title: High-throughput small molecule identification using MALDI-TOF and a nanolayered substrate.
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.
authors.affiliation: Robotic Chemistry Group, Center for Molecular Imaging, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215, USA.
authors.forename: Jeong Heon
authors.initials: JH
authors.lastname: Lee
authors.forename: Hak Soo
authors.initials: HS
authors.lastname: Choi
authors.forename: Khaled A
authors.initials: KA
authors.lastname: Nasr
authors.forename: Miyoung
authors.initials: M
authors.lastname: Ha
authors.forename: Yangsun
authors.initials: Y
authors.lastname: Kim
authors.forename: John V
authors.initials: JV
authors.lastname: Frangioni
mesh_terms: D003460:Crystallization; D049329:Nanostructures; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*