Unlocking the Potential of Field Effect Transistor (FET) Biosensors: A Perspective on Methodological Advances in Computational and Molecular Biology

• Published in: Advanced Sensor Research Vol. 2; no. 11
• Main Authors: Rexha, Jesmina, Perta, Nunzio, Roscioni, Agnese, Motta, Stefano, La Teana, Anna, Maragliano, Luca, Romagnoli, Alice, Di Marino, Daniele
• Format: Journal Article
• Language: English
• Published: Stanford John Wiley & Sons, Inc 01.11.2023; Wiley-VCH
• Subjects: Alzheimer's disease; Antibodies; Antigens; Biological effects; Biology; Biomarkers; Biosensors; Cancer; Chemical sensors; computational biology; COVID-19; Dimensional stability; E coli; Electrodes; Environmental monitoring; Enzymes; Extracellular vesicles; Field effect transistors; field‐effect transistor; Glucose; Graphene; Liquid phases; Medical diagnosis; Medical research; Molecular biology; Molybdenum; Physiology; Prostate; protein engineering; Proteins; Reproducibility; Semiconductor devices; Sensors; Severe acute respiratory syndrome coronavirus 2; Signal monitoring; Target detection; Transistors
• ISSN: 2751-1219; 2751-1219
• DOI: 10.1002/adsr.202300053

Field‐effect transistor (FET)‐based sensors are increasingly gaining relevance in diagnostic, healthcare, and environmental monitoring applications. A FET operates by transducing chemical interactions between a surface‐immobilized bioreceptor and the target analyte into a detectable electrical signal. FET biosensors can detect and monitor molecules (i.e., biomarkers, small molecules, viruses, bacterias) present in liquid samples, making a “liquid gate” configuration of FETs the most suitable approach. However, this FET architecture presents dimensional constraints that affect bioreceptors’ stability and immobilization in the liquid phase. To overcome these limitations, herein, a combination of computational and molecular biology techniques for improving bioreceptors' applicability in biosensing is proposed. This results in the optimized and problem‐tailored protein receptors for specific FET biosensors applications, thus enhancing their overall performance. The interplay between the computational and experimental approaches will represent a ground‐breaking solution for the development of next‐generation biosensors.