Please use this identifier to cite or link to this item: https://doi.org/10.1002/qsar.200640083
Title: Small molecule microarrays: Applications using specially tagged chemical libraries
Authors: Wang, J.
Uttamchandani, M. 
Sun, H.
Yao, S.Q. 
Keywords: Chemical genetics
Combinatorial synthesis
Encoding
High-throughput screening
Microarray
Proteomics
Issue Date: Nov-2006
Citation: Wang, J., Uttamchandani, M., Sun, H., Yao, S.Q. (2006-11). Small molecule microarrays: Applications using specially tagged chemical libraries. QSAR and Combinatorial Science 25 (11) : 1009-1019. ScholarBank@NUS Repository. https://doi.org/10.1002/qsar.200640083
Abstract: Recent advances in proteomics and combinatorial synthesis have drawn impetus towards the development of robust technologies for the convenient identification of biologically relevant entities from within diverse chemical sets, as well as rapid strategies for the functional profiling of proteins. Amongst the various exciting platforms that have been developed to address these challenges, spatially addressable microarrays of small molecules have emerged as a versatile, high-density platform for high-throughput screening and analysis. The fabrication process of small molecule microarray demands that diverse molecular species and scaffolds be presented suitably for parallel screening, thereby necessitating unique design and synthetic considerations, particularly in the generation of specialized tags for encoded capture or immobilization on complementary surfaces. Of significance are the strategies that have been established to assemble organized assortments of compounds according to the downstream application requirements on microarrays. Many creative ideas have taken the technology well beyond its initial utility in lead discovery and molecular characterization, to cell-based screenings as well as protein characterization and fingerprinting. The increasing ease and expanding scale of chemical library creation, combined with the massive screening throughput offered, heralds great promise for SMM, which is set to take on wider applications in discovery, diagnostics and medicine. © 2006 Wiley-VCH Verlag GmbH & Co. KGaA.
Source Title: QSAR and Combinatorial Science
URI: http://scholarbank.nus.edu.sg/handle/10635/77652
ISSN: 1611020X
DOI: 10.1002/qsar.200640083
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