Computational studies for the development of extracellular vesicle-based biosensors

Abstract

Cancer affects millions of people, and early detection and efficient treatment are two strong levers to hurdle this disease. Recent studies on exosomes, a subset of extracellular vesicles, have deliberately shown the potential to function as a biomarker or treatment tool, thereby attracting the attention of researchers who work on developing biosensors. Due to the ability of computational methods to predict of the behavior of biomolecules, the combination of experimental and computational methods would enhance the analytical performance of the biosensor, including sensitivity, accuracy, and specificity, even detecting such vesicles from bodily fluids. In this regard, the role of computational methods such as molecular docking, molecular dynamics simulation, and density functional theory is overviewed in the development of biosensors. This review highlights the investigations and studies that have been reported using these methods to design exosome-based biosensors. This review concludes with the role of the quantum mechanics/molecular mechanics method in the investigation of chemical processes of biomolecular systems and the deficiencies in using this approach to develop exosome-based biosensors. In addition, the artificial intelligence theory is explained briefly to show its importance in the study of these biosensors.