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Updated: Jun 24, 2026

Synthetic Methodology for Asymmetric Ferrocene Derived Bio-conjugate Systems via Solid Phase Resin-based Methodology

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Published on: March 12, 2015

Molecular biosensor based on a coordinated iron complex.

Karim Salazar-Salinas¹, Luis A Jauregui, Carlos Kubli-Garfias

¹Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843-3122, USA.

The Journal of Chemical Physics

|March 19, 2009

Summary

This study presents a biosensor model for detecting nitric oxide and carbon monoxide. The biosensor shows varying detection capabilities, with nitric oxide being more detectable than carbon monoxide.

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Analyzing Dynamic Protein Complexes Assembled On and Released From Biolayer Interferometry Biosensor Using Mass Spectrometry and Electron Microscopy

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Published on: August 6, 2018

Area of Science:

Biochemistry
Computational Chemistry
Spectroscopy

Background:

Soluble guanylate cyclase (sGC) is a key enzyme in cellular signaling.
Nitric oxide (NO) is a crucial signaling molecule regulated by sGC.
Developing selective sensors for gaseous ligands is important for biological and environmental monitoring.

Purpose of the Study:

To model and test a biosensor based on the porphyrin nucleus of sGC.
To assess the sensor's ability to detect nitric oxide (NO) and carbon monoxide (CO).
To investigate molecular oxygen (O2) as a potential interferent.

Main Methods:

Density functional theory (DFT) for geometries and electronic structures.
Calculation of vibrational circular dichroism (VCD), infrared (IR), and Raman spectra.
Modeling iron complexes coordinated with gas moieties (NO, CO, O2).

Main Results:

The sensor model demonstrated detection capabilities for NO and CO.
Nitric oxide was found to be more detectable than carbon monoxide.
Ligand binding orientation influenced detectability: CO aligned with iron, while NO and O2 bent at an angle detectable by VCD.

Conclusions:

The proposed biosensor shows potential for detecting and quantifying gaseous ligands.
The sensor's selectivity is influenced by the binding orientation of the gas molecule.
This approach could be extended to detect environmental pollutants.