title: Prospective virtual screening with Ultrafast Shape Recognition: the identification of novel inhibitors of arylamine N-acetyltransferases.
abstract: There is currently a shortage of chemical molecules that can be used as bioactive probes to study molecular targets and potentially as starting points for drug discovery. One inexpensive way to address this problem is to use computational methods to screen a comprehensive database of small molecules to discover novel structures that could lead to alternative and better bioactive probes. Despite that pleasing logic the results have been somewhat mixed. Here we describe a virtual screening technique based on ligand-receptor shape complementarity, Ultrafast Shape Recognition (USR). USR is specifically applied to identify novel inhibitors of arylamine N-acetyltransferases by computationally screening almost 700 million molecular conformers in a time- and resource-efficient manner. A small number of the predicted active compounds were purchased and tested obtaining a confirmed hit rate of 40 per cent which is an outstanding result for a prospective virtual screening.
authors: Physical & Theoretical Chemistry Laboratory, University of Oxford, South Parks Road, Oxford OX1 3QZ, UK. pedro.ballester@gmail.com
authors: Pedro J
authors: PJ
authors: Ballester
authors: Isaac
authors: I
authors: Westwood
authors: Nicola
authors: N
authors: Laurieri
authors: Edith
authors: E
authors: Sim
authors: W Graham
authors: WG
authors: Richards
mesh_terms: D000465:Algorithms; D001191:Arylamine N-Acetyltransferase / Q000037:antagonists & inhibitors*; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D055808:Drug Discovery / Q000379:methods*; D004791:Enzyme Inhibitors / Q000302:isolation & purification*; D011487:Protein Conformation
chemical_list: D004791:Enzyme Inhibitors; D001191:Arylamine N-Acetyltransferase