Machine Learning-Guided Design of a Selective and Sensitive Serotonin Sensor Using Luciferase

Luciferase is an enzyme widely used in biology and biotechnology. It catalyzes the oxidation reaction of substrates such as luciferin, producing a fluorescent signal. Luciferase's fluorescent signal offers high sensitivity, selectivity, and temporal resolution, making it ideal for biosensors, bioimaging, and high-throughput screening.

In this paper, researchers leverage the high sensitivity and selectivity of luciferase to develop a selective and sensitive serotonin sensor. They employ machine learning algorithms to optimize the structure of luciferase, resulting in enhanced catalytic performance and increased selectivity. This method can help researchers develop more efficient and precise biosensors, providing additional tools and methods for life science research.