ISI Journals

Kinetic parameters play a crucial role in understanding the interactions between molecules in various biochemical processes, such as the interactions between viruses, antibodies, and trial drugs. The estimation of these parameters by experimentation is essential for this purpose. This study presents a proof-of-principle experiment that uses quantum sensing techniques to provide a more accurate estimation of kinetic parameters than the classical approach. The experiment examines the interaction of bovine serum albumin (BSA) with gold through an electrostatic mechanism. BSA is a significant protein in biochemical research and can be combined with other proteins and peptides to create sensors with high specificity. The interaction is probed in a plasmonic resonance sensor using single photons generated through parametric down-conversion. Our findings demonstrate that the sub-shot-noise level fluctuations in the sensor signal allow an improvement in precision of up to 31.8% for the kinetic parameter values. This enhancement can be increased further in principle. The study highlights the potential use of quantum states of light in biochemical sensing research. Kinetic models are essential for describing how molecules interact in a variety of biochemical processes. The estimation of a model’s kinetic parameters by experiment enables researchers to understand how pathogens, such as viruses, interact with other entities like antibodies and trial drugs. In this work, we report a simple proof-of-principle experiment that uses quantum sensing techniques to give a more precise estimation of kinetic parameters than is possible with a classical approach. The interaction we study is that of bovine serum albumin (BSA) binding to gold via an electrostatic mechanism. BSA is an important protein in biochemical research as it can be conjugated with other proteins and peptides to create sensors with a wide range of specificity. We use single photons generated via parametric down- conversion to probe the BSA-gold interaction in a plasmonic resonance sensor. We find that sub-shot- noise level fluctuations in the sensor signal allow us to achieve an improvement in the precision of up to 31.8% for the values of the kinetic parameters. This enhancement can in principle be further increased in the setup. Our work highlights the potential use of quantum states of light for sensing in biochemical research.