A method for identifying small molecule aggregators using photonic crystal biosensor microplates.

Leo L. Chan, Erich A. Lidstone, Kristin E. Finch, James T. Heeres, Paul J. Hergenrother, Brian T. Cunningham

Research output: Contribution to journalArticlepeer-review


Small molecules identified through high-throughput screens are an essential element in pharmaceutical discovery programs. It is now recognized that a substantial fraction of small molecules exhibit aggregating behavior leading to false positive results in many screening assays, typically due to nonspecific attachment to target proteins. Therefore, the ability to efficiently identify compounds within a screening library that aggregate can streamline the screening process by eliminating unsuitable molecules from further consideration. In this work we show that photonic crystal (PC) optical biosensor microplate technology can be utilized to identify and quantify small molecule aggregation. A group of aggregators and nonaggregators were tested using the PC technology, and measurements were compared with those gathered by three alternative methods: dynamic light scattering (DLS), an alpha-chymotrypsin colorimetric assay, and scanning electron microscopy (SEM). The PC biosensor measurements of aggregation were confirmed by visual observation using SEM, and were in general agreement with the alpha-chymotrypsin assay. As a label-free detection method, the PC biosensor aggregation assay is simple to implement and provides a quantitative direct measurement of the mass density of material adsorbed to the transducer surface, while the microplate-based sensor format enables compatibility with high-throughput automated liquid handling methods used in pharmaceutical screening.

Original languageEnglish (US)
Pages (from-to)788-791
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
StatePublished - Dec 1 2009
Externally publishedYes

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics


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