title: Life-science applications of the Cambridge Structural Database.
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.
authors.affiliation: Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, England. taylor@ccdc.cam.ac.uk
authors.forename: Robin
authors.initials: R
authors.lastname: Taylor
mesh_terms: D018360:Crystallography, X-Ray; D016208:Databases, Factual; D021281:Quantitative Structure-Activity Relationship