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.

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.

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.

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.

SUMMARYThere 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 IMPLEMENTATIONSource 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.CONTACThecker@rth.dk

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(n(2))], 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.

Determining the three-dimensional structures of large molecular assemblies is a challenging task in macromolecular X-ray crystallography (MX). Crystals of such molecules rarely diffract to high resolution. Often only noisy and inaccurate electron density maps can be obtained. Computational approaches for model building in MX have historically been focused on high-resolution data. Thus their application to data extending to lower than 3.0 A resolution is limited and typically results in incomplete and highly fragmented models. Hence, robust and fast methods that improve the completeness and the accuracy of models obtained from automated crystallographic model building routines are urgently needed, particularly to aid solution of low-resolution MX structures. In this thesis, this challenge has been addressed by the development of two approaches that use intrinsic information, which is already encoded in the model, and complementary information derived from structural databases. The first one exploits the fact that a significant proportion of crystal structures contain multiple copies of subunits or their assemblies in the asymmetric unit; based on the current content of the Protein Databank, more than 50% of structures contain such non-crystallographic symmetry (NCS). It was noticed that during automated model building with ARP/ wARP, particularly in its initial steps, NCS-related parts of the structure are often built to different extents. The reasons for that are manifold and include limited resolution of the data and poor initial phases. However, this also has a beneficial side effect. Each NCS-related copy can provide information that is not present in another one; combining this (intrinsic) information helps to advance the model building process and significantly increases the overall completeness of built structures, especially with low-resolution data. Often, the density between two built chain fragments is too poorly defined to be interpreted as part of a protein chain. Especially in the early stages of model building, this is the case for not only loops but also helices or strands. A method is introduced to fill these structural gaps with structural fragments from the PDB. It makes use of secondary structure predictions and statistical descriptions of the relationship between gap size and and the number of missing residues to identify connectable chains fragments. The two novel methods that were developed in this thesis have been integrated into the ARP/ wARP protein model building; the Protein NCS-based Structure (PNS) extender for using automatically detected NCS-relations for model extension and restraints in structure refinement and FittOFF (Fitting OF Fragments) for identifying structural gaps and filling them with fragments from the PDB. The application of both methods during model building with ARP/ wARP provides a significant improvement. In the best case for the PNSextender, model completeness improves from 56% to 72% at 3.2 A resolution. Additionally, more side chains are docked in sequence, and the length of the built fragments increases. For FittOFF, a noticeable increase in model completeness of up to 12% and doubling of the average fragment length was observed. Das Ziel der Makromolekularen Rontgenbeugung (MX) ist die Bestimmung der dreidimensionalen Strukturen von Molekulen. Eine besondere Herausforderung stellt die Strukturbestimmung von grossen Makromolekulen und deren Komplexen dar, welche bislang oft gar nicht moglich oder mit grossem Aufwand verbunden ist. Das Hauptproblem liegt darin, dass fur die Kristalle solcher Molekule wahrend eines Diffraktionsexperimentes nur selten Daten mit hoher Auflosung gemessen werden konnen. Das Ergebnis sind oft verrauschte und ungenaue Elektronendichtekarten. Ein weiteres Problemliegt darin, dass die bislang entwickelte Software fur automatische Modellierung in MX weitgehend auf hochaufgeloste Daten ausgelegt ist. Es ist zwar moglich diese auf niedrigaufgeloste Daten (unter 3.0 A) anzuwenden, die resultierenden Strukturmodelle sind jedoch meist unvollstandig und stark fragmentiert. Es besteht also der dringende Bedarf fur robuste und effiziente Methoden, welche die Vollstandigkeit und Genauigkeit von niedrigaufgelosten Strukturmodellen verbessern. In dieser Dissertation werden zwei Methoden vorgestellt, welche die Qualitat von Strukturmodellen basierend auf niedrigaufgelosten Daten deutlich verbessern. Hierfur werden vorhandene Informationen, die entweder intrinsisch, also in den zu analysierenden Daten bereits enthalten, oder komplementar, aus Datenbanken gewonnen, genutzt. Die erste Methode basiert darauf, dass viele Makromolekule multiple Kopien ihrer Teilstrukturen in der asymmetrischen Einheit aufweisen. Im Jahr 2012 beinhalteten mehr als 50% aller Kristallstrukturen in der Proteindatenbank (PDB) jene sogenannte Nichtkristalline Symmetrie (NCS). Bei der automatischen Modellierung in ARP/ wARP werden diese NCS-Teilstrukturen selten im gleichen Umfang rekonstruiert, insbesondere in den anfanglichen Zyklen. Die Grunde hierfur konnen von limitierter Auflosung bis hin zu schlechten initialen Phasen reichen. Die Tatsache, dass NCS-Teilstrukturen zu unterschiedlichen Graden modelliert werden, hat den Vorteil, dass jede dieser Teilstrukturen Informationen beinhalten kann die in einer anderen fehlen. Die Kombination dieser (intrinsischen) Informationen fuhrt zu einer Verbesserung der Vollstandigkeit der resultierenden Strukturmodelle, besonders wenn Daten mit niedriger Auflosung zu Grunde liegen. Die Fragmentierung von Strukturmodellen, basierend auf niedrigaufgelosten Daten, beruht auf der oft nicht ausreichenden Qualitat der Elektronendichte um Peptide eindeutig zu erkennen, und somit eine kontinuierliche Proteinkette aufbauen zu konnen. Insbesondere zu Beginn der automatischen Modellierung betrifft dies nicht nur Loops, sondern auch Helices oder Faltblatter. In der zweiten Methode, die im Zuge dieser Dissertation vorgestellt wird, werden diese strukturellen Lucken mit Strukturfragmenten aus der PDB aufgefullt. Hierfur ist eine Verbindung der richtigen Fragmente essentiell. Zur Identifikation der zu verbindenden Ankergruppen werden hier zwei Ansatze kombinert: Zum einen das Docken von Fragmenten in eine Sekundarstrukturvorhersage und zum anderen statistische Relationen zwischen der Distanz der ankernden Fragmenten zueinander und der Anzahl der fehlenden Residuen in einer strukturellen Lucke. Die beiden im Rahmen dieser Dissertation entwickelten, neuen Methoden wurden in das ARP/ wARP Proteinmodellierungsprotokoll integriert. Der Protein NCS-basierte Struktur (PNS) Extender, identifiziert NCS-Relationen automatisch und nutzt diese fur die Komplettierung von Strukturmodellen und als Restraints fur das Strukturrefinement. FittOFF (Fitten von Fragmenten) identifiziert strukturelle Lucken in unvollstandigen Strukturmodellen und fullt diese mit Strukturfragmenten aus der PDB auf. Durch die Integration beider Methoden in die ARP/ wARP Proteinmodellierung werden signifikante Verbesserungen erzielt. Der PNSextender ist in der Lage die Vollstandigkeit von Strukturmodellen bei Auflosungen um 3.2 A von 56% auf 72% zu verbessern. Des weiteren sind die resultierenden Strukturmodelle weniger fragmentiert und deutlich mehr Seitenketten werden erkannt. Mit FittOFF wird die Vollstandigkeit von Strukturmodellen um bis zu 12% erhoht und die durchschnitte Lange aller Fragmente verdoppelt.

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.

Petch-Holl dependence σ σT o = -1 2 was establish in the middle of last century.Value "k" characterize a grain boundaries ability to pass deformation from grain to grain.However, in materials with small dimesions of grains, various grains or the different phases investigators have to do with not equilibrium structure for which value "k" is not constant.Exit a lot modern studies what show about violation Petch-Holl law and it often is not carry out exactly.Chemical composition, dislocation and fine structure, texture and the grain dimension, which exert influence on the mechanical properties of polycrystals.In the present paper have shown a new sight on the grain crystallographic orientations role in polycrystals and their influence on the mechanical properties.The main topic presented paper is a theoretical approach to crystal orientation on the basis Crystallographic Indexes Periodical System (PSCI).Crystallographic indexes may be represented in form PSCI, which consist from eight groups (G) by accordance to with square indexes sum distribution.All components of axial or planar crystallographic orientations are subdivided on the seven types (N) with different lattice direction or different lattice planes (HKL) of unit cell relatively the main external internal axes of the sample.Any crystallographic orientations can be expressed across orientation symmetry groups (GSO) as four numbers (NG 1 G 2 G 3 ) in the three-dimensional space.Quantity of crystal GSO with a different unit cell equally 230 and exactly coincidient with 230 well-know space groups crystals.Physical sense of crystallographic orientations in the polycrystalline consist in the resulting symmetry them interaction with stress field.Stress field with point of view symmetry limited only 14 second-order tensor groups.On the basis superposition principle crystals and stress field appear now perhaps for study three-dimension texture and it influence on mechanical properties of different materials.For example were carry out investigation threedimensional orientations in tube steel samples with different mechanical properties: s T = 439 MPa, s B = 557 MPa, d 10 = 27%, KCV -50 = 218 245 2 -J cm , B 7 95%, and s T = 466 MPa, s B = 579 MPa, d 10 = 25%

Our method employs ab initio polyalanine models (or 'decoys'), produced in large numbers then clustered based on the presence of similar core structures.The largest of these clusters is likely to be closest to the native structure [2].Such ab initio modelling may result in an accurate prediction of the structural core of the target, but with inaccurate loops and termini.We have been developing an automated pipeline for the processing of ab initio models for use in Molecular Replacement.We show that truncation and clustering of models into ensembles can give a successful result where a single search model would fail.We find that the addition of a selection of side chains can also be used to improve the success rate.Importantly, the likely success or failure of the modelling can be predicted based on characteristics of the protein such as length and secondary structure, and by the convergence of the modelling program to produce a large cluster of models with a similar core structure.Predictions of success can be given at each stage of the pipeline as data are accumulated to give feedback to the user, and to prioritise models for use in Molecular Replacement.The pipeline has been tested on 241 proteins between 40-120 residues long, using Rosetta to produce 1000 decoys for each target.Ensembles were produced from these decoys, and Molecular Replacement carried out using MrBUMP.For 40 proteins, at least one search model was placed within 3Å of the deposited structure by MrBUMP, and in a further 42 cases, one or more search model was positioned to within 3-6Å.In 137 cases, ARP/wARP rebuilds resulted in mapping of traced residues to sequence.Of these, 71 proteins show a 50% or greater sequence coverage ratio with 20% or more of the backbone traced.We have thus shown that ab initio modelling can be a viable route to structure solution for many small proteins.Initial results with other ab initio programs show success where Rosetta models failed.Similarly, we are extending this work to other rebuilding programs such as buccaneer which may well improve performance further.This pipeline will be made freely available, and may ultimately require only the input of the protein sequence along with the experimental data.Unlike other computationally intensive methods [3], this method is suitable for modest hardware, allowing for broader adoption.

Sessions C592of biological molecules whose structures may be determined from xray diffraction data.Here, we describe a novel approach for the structure analysis of 2D IMP crystals using x-ray powder diffraction data [3].We apply our method to the recovery of the structure of the bacteriorhodopsin molecule to a resolution of 7Å.We use a priori information about unit cell lattice parameters, space group transformations and chemical composition in a bootstrap process that resolves the ambiguities associated with overlapping reflections.The measured ratios of reflections that can be resolved experimentally are used to refine the position, shape and orientation of low-resolution molecular structures within the unit cell, leading to the resolution of the remaining overlapping reflections.The molecular model is then made progressively more sophisticated as additional diffraction information is included in the analysis.Our approach can be used to provide reliable low-resolution phase information that can be further refined by the conventional methods of protein crystallography.