Biomedical Applications of Free Solution Molecular Interaction Studies

Abstract

Chemical and biomedical sciences depend heavily on interaction assays, particularly those providing structural insights. This dissertation shows that free-solution, label-free studies report molecular conformation and hydration changes upon binding. Intrinsic property changes are the mechanism allowing for unprecedented sensitivities (picomolar to femtomolar) in complex milieu, even when individual binding partners are undetectable. My research establishes that the conventional theory for predicting the signal magnitude of label-free assay methods is not applicable to the free-solution assay approach. I have proposed and validated a new model for these interaction studies, with the free-solution response function (FreeSRF), shown to be highly predictive when combined with quality structural data. The model could facilitate structural information to be obtained from a simple mix-and-read approach, the Free Solution Assay (FSA). In the course of these fundamental studies, I demonstrated an improved interferometric sensing approach, the compensated interferometer (CI), that facilitates high sensitivity nanovolume refractive index (RI) measurements and molecular interaction assays without a temperature controller. When combined with a commercially available droplet generator, the compensated interferometric reader (CIR) enables rapid, semi-automated FSA measurements. The current throughput is ~50 samples per day and requires less than 1 µL of sample per determination. To demonstrate the utility of FSA-CIR, several key biomedical applications were undertaken. The first was the quantification of chemical nerve agents in serum and the second was assays for quantification of 6 opioids in urine. Then capitalizing on the potential for FSA-CIR to provide 40-fold better sensitivity for the serum biomarker CYFRA 21-1 than the current gold standard, I used FSA-CIR to measure CYFRA 21-1 in a 225-patient cohort of patients with indeterminate pulmonary nodules, demonstrating improved discriminatory power for benign vs malignant nodules. This research paves the way for the implementation of biomarker analysis in the detection, diagnosis and treatment of lung cancer.