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Noncrystallographic symmetry is automatically detected and used to achieve higher completeness and greater accuracy of automatically built protein structures at resolutions of 2.3 Å or poorer., A novel method is presented for the automatic detection of noncrystallographic symmetry (NCS) in macromolecular crystal structure determination which does not require the derivation of molecular masks or the segmentation of density. It was found that throughout structure determination the NCS-related parts may be differently pronounced in the electron density. This often results in the modelling of molecular fragments of variable length and accuracy, especially during automated model-building procedures. These fragments were used to identify NCS relations in order to aid automated model building and refinement. In a number of test cases higher completeness and greater accuracy of the obtained structures were achieved, specifically at a crystallo­graphic resolution of 2.3 Å or poorer. In the best case, the method allowed the building of up to 15% more residues automatically and a tripling of the average length of the built fragments.

Motivation: To recognize remote relationships between RNA molecules, one must be able to align structures without regard to sequence similarity. We have implemented a method, which is swift [O(n2)], sensitive and tolerant of large gaps and insertions. Molecules are broken into overlapping fragments, which are characterized by their memberships in a probabilistic classification based on local geometry and H-bonding descriptors. This leads to a probabilistic similarity measure that is used in a conventional dynamic programming method. Results: Examples are given of database searching, the detection of structural similarities, which would not be found using sequence based methods, and comparisons with a previously published approach. Availability and implementation: Source code (C and perl) and binaries for linux are freely available at www.zbh.uni-hamburg.de/fries. Contact: tim.wiegels@gmail.com

The molecular viewer ArpNavigator allows easy execution of ARP/wARP model-building routines while model-update steps are shown in real time, rendering the whole process transparent to the user., Automated model-building software aims at the objective interpretation of crystallographic diffraction data by means of the construction or completion of macromolecular models. Automated methods have rapidly gained in popularity as they are easy to use and generate reproducible and consistent results. However, the process of model building has become increasingly hidden and the user is often left to decide on how to proceed further with little feedback on what has preceded the output of the built model. Here, ArpNavigator, a molecular viewer tightly integrated into the ARP/wARP automated model-building package, is presented that directly controls model building and displays the evolving output in real time in order to make the procedure transparent to the user.

Bioinformatics 29(22), 2941 - 2942 (2013). doi:10.1093/bioinformatics/btt496, There are many programs that can read the secondary structure of an RNA molecule and draw a diagram, but hardly any that can cope with 10(3) bases. RNAfdl is slow but capable of producing intersection-free diagrams for ribosome-sized structures, has a graphical user interface for adjustments and produces output in common formats. Availability and implementation: Source code is available under the GNU General Public License v3.0 at http://sourceforge.net/projects/rnafdl for Linux and similar systems or Windows using MinGW. RNAfdl is implemented in C, uses the Cairo 2D graphics library and offers both command line and graphical user interfaces., Published by Oxford University Press, Oxford

The ARP/wARP software project combines automated model building and refinement into an unified approach for macromolecular crystal structure determination. The project is based on two decades of extensive research and development in the areas of macromolecular X-ray crystallography, informatics, data mining and statistical pattern recognition. ARP/wARP collects a vast amount of computationally efficient methods and provides easy-to-use pipelines for building models of proteins, nucleotides, ligands, as well as their complexes. All methods are intuitively accessible from the ArpNavigator [1], which grants direct visualisation and real-time interaction with model building results. Structures determined using ARP/wARP include histones, hsp70, viral proteases, an insect antifreeze protein, transferases, deadenylases, synthases, kinases, photolyases and the spliceosome. The novel release of ARP/wARP, version 7.4, comes with notable innovations for determining structures at medium-to-low resolution such as exploitation of non-crystallographic symmetry, improved protocols for model update and estimation of validity of built models. Joint releases with the CCP4 suite improve software development and integration, and make the installation and updates fast and convenient for the user. A novel procedure for the automatic identification of ligands in electron density maps is introduced. It is based on the sparse parameterisation of density clusters and the matching of the pseudo-atomic grids thus created to conformationally variant ligands using mathematical descriptors of molecular shape, size and topology. The integration of the ViCi web-server for in-silico ligand-based drug design and updated stereo-chemical restraints for ligand fitting make ARP/wARP an asset for crystallographic drug discovery pipelines.

Telomeres are regions of non-coding DNA that cap the chromosomes, preventing the loss of coding DNA during cell division and contributing to chromosomal stability. In actively dividing cells, such as embryonic stem cells, the telomeres need to elongated by telomerase. The telomerase complex consist of the enzyme telomerase reverse transcriptase (TERT), telomerase RNA (TR) and additional proteins. TERT and TR are required for the telomerase activity in vitro. Telomerase is active in vast majority of the cancer cells ensuring continuous cell division and tumor growth. Syndromes leading to premature aging are often associated with short telomeres. Finding ways to regulate the telomerase activity would help to advance therapies for these conditions. However, the structural information available of the telomerase complex is very limited. We have chosen thermophilic yeast Hansenula polymorpha as a model system due to the stability of its proteins. The N-terminal domain of the TERT is essential for telomerase activity and possibly is involved in binding of TR, telomeric DNA and additional protein components of the telomerase complex. We have crystallised the N-terminal domain of H. polymorpha TERT and, in lack of a homologious structure, produced a seleno-methionine derivative of the protein. MAD data on N-terminal domain has been collected to resolution of 2.0 Å at the PETRA-III beamline P13 (EMBL/DESY) in Hamburg. We will discuss the structure-function relationship of the N-domain and the whole TERT component.

X-ray diffraction data from flexible macromolecules and their complexes can rarely be measured to a resolution better than 3 Å. Due to a loss of detectable atomic features, the determination of low-resolution structures is beyond the current operational range of crystallographic software and requires a large amount of manual intervention. ARP/wARP [1] v7.4 generates structures that are up to 80% complete at 3.0 Å, but the completeness drops sharply as the resolution gets worse. Reduction of the model completeness is accompanied with an increase in the number of fragments built, which become shorter. Such fragments are applicable for further model building if they are correct. Though, if they are wrong they may cause the formation of incorrectly built regions in the final model. Thus, there is a need to improve fragment quality before automated model completion is applied. We exploit the vast amount of structural information deposited in the Protein Data Bank (PDB) [2], to make use of it for structural validation of built fragments. Precisely, we evaluate the conformation of each fragment. If the conformation is present in several different protein models in the PDB, it is likely to be modelled correctly in the built model and is accepted. If, on the contrary, it cannot be found in any PDB model, it is probably incorrect. Here we present the software implementation of this validation, called ValiFrag, which checks the validity of automatically built protein chain fragments by evaluating their occurrence in the PDB. Protein models from the PDB were broken into dipeptides and conformational parameters for each of these were then stored in a database. For each automatically built fragment, ValiFrag computes the probability of it to be correct according to the conformation of all possible dipeptides. It can, therefore, assess which fragments are likely to be structurally incorrect and should possibly be modified, or even removed, to improve the final model.