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Principal Investigator: Hsien Wei YEH
Organization: UNIVERSITY OF CALIFORNIA SANTA CRUZ
Fiscal Year: 2023
Award: $249,000
Funding agency: National Institute of Biomedical Imaging and Bioengineering
úú PROJECT SUMMARY/ABSTRACT
Delivering diagnostic services at the point-of-care (POC) can improve the quality of healthcare in clinics, in
emergency settings, or at home, which can potentially ease hospitals’ burden, for instance, during the COVID-
19 pandemic. Precision and personalized medicine revolution also require POC testing to provide readily
available biomarker information to clinicians. The goal of this career development proposal is to create fast,
inexpensive, sensitive, and reliable molecular diagnostics to address the 21st-century healthcare challenges.
The central hypothesis is that we can efficiently utilize computational protein design to create modular
allosteric protein switches, named LOCKR (Latching Orthogonal Cage–Key pRotein), that enable the rapid
and reversible conformational changes upon interaction. As a proof of principle, we demonstrate that LOCKR-
based biosensors can be configured to produce bioluminescence upon the addition of clinical targets (e.g.,
botulinum toxin, cardiac troponin I, HER2 receptor, Fc domain, anti-HBV mAb, anti-SARS-CoV2 antibodies,
and SARS-CoV2 receptor-binding domain/spike protein, Fig 1 and 2) in homogeneous “all-in-solution”
assays. Due to the modularity of LOCKR sensor platform and the advance in de novo binder design for
arbitrary protein targets, we proposed the integration of both features as the universal strategy to develop
tailored biosensors for user-defined targets. The main specific aims for the independent phase are to
iteratively expand LOCKR-based diagnostics with the synergy of (1) de novo protein binder design to directly
detect various disease protein biomarkers, and (2) indirectly detect the antibodies that compete with the
designed interface, as POC devices; and (3) to repurpose the original luminescence signal with other
compatible readouts by exchanging the reporter modules. For more specific proof-of-concept projects during
the mentored phase, I describe in Aim 1 the use of state-of-the-art computational protein design methods to
create an interleukin-6 binder and biosensor. In Aim 2, I propose a general way to develop antibody
biosensors by demonstrating COVID-19 serological tests as an example. With my expertise in biosensor
engineering, I attempt in Aim 3 to develop a ratiometric bioluminescence resonance energy transfer (BRET)
biosensor to analyze the HBV antibody and a colorimetric biosensor to measure human cardiac troponin I
level. Ultimately, I anticipate this new sensor platform is significant for the development of robust protein
sensors that will be broadly applicable to arbitrary targets and enabling its POC compatible readouts for future
diagnostics.
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