title: 'Mutational SURF': a strategy for improving lead compounds identified from combinatorial libraries.
abstract: Synthesis and testing of mixtures of compounds in a combinatorial library offers the potential of much greater throughput than the 'one compound, one well' approach. When mixtures of compounds are screened, however, pooling and deconvolution strategies must be employed to identify the most active compound in the library. The possibility exists that the most active compound will not be identified. We have developed a theoretical model of library deconvolution using the well characterized properties of nucleic acid hybridization to calculate activities of individual molecules in libraries of more than 250,000 compounds. Calculations using this model have been employed to evaluate strategies for pooling and deconvolution. In the presence of errors in synthesis and testing, iterative deconvolution or position scanning sometimes identified a compound with sub-optimal activity. We describe a procedure called 'mutational SURF' in which 'mutants' of the selected compound are individually synthesized and tested. Simulations of mutational SURF using our model libraries suggest that mutational SURF provides an efficient method for improving the activity of lead compounds identified from combinatorial libraries.
authors.affiliation: ISIS Pharmaceuticals, Carlsbad, CA 92008, USA.
authors.forename: S M
authors.initials: SM
authors.lastname: Freier
authors.forename: D A
authors.initials: DA
authors.lastname: Konings
authors.forename: J R
authors.initials: JR
authors.lastname: Wyatt
authors.forename: D J
authors.initials: DJ
authors.lastname: Ecker
mesh_terms: D001483:Base Sequence; D003198:Computer Simulation; D008956:Models, Chemical; D008969:Molecular Sequence Data; D009010:Monte Carlo Method; D009154:Mutation; D012313:RNA / Q000737:chemistry
chemical_list: D012313:RNA