Detection of small organic molecules with three-dimensional biomolecule-based biosensors using bioinformatics applications

Endocrine-disrupting chemicals (EDCs) are an array of compounds, either synthetic or naturally occurring, that have the ability to mimic or interfere with the normal hormonal activity within the body upon exposure. The genesis of these substances is attributed to the consumption of polluted water, inhalation of polluted air, consumption of contaminated food, or exposure to polluted soil. As a result, biosensors have been constructed for the purpose of rapid and targeted detection of endocrine-disrupting compounds (EDCs) in environmental samples. Biosensors employ aptamers, which are biological recognition elements, in their production. Aptamers have emerged as a promising substitute for various applications, exhibiting superiority over numerous biomolecules due to their inherent advantages such as enhanced stability, reusability, artificial synthesis, and prolonged preservation. Aptamer biosensors serve a crucial role in the detection of small molecules due to these characteristics. Due to the intricacy of aptamer structure, their elucidation by conventional methods is extremely challenging. This circumstance has led to the development of three-dimensional aptamer structures based on various models and techniques. This study aims to provide an approach to predicting the 3D structures of the SS-DNA required for this sequence by initially selecting an aptamer sequence showing biosensor properties specific to BPA, one of the endocrine-disrupting chemicals detected in water samples in the literature. The present study aims to elucidate the intermolecular mechanisms and binding affinity between aptamers and endocrine-disrupting chemicals through the utilization of bioinformatics techniques such as molecular docking, molecular dynamics simulation, and binding energies. Furthermore, a comparative analysis of the reliability of different modeling programs and force fields will be conducted by assessing their correlation with experimental results reported in the literature. The results of our study using these computational strategies will provide useful information to reveal the intermolecular mechanisms and affinity required for aptamer-based biosensors and to develop a new aptamer for aptamer-based biosensors in a shorter time and at a lower cost. Keywords: Aptamer, Binding energy, Endocrine disruptive chemicals, molecular docking, molecular dynamic simulation