Human olfactory receptor 17-40 as active part of a nanobiosensor: A microscopic investigation of its electrical properties

TL;DR

This study investigates the electrical properties of human olfactory receptor 17-40 using a graph-based impedance model to understand its potential as a component in nanobiosensors for detecting odor molecules.

Contribution

It introduces a microscopic impedance modeling approach to interpret the electrical responses of the olfactory receptor, aiding in the development of protein-based nanobiosensors.

Findings

The impedance spectra vary with ligand concentration.

A unified topological scheme explains electrical responses.

Model successfully interprets experimental data.

Abstract

Increasing attention has been recently devoted to protein-based nanobiosensors. The main reason is the huge number of possible technological applications, going from drug detection to cancer early diagnosis. Their operating model is based on the protein activation and the corresponding conformational change, due to the capture of an external molecule, the so-called ligand. Recent measurements, performed with different techniques on human 17-40 olfactory receptor, evidenced a very narrow window of response in respect of the odour concentration. This is a crucial point for understanding whether the use of this olfactory receptor as sensitive part of a nanobiosensor is a good choice. In this paper we investigate the topological and electrical properties of the human olfactory receptor 17-40 with the objective of providing a microscopic interpretation of available experiments. To this purpose, we model the protein by means of a graph able to capture the mean features of the 3D backbone structure. The graph is then associated with an equivalent impedance network, able to evaluate the impedance spectra of the olfactory receptor, in its native and activated state. We assume a topological origin of the different protein electrical responses to different ligand concentrations: In this perspective all the experimental data are collected and interpreted satisfactorily within a unified scheme, also useful for application to other proteins.