Biosensors combine a molecular recognition element with a signal-conversion unit. Some biosensors have already been successfully commercialized for clinical applications, such as electrochemical blood glucose sensors. Molecular biosensors are attractive clinical diagnostic tools because they can enable real-time measurement, rapid diagnosis, multi-target analysis, automation, and reduced cost.
Advances in molecular biology have also improved our understanding of disease-related protein biomarkers and DNA mutations, making biosensors increasingly promising for early diagnosis. In general, two molecular sensing strategies are widely used: a lock-and-key approach that targets a specific analyte, and a cross-reactive or pattern-generation approach that monitors overall molecular distributions.
In the lock-and-key design, a specific bioreceptor is immobilized on a sensing surface so that it forms a strong and selective interaction with a target analyte. In practice, however, many lock-and-key biosensors still suffer from interference caused by molecules that are chemically or structurally similar to the desired target. Biomarkers themselves can also be imperfect disease indicators because many are not unique to a single disease, many diseases involve multiple biomarkers, and protein interactions in complex media such as serum can make reliable detection difficult.
These challenges motivate the use of broader biomolecular distribution patterns rather than relying on a single target molecule. The cross-reactive strategy was developed as an alternative for this purpose. Inspired by the senses of taste and smell, it uses an array of differentially responsive receptors to generate response patterns when analytes are present at elevated levels in a sample.
A key advantage of the cross-reactive method is that the individual receptors do not need to be highly specific or selective, unlike traditional lock-and-key designs that often require time-consuming and labor-intensive receptor synthesis and optimization. Our current work focuses on developing biosensor platforms based on this cross-reactive strategy.