Cambridge Crystallographic Data Center

Cambridge, United Kingdom

Cambridge Crystallographic Data Center

Cambridge, United Kingdom
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Agency: GTR | Branch: EPSRC | Program: | Phase: Training Grant | Award Amount: 4.52M | Year: 2014

Moores Law states that the number of active components on an microchip doubles every 18 months. Variants of this Law can be applied to many measures of computer performance, such as memory and hard disk capacity, and to reductions in the cost of computations. Remarkably, Moores Law has applied for over 50 years during which time computer speeds have increased by a factor of more than 1 billion! This remarkable rise of computational power has affected all of our lives in profound ways, through the widespread usage of computers, the internet and portable electronic devices, such as smartphones and tablets. Unfortunately, Moores Law is not a fundamental law of nature, and sustaining this extraordinary rate of progress requires continuous hard work and investment in new technologies most of which relate to advances in our understanding and ability to control the properties of materials. Computer software plays an important role in enhancing computational performance and in many cases it has been found that for every factor of 10 increase in computational performance achieved by faster hardware, improved software has further increased computational performance by a factor of 100. Furthermore, improved software is also essential for extending the range of physical properties and processes which can be studied computationally. Our EPSRC Centre for Doctoral Training in Computational Methods for Materials Science aims to provide training in numerical methods and modern software development techniques so that the students in the CDT are capable of developing innovative new software which can be used, for instance, to help design new materials and understand the complex processes that occur in materials. The UK, and in particular Cambridge, has been a pioneer in both software and hardware since the earliest programmable computers, and through this strategic investment we aim to ensure that this lead is sustained well into the future.

Groom C.R.,Cambridge Crystallographic Data Center | Allen F.H.,Cambridge Crystallographic Data Center
Angewandte Chemie - International Edition | Year: 2014

The Cambridge Crystallographic Data Centre (CCDC) was established in 1965 to record numerical, chemical and bibliographic data relating to published organic and metal-organic crystal structures. The Cambridge Structural Database (CSD) now stores data for nearly 700 000 structures and is a comprehensive and fully retrospective historical archive of small-molecule crystallography. Nearly 40 000 new structures are added each year. As X-ray crystallography celebrates its centenary as a subject, and the CCDC approaches its own 50th year, this article traces the origins of the CCDC as a publicly funded organization and its onward development into a self-financing charitable institution. Principally, however, we describe the growth of the CSD and its extensive associated software system, and summarize its impact and value as a basis for research in structural chemistry, materials science and the life sciences, including drug discovery and drug development. Finally, the article considers the CCDC's funding model in relation to open access and open data paradigms. Crystal-clear data: The Cambridge Crystallographic Data Centre (CCDC) was established in 1965; its core product, the Cambridge Structural Database (CSD), stores numerical, chemical, and bibliographic data for nearly 700 000 crystal structures. As X-ray crystallography celebrates its centenary, the CCDC nears its own 50th anniversary. The origins of the CCDC and development of the CSD system is presented. The CCDC's funding model in relation to open access paradigms is also considered. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Galek P.T.A.,Cambridge Crystallographic Data Center
CrystEngComm | Year: 2011

A new method is presented to compare crystal packing based on moments of inertia tensors. The approach allows any two crystal structures to be compared irrespective of chemical connectivity. Moreover, the strictly real-space method offers significant ease of interpretation of structural comparisons. The approach allows packing similarity to be identified in otherwise disparate compounds and has the potential to lead to new insight into the influences driving molecular aggregation, crystallisation and polymorphism. The packing relationships between several examples from the Cambridge Structural Database are discussed. © 2011 The Royal Society of Chemistry.

Motherwell W.D.S.,Cambridge Crystallographic Data Center
CrystEngComm | Year: 2010

The relationship between molecular shape and packing patterns in molecular crystals has been investigated using the Cambridge Structural Database (CSD). The methodology for molecular shape uses the enclosing box based on the principal axes of inertia, with some descriptors of the amount of void space between the van der Waals surface and the faces of the rectangular box. The ratio of the molecular volume to the volume of the box, and some counts of atom types describing chemical character were also found useful. Packing descriptors are based on the molecular coordination shell of neighbours in contact with a reference molecule, usually 14-16. A set of 16 vectors between molecular centres are sorted by magnitude and stored in tabular form for a set of 133448 CSD entries, together with other descriptors such as unit cell, space group, H-bonds, etc. A computer program was written to search the table file by molecular shape within specified tolerance ranges. This allows one to select a set of molecules most similar in shape to a given target molecule, and cluster the packing patterns. Cluster analysis on the sets of 16 sorted coordination distances often shows visually recognisable structural patterns. Methods for detection of 1D and 2D substructures are discussed. There is broad correlation of packing patterns and molecular shapes classed as rods, discs and spheres and packing patterns based on partition of the 14 distances by largest gap. Case studies showing clustering of packing patterns are presented, using sets of molecules judged most similar to target CSD molecules. © 2010 The Royal Society of Chemistry.

Allen F.H.,Cambridge Crystallographic Data Center | Bruno I.J.,Cambridge Crystallographic Data Center
Acta Crystallographica Section B: Structural Science | Year: 2010

The number of structures in the Cambridge Structural Database (CSD) has increased by an order of magnitude since the preparation of two major compilations of standard bond lengths in mid-1985. It is now of interest to examine whether this huge increase in data availability has implications for the mean bond-length values published in the late 1980s. Those compilations reported mean X - H bond lengths derived from rather sparse information and for rather few chemical environments. During the intervening years, the number of neutron studies has also increased, although only by a factor of around 2.25, permitting a new analysis of X - H bond-length distributions for (a) organic X = C, N, O, B, and (b) a variety of terminal and homometallic bridging transition metal hydrides. New mean values are reported here and are compared with earlier results. These new overall means are also complemented by an analysis of X - H distances at lower temperatures (T ≤ 140 K), which indicates the general level of librational effects in X - H systems. The study also extends the range of chemical environments for which statistically acceptable mean X - H bond lengths can be obtained, although values from individual structures are also collated to further extend the chemical range of this compilation. Updated default neutron-normalization distances for use in hydrogen-bond and deformation-density studies are also proposed for C - H, N - H and O - H, and the low-temperature analysis provides specific values for certain chemical environments and hybridization states of X. © 2010 International Union of Crystallography. Printed in Singapore-all rights reserved.

Cruz-Cabeza A.J.,Cambridge Crystallographic Data Center | Cruz-Cabeza A.J.,University of Amsterdam
CrystEngComm | Year: 2012

Differences in the predicted aqueous pK a values (ΔpK a) have been calculated for 6465 crystalline complexes containing ionised and non-ionised acid-base pairs in the Cambridge Structural Database. A linear relationship between ΔpK a and the probability of proton transfer between acid-base pairs has been derived for crystalline complexes with ΔpK a between -1 and 4. The pK a rule is validated and quantitated. This journal is © The Royal Society of Chemistry 2012.

Schmidt M.F.,University of Cambridge | Korb O.,Cambridge Crystallographic Data Center | Abell C.,University of Cambridge
ACS Chemical Biology | Year: 2013

As microRNA silencing processes are mediated by the protein Argonaute 2 and for target RNA binding only a short sequence at the microRNA's 5′ end (seed region) is crucial, we report a novel inhibitor class: the microRNA-specific Argonaute 2 protein inhibitors that not only block this short recognition sequence but also bind to the protein's active site. We developed a model for rational drug design, enabling the identification of Argonaute 2 active site binders and their linkage with a peptide nucleic acid sequence (PNA), which addresses the microRNA of interest. The designed inhibitors targeting microRNA-122, a hepatitis C virus drug target, had an IC50 of 100 nM, 10-fold more active than the simple PNA sequence (IC50 of 1 μM), giving evidence that the strategy has potential. Due to their lower molecular weight, these inhibitors may show better pharmacokinetic properties than reported oligonucleotide inhibitors, enabling them for potential therapeutic use. © 2013 American Chemical Society.

Cambridge Crystallographic Data Center | Date: 2012-04-30

Provided is a computer-based method of aligning a plurality of molecules including: (i) providing one or more conformers for each molecule; (ii) identifying triplets for each conformer; (iii) determining a triplet type for each triplet; (iv) identifying a base triplet type; (v) rotating and translating the conformers having the base triplet type to overlay the conformers so that the triplets providing the base triplet type are superposed in the same orientation; (vi) for each overlayed conformer, determining a respective bit string fingerprint which encodes the 3D positions of the conformers fitting points and their respective pharmacophore features relative to the triplet providing the base triplet type; and (vii) aligning the molecules by searching the bit string fingerprints for combinations of overlayed conformers, each from a different molecule, which have high concordance in terms of pharmacophore points.

Taylor R.,Cambridge Crystallographic Data Center
CrystEngComm | Year: 2014

The tendency for an interaction to occur in crystal structures is not a simple function of its calculated energy in vacuo. This was shown by ranking intermolecular atom⋯atom interactions in organic crystal structures on the ratio (RF) of their observed frequency of occurrence to the frequency expected at random, i.e. if determined solely by the exposed surface areas of atoms. The study was based on line-of-sight interactions in structures taken from the Cambridge Structural Database. Only one interaction per atom was included in the analysis, the one with the smallest value of d-V, where d is the interatomic distance and V the sum of the atoms' van der Waals radii. 95% confidence intervals were determined for each RF value, enabling identification of interactions that occur significantly more often than expected by chance. Strong hydrogen bonds have the highest RF values, followed by two halogen-bonding interactions, I⋯N and I⋯O. These strong interactions typically occur 3 to 10 times more often than would be expected by chance. Although comparatively weak in energetic terms, C-H⋯F and C-H⋯Cl have RF values significantly in excess of the random expectation value of 1, and higher, for example, than those of Br⋯O and Cl⋯O. RF values clearly reveal the effects of polarisation on the propensity for C-halogen groups to form halogen bonds and C-H groups to form hydrogen bonds to oxygen, and highlight the dramatic differences between the interactions of phenyl and pentafluorophenyl. This journal is © the Partner Organisations 2014.

Agency: GTR | Branch: BBSRC | Program: | Phase: Training Grant | Award Amount: 96.70K | Year: 2016

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

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