeric Bernard, Michael NilgesAbstract:Summary: 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 Contact: [email protected]
Michael Habeck - One of the best experts on this subject based on the ideXlab platform.
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Bayesian Weighting of Statistical Potentials in NMR Structure Calculation
PloS one, 2014Co-Authors: Martin Mechelke, Michael HabeckAbstract:The use of statistical potentials in NMR Structure Calculation improves the accuracy of the final Structure but also raises issues of double counting and possible bias. Because statistical potentials are averaged over a large set of Structures, they may not reflect the preferences of a particular Structure or data set. We propose a Bayesian method to incorporate a knowledge-based backbone dihedral angle potential into an NMR Structure Calculation. To avoid bias exerted through the backbone potential, we adjust its weight by inferring it from the experimental data. We demonstrate that an optimally weighted potential leads to an improvement in the accuracy and quality of the final Structure, especially with sparse and noisy data. Our findings suggest that no universally optimal weight exists, and that the weight should be determined based on the experimental data. Other knowledge-based potentials can be incorporated using the same approach.
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isd a software package for bayesian nmr Structure Calculation
Bioinformatics, 2008Co-Authors: Wolfgang Rieping, Michael Nilges, Michael HabeckAbstract:The conventional approach to calculating biomolecular Structures from nuclear magnetic resonance (NMR) data is often viewed as subjective due to its dependence on rules of thumb for deriving geometric constraints and suitable values for theory parameters from noisy experimental data. As a result, it can be difficult to judge the precision of an NMR Structure in an objective manner. The inferential Structure determination (ISD) framework, which has been introduced recently, addresses this problem by using Bayesian inference to derive a probability distribution that represents both the unknown Structure and its uncertainty. It also determines additional unknowns, such as theory parameters, that normally need to be chosen empirically. Here we give an overview of the ISD software package, which implements this methodology. Availability: http://www.bioc.cam.ac.uk/isd Contact: wolfgang.rieping@bioc.cam.ac.uk, michael.habeck@tuebingen.mpg.de.
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Probabilistic Structure Calculation
Comptes Rendus Chimie, 2008Co-Authors: Michael Nilges, Michael Habeck, Wolfgang RiepingAbstract:Abstract Molecular Structures are usually calculated from experimental data with some method of energy minimisation or non-linear optimisation. Key aims of a Structure Calculation are to estimate the coordinate uncertainty, and to provide a meaningful measure of the quality of the fit to the data. We discuss approaches to optimally combine prior information and experimental data and the connection to probability theory. We analyse the appropriate statistics for NOEs and NOE-derived distances, and the related question of restraint potentials. Finally, we will discuss approaches to determine the appropriate weight on the experimental evidence and to obtain in this way an estimate of the data quality from the Structure Calculation. Whereas objective estimates of coordinates and their uncertainties can only be obtained by a full Bayesian treatment of the problem, standard Structure Calculation methods continue to play an important role. To obtain the full benefit of these methods, they should be founded on a rigorous Bayesian analysis.
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aria2 automated noe assignment and data integration in nmr Structure Calculation
Bioinformatics, 2007Co-Authors: Wolfgang Rieping, Therese E Malliavin, Benjamin Bardiaux, Michael Habeck, Aymeric Bernard, Michael NilgesAbstract:Summary: 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 Contact: [email protected]
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Weighting of experimental evidence in macromolecular Structure determination
Proceedings of the National Academy of Sciences of the United States of America, 2006Co-Authors: Michael Habeck, Wolfgang Rieping, Michael NilgesAbstract:The determination of macromolecular Structures requires weighting of experimental evidence relative to prior physical information. Although it can critically affect the quality of the calculated Structures, experimental data are routinely weighted on an empirical basis. At present, cross-validation is the most rigorous method to determine the best weight. We describe a general method to adaptively weight experimental data in the course of Structure Calculation. It is further shown that the necessity to define weights for the data can be completely alleviated. We demonstrate the method on a Structure Calculation from NMR data and find that the resulting Structures are optimal in terms of accuracy and structural quality. Our method is devoid of the bias imposed by an empirical choice of the weight and has some advantages over estimating the weight by cross-validation.
Kurt Wuthrich - One of the best experts on this subject based on the ideXlab platform.
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torsion angle dynamics for nmr Structure Calculation with the new program dyana
Journal of Molecular Biology, 1997Co-Authors: Peter Guntert, Christian Mumenthaler, Kurt WuthrichAbstract:Abstract The new program D yana (DYnamics Algorithm for Nmr Applications) for efficient Calculation of three-dimensional protein and nucleic acid Structures from distance constraints and torsion angle constraints collected by nuclear magnetic resonance (NMR) experiments performs simulated annealing by molecular dynamics in torsion angle space and uses a fast recursive algorithm to integrate the equations of motions. Torsion angle dynamics can be more efficient than molecular dynamics in Cartesian coordinate space because of the reduced number of degrees of freedom and the concomitant absence of high-frequency bond and angle vibrations, which allows for the use of longer time-steps and/or higher temperatures in the Structure Calculation. It also represents a significant advance over the variable target function method in torsion angle space with the R edac strategy used by the predecessor program D iana . D yana computation times per accepted conformer in the “bundle” used to represent the NMR Structure compare favorably with those of other presently available Structure Calculation algorithms, and are of the order of 160 seconds for a protein of 165 amino acid residues when using a DEC Alpha 8400 5/300 computer. Test Calculations starting from conformers with random torsion angle values further showed that D yana is capable of efficient Calculation of high-quality protein Structures with up to 400 amino acid residues, and of nucleic acid Structures.
