Fragment-based identification of druggable ‘hot spots’ of proteins using Fourier domain correlation techniques
Author(s) -
Ryan Brenke,
Dima Kozakov,
GwoYu Chuang,
Dmitri Beglov,
David R. Hall,
Melissa Landon,
Carla Mattos,
Sándor Vajda
Publication year - 2009
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btp036
Subject(s) - druggability , fast fourier transform , small molecule , biological system , chemistry , energy (signal processing) , algorithm , computer science , physics , biology , biochemistry , quantum mechanics , gene
The binding sites of proteins generally contain smaller regions that provide major contributions to the binding free energy and hence are the prime targets in drug design. Screening libraries of fragment-sized compounds by NMR or X-ray crystallography demonstrates that such 'hot spot' regions bind a large variety of small organic molecules, and that a relatively high 'hit rate' is predictive of target sites that are likely to bind drug-like ligands with high affinity. Our goal is to determine the 'hot spots' computationally rather than experimentally.
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