| Literature DB >> 21651231 |
Jeong Heon Lee1, Hak Soo Choi, Khaled A Nasr, Miyoung Ha, Yangsun Kim, John V Frangioni.
Abstract
Encoderless combinatorial chemistry requires high-throughput product identification without the use of chemical or other tags. We developed a novel nanolayered substrate plate and combined it with a microarraying robot, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry, and custom software to produce a high-throughput small molecule identification system. To optimize system performance, we spotted 5 different chemical entities, spanning a m/z range of 195 to 1338, in 20,304 spots for a total of 101,520 molecules. The initial spot identification rate was 99.85% (20,273 spots), and after a proofreading algorithm was added, 100% of 20,304 spots and 101,520 molecules were identified. An internal recalibration algorithm also significantly improved mass accuracy to as low as 45 ppm. Using this optimized system, 47 different chemical entities, spanning a m/z range of 138 to 1,592, were spotted over 5,076 spots and could be identified with 100% accuracy. Our study lays the foundation for improved encoderless combinatorial chemistry.Entities:
Mesh:
Year: 2011 PMID: 21651231 PMCID: PMC3128203 DOI: 10.1021/ac2006735
Source DB: PubMed Journal: Anal Chem ISSN: 0003-2700 Impact factor: 6.986