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Michael Nilges

Publications and source records attributed to Michael Nilges.

At least 19 recordsLinked to original sources
PubMed2006

Determination of dihedral Psi angles in large proteins by combining NH(N)/C(alpha)H(alpha) dipole/dipole cross-correlation and chemical shifts.

We propose a strategy based on the combination of experimental NH(N)/C(alpha)H(alpha) dipole/dipole cross-correlated relaxation rates and chemical shift analysis for the determination of Psi torsion angles in proteins. The method allows the determination of a dihedral angle that is not easily accessible by nuclear magnetic resonance (NMR). The measurement of dihedral angle restraints can be used for structure calculation, which is known to improve the quality of NMR structures. The method is of particular interest in the case of large proteins, for which spectral assignment of the nuclear Overhauser effect spectra, and therefore straightforward structural determination, is out of reach. One advantage of the method is that it is reasonably simple to implement, and could be used in association with other methods aiming at obtaining structural information on complex systems, such as residual dipolar coupling measurements. An illustrative example is analyzed in the case of the 30-kDa protein 6-phosphogluconolactonase.

Animals↗
PubMed2006

Error distribution derived NOE distance restraints.

Errors and imprecisions in distance restraints derived from NOESY peak volumes are usually accounted for by generous lower and upper bounds on the distances. In this paper, we propose a new form of distance restraints, replacing the subjective bounds by a potential function obtained from the error distribution of the distances. We derived the shape of the potential from molecular dynamics calculations and by comparison of NMR data with X-ray crystal structures. We used complete cross-validation to derive the optimal weight for the data in the calculation. In a model system with synthetic restraints, the accuracy of the structures improved significantly compared to calculations with the usual form of restraints. For experimental data sets, the structures systematically approach the X-ray crystal structures of the same protein. Also standard quality indicators improve compared to standard calculations. The results did not depend critically on the exact shape of the potential. The new approach is less subjective and uses fewer assumptions in the interpretation of NOESY peak volumes as distance restraints than the usual approach. Figures of merit for the structures, such as the RMS difference from the average structure or the RMS difference from the data, are therefore less biased and more meaningful measures of structure quality than with the usual form of restraints.

Algorithms↗
PubMed2006

Weighting of experimental evidence in macromolecular structure determination.

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.

Bias↗
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↗
PubMed2006

Flexibility and conformational entropy in protein-protein binding.

To better understand the interplay between protein-protein binding and protein dynamics, we analyzed molecular dynamics simulations of 17 protein-protein complexes and their unbound components. Complex formation does not restrict the conformational freedom of the partner proteins as a whole, but, rather, it leads to a redistribution of dynamics. We calculate the change in conformational entropy for seven complexes with quasiharmonic analysis. We see significant loss, but also increased or unchanged conformational entropy. Where comparison is possible, the results are consistent with experimental data. However, stringent error estimates based on multiple independent simulations reveal large uncertainties that are usually overlooked. We observe substantial gains of pseudo entropy in individual partner proteins, and we observe that all complexes retain residual stabilizing intermolecular motions. Consequently, protein flexibility has an important influence on the thermodynamics of binding and may disfavor as well as favor association. These results support a recently proposed unified model for flexible protein-protein association.

Animals↗
PubMed2005

Modeling errors in NOE data with a log-normal distribution improves the quality of NMR structures.

The distribution of the deviation of calculated from measured nuclear Overhauser effect (NOE) intensities is a priori unknown. The use of a log-normal distribution to describe these deviations permits the direct calculation of a structure from the measured intensities without first converting them into distance bounds. We show that the log-normal distribution is a natural choice for describing errors in NOE data and that it improves the accuracy, precision, and quality of the calculated structures compared to the usual bounds representation.

Magnetic Resonance Spectroscopy↗
PubMed2005

Bayesian inference applied to macromolecular structure determination.

The determination of macromolecular structures from experimental data is an ill-posed inverse problem. Nevertheless, conventional techniques to structure determination attempt an inversion of the data by minimization of a target function. This approach leads to problems if the data are sparse, noisy, heterogeneous, or difficult to describe theoretically. We propose here to view biomolecular structure determination as an inference rather than an inversion problem. Probability theory then offers a consistent formalism to solve any structure determination problem: We use Bayes' theorem to derive a probability distribution for the atomic coordinates and all additional unknowns. This distribution represents the complete information contained in the data and can be analyzed numerically by Markov chain Monte Carlo sampling techniques. We apply our method to data obtained from a nuclear magnetic resonance experiment and discuss the estimation of theory parameters.

Bayes Theorem↗
PubMed2005

Functional analysis of early secreted antigenic target-6, the dominant T-cell antigen of Mycobacterium tuberculosis, reveals key residues involved in secretion, complex formation, virulence, and immunogenicity.

Proteins of the 6-kDa early secreted antigenic target (ESAT-6) secretion system-1 of Mycobacterium tuberculosis are not only strongly involved in the anti-mycobacterial Th1-host immune response but are also key players for virulence. In this study, protein engineering together with bioinformatic, immunological, and virulence analyses allowed us to pinpoint regions of the ESAT-6 molecule that are critical for its biological activity in M. tuberculosis. Mutation of the Trp-Xaa-Gly motif, conserved in a wide variety of ESAT-6-like proteins, abolished complex formation with the partner protein CFP-10, induction of specific T-cell responses, and virulence. Replacement of conserved Leu residues interfered with secretion, coiled-coil formation, and virulence, whereas certain mutations at the extreme C terminus did not affect secretion but caused attenuation, possibly because of altered ESAT-6 targeting or trafficking. In contrast, the mutation of several residues on the outer surface of the four-helical bundle structure of the ESAT-6.CFP-10 complex showed much less effect. Construction of recombinant BCG expressing ESAT-6 with a C-terminal hexahistidine tag allowed us to co-purify ESAT-6 and CFP-10, experimentally confirming their strong interaction both in and outside of the mycobacterial cell. The strain induced potent, antigen-specific T-cell responses and intermediate in vivo growth in mice, suggesting that it remained immunogenic and biologically active despite the tag. Together with previous NMR data, the results of this study have allowed a biologically relevant model of the ESAT-6.CFP-10 complex to be constructed that is critical for understanding the structure-function relationship in tuberculosis pathogenesis.

Antigens, Bacterial↗
PubMed2005

Inferential structure determination.

Macromolecular structures calculated from nuclear magnetic resonance data are not fully determined by experimental data but depend on subjective choices in data treatment and parameter settings. This makes it difficult to objectively judge the precision of the structures. We used Bayesian inference to derive a probability distribution that represents the unknown structure and its precision. This probability distribution also determines additional unknowns, such as theory parameters, that previously had to be chosen empirically. We implemented this approach by using Markov chain Monte Carlo techniques. Our method provides an objective figure of merit and improves structural quality.

Algorithms↗
PubMed2005

RECOORD: a recalculated coordinate database of 500+ proteins from the PDB using restraints from the BioMagResBank.

State-of-the-art methods based on CNS and CYANA were used to recalculate the nuclear magnetic resonance (NMR) solution structures of 500+ proteins for which coordinates and NMR restraints are available from the Protein Data Bank. Curated restraints were obtained from the BioMagResBank FRED database. Although the original NMR structures were determined by various methods, they all were recalculated by CNS and CYANA and refined subsequently by restrained molecular dynamics (CNS) in a hydrated environment. We present an extensive analysis of the results, in terms of various quality indicators generated by PROCHECK and WHAT_CHECK. On average, the quality indicators for packing and Ramachandran appearance moved one standard deviation closer to the mean of the reference database. The structural quality of the recalculated structures is discussed in relation to various parameters, including number of restraints per residue, NOE completeness and positional root mean square deviation (RMSD). Correlations between pairs of these quality indicators were generally low; for example, there is a weak correlation between the number of restraints per residue and the Ramachandran appearance according to WHAT_CHECK (r = 0.31). The set of recalculated coordinates constitutes a unified database of protein structures in which potential user- and software-dependent biases have been kept as small as possible. The database can be used by the structural biology community for further development of calculation protocols, validation tools, structure-based statistical approaches and modeling. The RECOORD database of recalculated structures is publicly available from http://www.ebi.ac.uk/msd/recoord.

Databases, Protein↗
PubMed2005

Normal mode analysis suggests a quaternary twist model for the nicotinic receptor gating mechanism.

We present a three-dimensional model of the homopentameric alpha7 nicotinic acetylcholine receptor (nAChR), that includes the extracellular and membrane domains, developed by comparative modeling on the basis of: 1), the x-ray crystal structure of the snail acetylcholine binding protein, an homolog of the extracellular domain of nAChRs; and 2), cryo-electron microscopy data of the membrane domain collected on Torpedo marmorata nAChRs. We performed normal mode analysis on the complete three-dimensional model to explore protein flexibility. Among the first 10 lowest frequency modes, only the first mode produces a structural reorganization compatible with channel gating: a wide opening of the channel pore caused by a concerted symmetrical quaternary twist motion of the protein with opposing rotations of the upper (extracellular) and lower (transmembrane) domains. Still, significant reorganizations are observed within each subunit, that involve their bending at the domain interface, an increase of angle between the two beta-sheets composing the extracellular domain, the internal beta-sheet being significantly correlated to the movement of the M2 alpha-helical segment. This global symmetrical twist motion of the pentameric protein complex, which resembles the opening transition of other multimeric ion channels, reasonably accounts for the available experimental data and thus likely describes the nAChR gating process.

Amino Acid Sequence↗
PubMed2005

Replica-exchange Monte Carlo scheme for bayesian data analysis.

We develop a sampling algorithm to explore the probability densities arising in Bayesian data analysis problems. Our algorithm is a multiparameter generalization of a replica-exchange Monte Carlo scheme. The strategy relies on gradual weighing of experimental data and on Tsallis generalized statistics. We demonstrate the effectiveness of the method on nuclear magnetic resonance data for a folded protein.

Algorithms↗
PubMed2005

The impact of protein flexibility on protein-protein docking.

Accounting for protein flexibility in protein-protein docking algorithms is challenging, and most algorithms therefore treat proteins as rigid bodies or permit side-chain motion only. While the consequences are obvious when there are large conformational changes upon binding, the situation is less clear for the modest conformational changes that occur upon formation of most protein-protein complexes. We have therefore studied the impact of local protein flexibility on protein-protein association by means of rigid body and torsion angle dynamics simulation. The binding of barnase and barstar was chosen as a model system for this study, because the complexation of these 2 proteins is well-characterized experimentally, and the conformational changes accompanying binding are modest. On the side-chain level, we show that the orientation of particular residues at the interface (so-called hotspot residues) have a crucial influence on the way contacts are established during docking from short protein separations of approximately 5 A. However, side-chain torsion angle dynamics simulations did not result in satisfactory docking of the proteins when using the unbound protein structures. This can be explained by our observations that, on the backbone level, even small (2 A) local loop deformations affect the dynamics of contact formation upon docking. Complementary shape-based docking calculations confirm this result, which indicates that both side-chain and backbone levels of flexibility influence short-range protein-protein association and should be treated simultaneously for atomic-detail computational docking of proteins.

Computer Simulation↗
PubMed2005

Influence of chemical shift tolerances on NMR structure calculations using ARIA protocols for assigning NOE data.

Large-scale protein structure determination by NMR via automatic assignment of NOESY spectra requires the adjustment of several parameters for optimal performance. Among those are the chemical shift tolerance windows (delta), which allow for the compensation of badly matching chemical shifts in the assignment-list and peak-lists, and the maximum number of assignment possibilities allowed per peak (n(max)). Here, we test the influence of different values for Delta and n(max) on the performance of automated assignment of NOESY spectra by ARIA. Using Cesta.py (a Python script available from http://pasteur.fr/binfs/), we analyse the number of rejected peaks and the average number of assignments as a function of Delta and derive criteria for optimising delta and n(max) prior to structure calculation. The analysis also makes it possible to detect inconsistencies in the dataset, e.g., badly matching frequencies in the NOESY peak-lists and in the provided assignment-list. We show that ARIA can deal with a large number of assignment possibilities for each peak, provided the correct option is present, and that consequently narrow tolerances should be avoided.

Data Interpretation, Statistical↗
PubMed2005

Quantitative study of the effects of chemical shift tolerances and rates of SA cooling on structure calculation from automatically assigned NOE data.

The calculation of protein structures from nuclear magnetic resonance (NMR) data has been greatly facilitated by improvements in software for the automatic assignment of NOESY spectra. Nevertheless, for larger proteins, resonance overlap may lead to an overwhelming number of assignment options per peak. Although most software for automatic NOESY assignment can deal with a certain level of assignment ambiguity, structure calculations fail when this becomes too high. Reducing the number of assignment options per peak by reducing the chemical shift tolerances can lead to correct assignments being excluded, and thus also to incorrect structures. We have investigated, systematically, for three proteins of different size, the influence of the chemical shift tolerance limits (Delta) and of the number of simulated annealing (SA) cooling steps on the performance of the software ARIA. Large tolerance windows, and the correspondingly high levels of ambiguity, did not cause problems when appropriately slower cooling was used in our SA protocol. In cases where a high percentage of well-converged structures was not achieved, we demonstrate that it is more productive to calculate fewer structures whilst applying slow cooling, than to calculate many structures with fast cooling. In this way, high-quality structures were obtained even for proteins whose NMR spectra showed great degeneracy, and where there was much inconsistency in peak alignment between different samples. The method described herein opens the way to the automated structure determination of larger proteins from NMR data.

Algorithms↗
PubMed2005

Bayesian estimation of Karplus parameters and torsion angles from three-bond scalar couplings constants.

We apply Bayesian inference to analyze three-bond scalar coupling constants in an objective and consistent way. The Karplus curve and a Gaussian error law are used to model scalar coupling measurements. By applying Bayes' theorem, we obtain a probability distribution for all unknowns, i.e., the torsion angles, the Karplus parameters, and the standard deviation of the Gaussian. We infer all these unknowns from scalar coupling data using Markov chain Monte Carlo sampling and analytically derive a probability distribution that only involves the torsion angles.

Algorithms↗
PubMed2004

Conservation of the biochemical properties of IncA from Chlamydia trachomatis and Chlamydia caviae: oligomerization of IncA mediates interaction between facing membranes.

The developmental cycle of Chlamydiaceae occurs in a membrane compartment called an inclusion. IncA is a member of a family of proteins synthesized and secreted onto the inclusion membrane by bacteria. IncA proteins from different species of Chlamydiaceae show little sequence similarity. We report that the biochemical properties of Chlamydia trachomatis and Chlamydia caviae are conserved. Both proteins self-associate to form multimers. When artificially expressed by the host cell, they localize to the endoplasmic reticulum. Strikingly, heterologous expression of IncA in the endoplasmic reticulum completely inhibits concomitant inclusion development. Using truncated forms of IncA from C. caviae, we show that expression of the C-terminal cytoplasmic domain of the protein at the surface of the endoplasmic reticulum is sufficient to disrupt the bacterial developmental cycle. On the other hand, development of a C. trachomatis strain that does not express IncA is not inhibited by artificial IncA expression, showing that the disruptive effect observed with the wild-type strain requires direct interactions between IncA molecules at the inclusion and on the endoplasmic reticulum. Finally, we modeled IncA tetramers in parallel four helix bundles based on the structure of the SNARE complex, a conserved structure involved in membrane fusion in eukaryotic cells. Both C. trachomatis and C. caviae IncA tetramers were highly stable in this model. In conclusion, we show that the property of IncA proteins to assemble into multimeric structures is conserved between chlamydial species, and we propose that these proteins may have co-evolved with the SNARE machinery for a role in membrane fusion.

Adenocarcinoma↗