A Method for Identifying Small Molecule Aggregators Using Photonic Crystal Biosensor Microplates 1 Leo L. Chan, 2 Erich Lidstone, 3 Kristin E. Finch, 3 James T. Heeres, 3,4 Paul J. Hergenrother, and 1 Brian T. Cunningham University of Illinois at Urbana-Champaign 1 Dept. of Electrical and Computer Engineering, Nano Sensors Group, 2 Department of Bioengineering, 3 Department of Biochemistry, 4 Department of Chemistry 1. ABSTRACT 5. DYNAMIC LIGHT SCATTERING (DLS) SURVEY OF COMPOUND LIBRARY 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 a-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 a-chymotrypsin assay. DLS measurements, in contrast, demonstrated inconsistent readings for many compounds that are found to form aggregates in shapes very different from the classical spherical particles assumed in DLS modeling. 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. 6.  -CHYMOTRYPSIN BASED INHIBITION ASSAY 7. PHOTONIC CRYSTAL BIOSENSOR ASSAY 8. PHOTONIC CRYSTAL BIOSENSOR VISUALIZATION and SCANNING ELECTRON MICROSCOPY CONFIRMATION 10. ACKNOWLEDGEMENTS 9. DETERGENT INHIBITION OF AGGREGATION 4. SMALL MOLECULE LIBRARY Particle size is determined using Mie Theory assumptions about the light scattered by sample particles in solution. Particles are assumed to be spherical and uniform in size. Fit error is highly variable, as aggregates can, in fact, form in shapes including irregular non-uniform clumps, thin sheets, and fibrous tendrils. Detergent has been shown to decrease the amount of aggregation exhibited by known promiscuous inhibitors The PC aggregation detection experiment was repeated in the presence of detergent to confirm that this decrease in aggregation could be observed using the PC biosensor When the experiment was run with 0.05% (v/v) Tween-20, marked decreases in PWV shift were observed on the PC biosensor The concentration dependence of the detergent effect is illustrated over a range of detergent concentrations (0-5%, v/v) with Congo Red 2. BACKGROUND Label-free photonic crystal optical biosensors (SRU Biosystems) have recently been demonstrated as a highly sensitive method for performing a wide variety of biochemical and cell-based assays The sensors are incorporated into SBS standard format 96, 384, and 1536-well microplates The device structure is designed to reflect only a narrow band of wavelengths when illuminated with white light at normal incidence Positive shifts of the reflected Peak Wavelength Value (PWV) indicate the adsorption of detected material on the sensor surface Cross-section schematic of the sensor with small molecule aggregate Photonic crystal sensor incorporated into multi-well microplate Peak wavelength value (PWV) shift as a result of aggregation PWV shift  -chymotrypsin cleaves succinyl-AAPF-PNA to produce an increase in absorbance at a wavelength of 405 nm. 2.Reaction rate is determined by examining the linear portion of the data set (approx. 10 min) 3.Decreases in reaction rate correspond with inhibitory activity of compounds in solution with reaction mixture 4.Increases in reaction rate may be due to the presence of spectral overlap in the sample compound 5.Several compounds were identified as promiscuous inhibitors by this assay We are grateful to the National Institutes of Health (R01 CA118562) for funding this work. The authors thankfully acknowledge SRU Biosystems for providing the photonic crystal biosensor microplates. One of the authors (BTC) is a founder of SRU Biosystems. Co-authors L. L. Chan and E. A. Lidstone contributed equally to this work. 3. INSTRUMENTATION & METHOD Readout instrument The sensor is illuminated at normal incidence and reflects a narrow band wavelengths Reflected light is collected through a detection fiber, and guided into a spectrometer Operation Reflected PWV is collected over a period of hours The collected PWV is used to generate a kinetic and endpoint plots of biomolecular binding events High throughput screen (HTS) for aggregators Select 22 compound library including aggregators and nonaggregators Screen for compound aggregation on sensor surface Confirm with existing aggregation detection assays Test compounds using dynamic light scattering (DLS) Confirm results with  -chymotrypsin inhibition assay Verify aggregation by visual inspection using scanning electron microscopy (SEM) SM Aggregate Aggregator Non-AggregatorSM Addition SA-coated biosensor The reflected narrow band of light is measured by a spectrophotometer; shifts in the peak wavelength value (PWV ) indicate binding events on the sensor surface. The streptavidin-coated biosensor is incubated with the suspected aggregator for a period of hours. PWV is monitored throughout the process. Wash Step Wash Step Drug-like compound library Congo Red serves as a control aggregator. Biotin is a control nonaggregator. The compounds selected vary in mass, functional groups, and structure All molecules were selected from an in-house small molecule library. Particle Size Fit Error 100 nm bead control Congo Red Biotin Congo Red Buffer Kinetic Profile Endpoint Read 1.Samples are incubated in microplate wells over a period of hours 2.During this time, peak wavelength (PWV) shift data is collected using the BIND TM Reader (SRU Biosystems, Woburn MA, USA) 3.After the incubation period, the sensor is washed with buffer to reduce background noise 4.Endpoint data is collected after this wash, and is useful for evaluating a number of compounds at a glance 5.Kinetic data gives more information about the rate at which the compound aggregates on the sensor 6.A steady rise in PWV indicates aggregator characteristics, as does a sharp PWV increase 7.Results were comparable to those obtained using the  -chymotrypsin inhibition assay 8.More time-efficient from a user standpoint 9.Direct assessment of the physical properties of the small molecules, no dependence on an enzymatic reaction SEM shows aggregate formation for compounds indicated by photonic crystal assay Kinetic binding profiles mirrors that of known aggregator control CR The PWV shift data shown above can be visualized using another detection instrument Compounds 8 and 19 were indicated as aggregators by the PC assay, and show increased PWV across the sensor surface The BIND TM imaging instrument (SRU Biosystems, Woburn USA) uses free-space optics to resolve binding events on the sensor surface at a resolution of 22.6  m/pixel