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Proceedings Paper

Dealing with reduced data acquisition times in Fluorescence Correlation Spectroscopy (FCS) for High-Throughput Screening (HTS) applications
Author(s): Lloyd M. Davis; David A. Ball; Peter E. Williams; Kerry M. Swift; Edmund D. Matayoshi
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Paper Abstract

Fluorescence Correlation Spectroscopy (FCS) may be used to assay the binding of drug-like ligands to signaling proteins and other bio-particles. For High Throughput Screening (HTS), a competitive format is typically used in which binding of an unlabeled compound results in displacement of a fluorescently labeled ligand. Unweighted curve-fitting of the normalized autocorrelation function (ACF) to a two-diffusion-component model can resolve the fractions of free and bound ligand if the diffusion rates differ sufficiently and if the experimentally estimated ACF has adequate precision. However, for HTS (and also for intracellular FCS studies) it is desirable to minimize the experimental data collection time. In this case, the precision of the ACF is limited and it becomes important to account for the statistical features of the ACF estimate when designing an assay. The errors at different points in the estimated ACF are correlated and hence least-squares fitting methods are not strictly statistically rigorous. We compare different methods for estimating and curve-fitting the ACF from the raw data of short duration FCS measurements. The methods are applied to data from experiments to assay binding of Alexa-488-labeled Bak peptide with Bcl-xL, which is an intracellular protein that acts to protect against programmed cell death. We present results from a detailed Monte Carlo simulation of the experiment, which is useful for validating short-duration assay capabilities. We also discuss the measurement of changes in steady state fluorescence anisotropy due to restricted rotational diffusion upon binding, which provides a complementary assay method.

Paper Details

Date Published: 18 July 2003
PDF: 12 pages
Proc. SPIE 4966, Microarrays and Combinatorial Technologies for Biomedical Applications: Design, Fabrication, and Analysis, (18 July 2003); doi: 10.1117/12.477780
Show Author Affiliations
Lloyd M. Davis, Univ. of Tennessee Space Institute (United States)
David A. Ball, Univ. of Tennessee Space Institute (United States)
Peter E. Williams, Univ. of Tennessee Space Institute (United States)
Kerry M. Swift, Abbott Labs. (United States)
Edmund D. Matayoshi, Abbott Labs. (United States)


Published in SPIE Proceedings Vol. 4966:
Microarrays and Combinatorial Technologies for Biomedical Applications: Design, Fabrication, and Analysis
Dan V. Nicolau; Ramesh Raghavachari, Editor(s)

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