Searching for stereoisomerism in crystallographic databases: algorithm, analysis and chiral curiosities

2017 ◽  
Vol 73 (3) ◽  
pp. 453-465 ◽  
Author(s):  
E. Grothe ◽  
H. Meekes ◽  
R. de Gelder
Keyword(s):  
Computer Program ◽  
Crystallographic Data ◽  
Cambridge Structural Database ◽  
Algorithm Analysis ◽  
Automated Identification ◽  
Crystallographic Databases ◽  
Multiple Structures ◽  
Ring Structures ◽  
Structural Database

The automated identification of chiral centres in molecular residues is a non-trivial task. Current tools that allow the user to analyze crystallographic data entries do not identify chiral centres in some of the more complex ring structures, or lack the possibility to determine and compare the chirality of multiple structures. This article presents an approach to identify asymmetric C atoms, which is based on the atomic walk count algorithm presented by Rücker & Rücker [(1993),J. Chem. Inf. Comput. Sci.33, 683–695]. The algorithm, which we implemented in a computer program namedChiChi, is able to compare isomeric residues based on the chiral centres that were identified. This allows for discrimination between enantiomers, diastereomers and constitutional isomers that are present in crystallographic databases.ChiChiwas used to process 254 354 organic entries from the Cambridge Structural Database (CSD). A thorough analysis of stereoisomerism in the CSD is presented accompanied by a collection of chiral curiosities that illustrate the strength and versatility of this approach.

Cluster analyses of metal-organic fragments using the dSNAP software

2009 ◽  
Vol 65 (6) ◽  
pp. 707-714
Author(s):  
Anna Collins ◽  
Chick C. Wilson ◽  
Christopher J. Gilmore
Keyword(s):  
Metal Complex ◽  
Computer Program ◽  
Cambridge Structural Database ◽  
Clustering Method ◽  
Cluster Analyses ◽  
Organic Systems ◽  
Different Types ◽  
Metal Organic ◽  
Structural Database

The dSNAP computer program has been used to classify searches of the Cambridge Structural Database for two ligands: —O—CH2—CH2—O— and N(CH2CH2O—)3 commonly found in metal-organic systems. The clustering method used is based on total geometries (i.e. all the lengths and angles involving all the atoms in the search fragment, whether bonded or not) and proved capable of distinguishing in a wholly automatic, objective way between different types of metal complex purely on the basis of the geometry of the ligand and the relative positions of the O atoms to the metals.

scholarly journals A citation analysis of the Cambridge Crystallographic Data Centre

2001 ◽  
Vol 34 (3) ◽  
pp. 375-380 ◽  
Author(s):  
Jane Redman ◽  
Peter Willett ◽  
Frank H. Allen ◽  
Robin Taylor
Keyword(s):  
Citation Analysis ◽  
Basic Research ◽  
Crystallographic Data ◽  
Cambridge Structural Database ◽  
Cambridge Crystallographic Data Centre ◽  
Research Papers ◽  
Highly Cited Papers ◽  
Data Centre ◽  
Structural Database ◽  
Highly Cited

Citation analysis has been widely used to quantify the influence of research articles on the development of science. This paper reports a citation analysis of ten highly cited papers associated with the Cambridge Crystallographic Data Centre (CCDC), covering the variation of citation with time, the journals in which citations occur, and the types of organization and the geographic regions that use the Cambridge Structural Database. The ten most highly cited papers, comprising four database descriptions (CSD), two geometrical tabulations (TAB) and four basic research papers (RES), received a total of 8494 citations over the period 1981–1998, with more than half of these citations occurring in the literature published from 1995 onwards. The high citation rates of the database descriptions (3573 of 8494) indicate the value of crystallographic data. However, the large number of citations of the geometrical tables (3172) and the research papers (1767) indicate that this value resides not just in the raw data held in the Cambridge Structural Database, but also in the structural knowledge that can be derived from it. In the most recent years covered by the analysis (1995–1998), these ten CCDC publications have received more than 1000 citations per annum (CSD 507, TAB 398 and RES 153 citations per annum) and the detailed analysis shows that these papers, and the data that they discuss, are used not only by crystallographers but also by researchers across the entire range of the chemical sciences.

scholarly journals Arrays with Local Centers of Symmetry in Space Groups Pca21 and Pna21

1998 ◽  
Vol 54 (6) ◽  
pp. 921-924 ◽  
Author(s):  
R. E. Marsh ◽  
V. Schomaker ◽  
F. H. Herbstein
Keyword(s):  
Crystallographic Data ◽  
Cambridge Structural Database ◽  
Cambridge Crystallographic Data Centre ◽  
Asymmetric Unit ◽  
Space Groups ◽  
Data Centre ◽  
Structural Database

Of the several hundred structures in the Cambridge Structural Database [version 4.6 (1992), Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge, England] having space groups Pca21 or Pna21 and more than one molecule in the asymmetric unit (Z > 4), approximately three-quarters contain local centers of symmetry. These local centers, which are not crystallographic centers, occur predominantly near x = 1\over8, y = 1\over4 in Pca21 or near x = 1\over8, y = 0 in Pna21; this also holds for the limited number of examples we have examined of pseudo-centrosymmetric molecules with Z = 4. Local centers at these points create unusual correlations between corresponding atoms in the two molecules.

Searching the Cambridge Structural Database for the `best' representative of each unique polymorph

2006 ◽  
Vol 62 (4) ◽  
pp. 567-579 ◽  
Author(s):  
Jacco van de Streek
Keyword(s):  
Crystal Structure ◽  
Computer Program ◽  
Crystal Structures ◽  
Cambridge Structural Database ◽  
Structural Database

A computer program has been written that removes suspicious crystal structures from the Cambridge Structural Database and clusters the remaining crystal structures as polymorphs or redeterminations. For every set of redeterminations, one crystal structure is selected to be the best representative of that polymorph. The results, 243 355 well determined crystal structures grouped by unique polymorph, are presented and analysed.

scholarly journals A Computational Study of Metallacycles Formed by Pyrazolate Ligands and the Coinage Metals M = Cu(I), Ag(I) and Au(I): (pzM)n for n = 2, 3, 4, 5 and 6. Comparison with Structures Reported in the Cambridge Crystallographic Data Center (CCDC)

Molecules ◽  
2020 ◽  
Vol 25 (21) ◽  
pp. 5108
Author(s):  
José Elguero ◽  
Ibon Alkorta
Keyword(s):  
Data Center ◽  
Computational Study ◽  
Crystallographic Data ◽  
Cambridge Structural Database ◽  
X Ray ◽  
Cambridge Crystallographic Data Center ◽  
Coinage Metals ◽  
Structural Database

The structures reported in the Cambridge Structural Database (CSD) for neutral metallacycles formed by coinage metals in their valence (I) (cations) and pyrazolate anions were examined. Depending on the metal, dimers and trimers are the most common but some larger rings have also been reported, although some of the larger structures are not devoid of ambiguity. M06-2x calculations were carried out on simplified structures (without C-substituents on the pyrazolate rings) in order to facilitate a comparison with the reported X-ray structures (geometries and energies). The problems of stability of the different ring sizes were also analyzed.

scholarly journals dSNAP: a computer program to cluster and classify Cambridge Structural Database searches

2005 ◽  
Vol 38 (5) ◽  
pp. 833-841 ◽  
Author(s):  
Gordon Barr ◽  
Wei Dong ◽  
Christopher J. Gilmore ◽  
Andrew Parkin ◽  
Chick C. Wilson
Keyword(s):  
Cluster Analysis ◽  
Data Processing ◽  
Computer Program ◽  
Classification Scheme ◽  
Multivariate Data ◽  
Distance Matrix ◽  
Cambridge Structural Database ◽  
Levels Of Detail ◽  
Structural Database ◽  
Visualization Tools

A computer program that automatically classifies and clusters structural fragments extracted from mining the Cambridge Structural Database is described. The methodology is based on cluster analysis and multivariate data processing of distance matrix information describing the extracted fragments. Coupled with the calculations is a set of visualization tools that enable the user to view and verify the proposed classification scheme, and further explore it in varying levels of detail. Two examples are presented: the first is based on a simple difluoroalkene fragment and the second, more complex, on a chiral vicinal dialcohol,R1(OH)CHCH(OH)R2.

Life-science applications of the Cambridge Structural Database

2002 ◽  
Vol 58 (6) ◽  
pp. 879-888 ◽  
Author(s):  
Robin Taylor
Keyword(s):  
Intermolecular Interactions ◽  
Life Science ◽  
Crystal Packing ◽  
Three Dimensional ◽  
Crystallographic Data ◽  
Cambridge Structural Database ◽  
Biologically Active ◽  
Ligand Interaction ◽  
Chemical Structures ◽  
Structural Database

Several studies show that the molecular geometries and intermolecular interactions observed in small-molecule crystal structures are relevant to the modelling ofin vivosituations, although the influence of crystal packing is sometimes important and should always be borne in mind. Torsional distributions derived from the Cambridge Structural Database (CSD) can be used to map out potential-energy surfaces and thereby help identify experimentally validated conformational minima of molecules with several rotatable bonds. The use of crystallographic data in this way is complementary toin vacuotheoretical calculations since it gives insights into conformational preferences in condensed-phase situations. Crystallographic data also underpin many molecular-fragment libraries and programs for generating three-dimensional models from two-dimensional chemical structures. The modelling of ligand binding to metalloenzymes is assisted by information in the CSD on preferred coordination numbers and geometries. CSD data on intermolecular interactions are useful in structure-based inhibitor design both in indicating how probable a protein–ligand interaction is and what its geometry is likely to be. They can also be used to guide searches for bioisosteric replacements. Crystallographically derived information has contributed to many life-science software applications, including programs for locating binding `hot spots' on proteins, docking ligands into enzyme active sites,de novoligand design, molecular superposition and three-dimensional QSAR. Overall, crystallographic data in general, and the CSD in particular, are very significant tools for the rational design of biologically active molecules.

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