Nanocarbon-assisted biosensor for diagnosis of exhaled biomarkers of lung cancer: DFT approach

Abstract

Density functional theory (DFT) calculations were performed to investigate a nanocarbon-assisted biosensor for diagnosis of exhaled biomarkers of lung cancer. To this aim, an oxidized model of C-20 fullerene (OC) was chosen as the surface for adsorbing each of five remarkable volatile organic compounds (VOC) biomarkers including hydrogen cyanide, methanol, methyl cyanide, isoprene, and 1-propanol designated by B1-B5. Geometries of the models were first optimized to achieve the minimum energy structures to be involved in further optimization of B@OC bi-molecular complexes. The relaxation of B counterparts at the surface of OC provided insightful information for capability of the investigated system for possible diagnosis of such biomarkers. In this case, B1 was placed at the highest rank of adsorption to make the strongest B1@OC complex among others whereas the weakest complex was seen for B4@OC complex. The achievement was very much important for differential detection of each of VOC biomarkers by the investigated OC nanocarbon. Moreover, the recorded infrared spectra indicated that the complexes could be very well recognized in complex forms and also among other complexes. As a final remark, such proposed nanocarbon-assisted biosensor could work for diagnosis of remarkable VOC biomarkers of lung cancer.