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Small details, great impacts: Controlled antibody anchoring for enhanced immunoassays
Zhiwei Liu1, Jian Yang2, Zhouyi Xiong2
1School of Life and Health Technology, Dongguan University of Technology, Dongguan 523808, China; Dongguan Food Industry Technology Innovation Center, Dongguan 523808, China.
None:
Immunoassays are essential tools in clinical diagnostics, food safety surveillance, and environmental monitoring; however, a persistent discrepancy exists between the theoretical performance of bioreceptors and their practical efficacy in sensor devices. This performance gap is largely rooted in the stochastic nature of antibody anchoring at sensing interfaces, which frequently causes surface-induced denaturation, orientational heterogeneity, and steric occlusion. This review provides a microscopic framework to elucidate these deleterious interfacial behaviors and advocates a shift from empirical trial-and-error practices toward rational, controllable interface design. We systematically categorize and evaluate strategies for controlled antibody anchoring along a passive-to-active regulation spectrum. Passive positioning strategies, including affinity-mediated capture and site-defined chemical anchoring, use external binding mediators or localized antibody modifications to guide antibodies into functional postures. By contrast, active programming approaches, including genetically engineered antibodies and anchoring guided by intrinsic antibody properties, elevate antibodies into autonomous structural components that direct their own spatial integration at interfaces. Furthermore, exploratory concepts from adjacent disciplines and possible long-range conformational effects of antibody anchoring are also briefly considered as complementary perspectives for future interface design. To resolve the field's fragmented evaluation metrics, we propose a reporting framework that integrates key measurements needed to support claims of improved antibody anchoring. Finally, challenges and future directions are outlined, emphasizing the integration of computational interface engineering, AI-guided protein design, and standardized evaluation protocols. Together, these advances chart a clear path toward predictable, robust, and optimized immunosensing platforms.
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