Literature DB >> 12037325

Life-science applications of the Cambridge Structural Database.

Robin Taylor1.   

Abstract

Several studies show that the molecular geometries and intermolecular interactions observed in small-molecule crystal structures are relevant to the modelling of in vivo situations, 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 to in vacuo theoretical 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 novo ligand 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.

Mesh:

Year:  2002        PMID: 12037325     DOI: 10.1107/s090744490200358x

Source DB:  PubMed          Journal:  Acta Crystallogr D Biol Crystallogr        ISSN: 0907-4449


  11 in total

1.  Comparative analyses of three-dimensional models of bacterial reaction centers.

Authors:  A Camara-Artigas; J P Allen
Journal:  Photosynth Res       Date:  2004       Impact factor: 3.573

2.  Proper balance of solvent-solute and solute-solute interactions in the treatment of the diffusion of glucose using the Drude polarizable force field.

Authors:  Mingjun Yang; Asaminew H Aytenfisu; Alexander D MacKerell
Journal:  Carbohydr Res       Date:  2018-01-31       Impact factor: 2.104

3.  Discovering new classes of Brugia malayi asparaginyl-tRNA synthetase inhibitors and relating specificity to conformational change.

Authors:  Sai Chetan K Sukuru; Thibaut Crepin; Youli Milev; Liesl C Marsh; Jonathan B Hill; Regan J Anderson; Jonathan C Morris; Anjali Rohatgi; Gavin O'Mahony; Morten Grøtli; Franck Danel; Malcolm G P Page; Michael Härtlein; Stephen Cusack; Michael A Kron; Leslie A Kuhn
Journal:  J Comput Aided Mol Des       Date:  2006-04-28       Impact factor: 3.686

4.  New structures of hydronium cation clusters.

Authors:  Sonjae Wallace; Lulu Huang; Chérif F Matta; Lou Massa; Ivan Bernal
Journal:  C R Chim       Date:  2012-07-06       Impact factor: 3.117

Review 5.  Data-driven high-throughput prediction of the 3-D structure of small molecules: review and progress.

Authors:  Alessio Andronico; Arlo Randall; Ryan W Benz; Pierre Baldi
Journal:  J Chem Inf Model       Date:  2011-03-18       Impact factor: 4.956

6.  Applications of the Cambridge Structural Database in chemical education.

Authors:  Gary M Battle; Gregory M Ferrence; Frank H Allen
Journal:  J Appl Crystallogr       Date:  2010-08-03       Impact factor: 3.304

7.  Conformational variability of benzamidinium-based inhibitors.

Authors:  Xue Li; Xiao He; Bing Wang; Kenneth Merz
Journal:  J Am Chem Soc       Date:  2009-06-10       Impact factor: 15.419

8.  An interaction-motif-based scoring function for protein-ligand docking.

Authors:  Zhong-Ru Xie; Ming-Jing Hwang
Journal:  BMC Bioinformatics       Date:  2010-06-02       Impact factor: 3.169

9.  WebCSD: the online portal to the Cambridge Structural Database.

Authors:  Ian R Thomas; Ian J Bruno; Jason C Cole; Clare F Macrae; Elna Pidcock; Peter A Wood
Journal:  J Appl Crystallogr       Date:  2010-02-12       Impact factor: 3.304

Review 10.  Data to knowledge: how to get meaning from your result.

Authors:  Helen M Berman; Margaret J Gabanyi; Colin R Groom; John E Johnson; Garib N Murshudov; Robert A Nicholls; Vijay Reddy; Torsten Schwede; Matthew D Zimmerman; John Westbrook; Wladek Minor
Journal:  IUCrJ       Date:  2015-01-01       Impact factor: 4.769

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