Michael Nilges

Crystallography & NMR system: A new software suite for macromolecular structure determination.

A new software suite, called Crystallography & NMR System (CNS), has been developed for macromolecular structure determination by X-ray crystallography or solution nuclear magnetic resonance (NMR) spectroscopy. In contrast to existing structure-determination programs, the architecture of CNS is highly flexible, allowing for extension to other structure-determination methods, such as electron microscopy and solid-state NMR spectroscopy. CNS has a hierarchical structure: a high-level hypertext markup language (HTML) user interface, task-oriented user input files, module files, a symbolic structure-determination language (CNS language), and low-level source code. Each layer is accessible to the user. The novice user may just use the HTML interface, while the more advanced user may use any of the other layers. The source code will be distributed, thus source-code modification is possible. The CNS language is sufficiently powerful and flexible that many new algorithms can be easily implemented in the CNS language without changes to the source code. The CNS language allows the user to perform operations on data structures, such as structure factors, electron-density maps, and atomic properties. The power of the CNS language has been demonstrated by the implementation of a comprehensive set of crystallographic procedures for phasing, density modification and refinement. User-friendly task-oriented input files are available for nearly all aspects of macromolecular structure determination by X-ray crystallography and solution NMR.

Determination of three‐dimensional structures of proteins from interproton distance data by hybrid distance geometry‐dynamical simulated annealing calculations

A new hybrid distance space‐real space method for determining three‐dimensional structures of proteins on the basis of interproton distance restraints is presented. It involves the following steps: (i) the approximate polypeptide fold is obtained by generating a set of substructures comprising only a small subset of atoms by projection from multi‐dimensional distance space into three‐dimensional cartesian coordinate space using a procedure known as ‘embedding’; (ii) all remaining atoms are then added by best fitting extended amino acids one residue at a time to the substructures; (iii) the resulting structures are used as the starting point for real space dynamical simulated annealing calculations. The latter involve heating the system to a high temperature followed by slow cooling in order to overcome potential barriers along the pathway towards the global minimum region. This is carried out by solving Newtons equations of motion. Unlike conventional restrained molecular dynamics, however, the non‐bonded interactions are represented by a simple van der Waals repulsion term. The method is illustrated by calculations on crambin (46 residues) and the globular domain of histone H5 (79 residues). It is shown that the hybrid method is more efficient computationally and samples a larger region of conformational space consistent with the experimental data than full metric matrix distance geometry calculations alone, particularly for large systems.

Refinement of protein structures in explicit solvent.

We present a CPU efficient protocol for refinement of protein structures in a thin layer of explicit solvent and energy parameters with completely revised dihedral angle terms. Our approach is suitable for protein structures determined by theoretical (e.g., homology modeling or threading) or experimental methods (e.g., NMR). In contrast to other recently proposed refinement protocols, we put a strong emphasis on consistency with widely accepted covalent parameters and computational efficiency. We illustrate the method for NMR structure calculations of three proteins: interleukin‐4, ubiquitin, and crambin. We show a comparison of their structure ensembles before and after refinement in water with and without a force field energy term for the dihedral angles; crambin was also refined in DMSO. Our results demonstrate the significant improvement of structure quality by a short refinement in a thin layer of solvent. Further, they show that a dihedral angle energy term in the force field is beneficial for structure calculation and refinement. We discuss the optimal weight for the energy constant for the backbone angle omega and include an extensive discussion of meaning and relevance of the calculated validation criteria, in particular root mean square Z scores for covalent parameters such as bond lengths. Proteins 2003;50:496–506.

Determination of three-dimensional structures of proteins from interproton distance data by dynamical simulated annealing from a random array of atoms Circumventing problems associated with folding

A new real space method, based on the principles of simulated annealing, is presented for determining protein structures on the basis of interproton distance restraints derived from NMR data. The method circumvents the folding problem associated with all real space methods described to date, by starting from a completely random array of atoms and introducing the force constants for the covalent, interproton distance and repulsive van der Waals terms in the target function appropriately. The system is simulated at high temperature by solving Newtons equations of motion. As the values of all force constants are very low during the early stages of the simulation, energy barriers between different folds of the protein can be overcome, and the global minimum of the target function is reliably located. Further, because the atoms are initially only weakly coupled, they can move essentially independently to satisfy the restraints. The method is illustrated using two examples of small proteins, namely crambin (46 residues) and potato carboxypeptidase inhibitor (39 residues).

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.

Architecture of the RNA polymerase II–TFIIF complex revealed by cross‐linking and mass spectrometry

Higher‐order multi‐protein complexes such as RNA polymerase II (Pol II) complexes with transcription initiation factors are often not amenable to X‐ray structure determination. Here, we show that protein cross‐linking coupled to mass spectrometry (MS) has now sufficiently advanced as a tool to extend the Pol II structure to a 15‐subunit, 670 kDa complex of Pol II with the initiation factor TFIIF at peptide resolution. The N‐terminal regions of TFIIF subunits Tfg1 and Tfg2 form a dimerization domain that binds the Pol II lobe on the Rpb2 side of the active centre cleft near downstream DNA. The C‐terminal winged helix (WH) domains of Tfg1 and Tfg2 are mobile, but the Tfg2 WH domain can reside at the Pol II protrusion near the predicted path of upstream DNA in the initiation complex. The linkers between the dimerization domain and the WH domains in Tfg1 and Tfg2 are located to the jaws and protrusion, respectively. The results suggest how TFIIF suppresses non‐specific DNA binding and how it helps to recruit promoter DNA and to set the transcription start site. This work establishes cross‐linking/MS as an integrated structure analysis tool for large multi‐protein complexes.

ARIA: automated NOE assignment and NMR structure calculation

MOTIVATION In the light of several ongoing structural genomics projects, faster and more reliable methods for structure calculation from NMR data are in great demand. The major bottleneck in the determination of solution NMR structures is the assignment of NOE peaks (nuclear Overhauser effect). Due to the high complexity of the assignment problem, most NOEs cannot be directly converted into unambiguous inter-proton distance restraints. RESULTS We present version 1.2 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of NOE data and NMR structure calculation. We summarize recent progress in correcting for spin diffusion with a relaxation matrix approach, representing non-bonded interactions in the force field and refining final structures in explicit solvent. We also discuss book-keeping, data exchange with spectra assignment programs and deposition of the analysed experimental data to the databases. AVAILABILITY ARIA 1.2 is available from: http://www.pasteur.fr/recherche/unites/Binfs/aria/. SUPPLEMENTARY INFORMATION XML DTDs (for chemical shifts and NOE crosspeaks), Python scripts for the conversion of various NMR data formats and the results of example calculations using data from the S. cerevisiae HRDC domain are available from: http://www.pasteur.fr/recherche/unites/Binfs/aria/

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. Proteins 2005.

Three−dimensional structure and stability of the KH domain: molecular insights into the fragile X syndrome

The KH module is a sequence motif found in a number of proteins that are known to be in close association with RNA. Experimental evidence suggests a direct involvement of KH in RNA binding. The human FMR1 protein, which has two KH domains, is associated with fragile X syndrome, the most common inherited cause of mental retardation. Here we present the three-dimensional solution structure of the KH module. The domain consists of a stable beta alpha alpha beta beta alpha fold. On the basis of our results, we suggest a potential surface for RNA binding centered on the loop between the first two helices. Substitution of a well-conserved hydrophobic residue located on the second helix destroys the KH fold; a mutation of this position in FMR1 leads to an aggravated fragile X phenotype.

The three-dimensional structure of α1-purothionin in solution: combined use of nuclear magnetic resonance, distance geometry and restrained molecular dynamics

The determination of the three‐dimensional solution structure of α1‐purothionin using a combination of metric matrix distance geometry and restrained molecular dynamics calculations based on n.m.r. data is presented. The experimental data comprise complete sequence‐specific proton resonance assignments, a set of 310 approximate interproton distance restraints derived from nuclear Overhauser effects, 27 Ø backbone torsion angle restraints derived from vicinal coupling constants, 4 distance restraints from hydrogen bonds and 12 distance restraints from disulphide bridges. The average atomic rms difference between the final nine converged structures and the mean structure obtained by averaging their coordinates is 1.5 ± 0.1 å for the backbone atoms and 2.0 ± 0.1 å for all atoms. The overall shape of α1‐purothionin is that of the capital letter L, similar to that of crambin, with the longer arm comprising two approximately parallel α‐helices and the shorter arm a strand and a mini anti‐parallel β sheet.