Representation of target-bound drugs by computed conformers: implications for conformational libraries.
BACKGROUND
The increasing number of known protein structures provides valuable information about pharmaceutical targets. Drug binding sites are identifiable and suitable lead compounds can be proposed. The flexibility of ligands is a critical point for the selection of potential drugs. Since computed 3D structures of millions of compounds are available, the knowledge of their binding conformations would be a great benefit for the development of efficient screening methods.


RESULTS
Integration of two public databases allowed superposition of conformers for 193 approved drugs with 5507 crystallised target-bound counterparts. The generation of 9600 drug conformers using an atomic force field was carried out to obtain an optimal coverage of the conformational space. Bioactive conformations are best described by a conformational ensemble: half of all drugs exhibit multiple active states, distributed over the entire range of the reachable energy and conformational space.A number of up to 100 conformers per drug enabled us to reproduce the bound states within a similarity threshold of 1.0 angstroms in 70% of all cases. This fraction rises to about 90% for smaller or average sized drugs.


CONCLUSIONS
Single drugs adopt multiple bioactive conformations if they interact with different target proteins. Due to the structural diversity of binding sites they adopt conformations that are distributed over a broad conformational space and wide energy range. Since the majority of drugs is well represented by a predefined low number of conformers (up to 100) this procedure is a valuable method to compare compounds by three-dimensional features or for fast similarity searches starting with pharmacophores. The underlying 9600 generated drug conformers are downloadable from the Super Drug Web site 1. All superpositions are visualised at the same source. Additional conformers (110,000) of 2400 classified WHO-drugs are also available.
Günther
Stefan
S
Institute for Biochemistry, Charité, Monbijoustr, 2, 10117 Berlin, Germany. stefan.guenther@charite.de
Senger
Christian
C
Michalsky
Elke
E
Goede
Andrean
A
Preissner
Robert
R
D000595:Amino Acid Sequence; D001665:Binding Sites; D003198:Computer Simulation; D030562:Databases, Protein; D016503:Drug Delivery Systems / Q000379:methods*; D015195:Drug Design; D008956:Models, Chemical; D008958:Models, Molecular; D008969:Molecular Sequence Data; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein / Q000379:methods; D013329:Structure-Activity Relationship
D004364:Pharmaceutical Preparations; D011506:Proteins