In Silico Analysis of Cardiac Disease Protein Biomarkers by Using Aptamers

Acute myocardial infarction (AMI), also known as a heart attack, is a serious medical condition and a leading cause of death worldwide. The diagnosis of AMI relies on a combination of clinical symptoms, physical examination, electrocardiogram (ECG), and blood tests detecting elevated levels of cardiac disease protein biomarkers indicative of heart muscle injury. Nevertheless, these techniques usually necessitate skilled personnel and pose a significant economic strain. Among these biomarkers, Tumor Necrosis Factor α (TNF-α) has been identified as specific to AMI. Recently, DNA-based aptamers that specifically bind to TNF-α have been developed to detect cardiac diseases. We hypothesize that the high specificity of these aptamers towards the TNF-α protein is due to a specific binding site present on the surface of this soluble protein. Consequently, the TNF-α-aptamer interactions have been investigated by molecular docking simulations. First, the aptamer 3D structures were modeled and docked onto the TNF-α protein. By comparing the TNF-α binding site using machine learning and electrostatic surface potential analysis, the docking results were further verified. Based on these findings, novel aptamers were rationally designed by making chemical mutations and were subsequently docked onto the TNF-α protein. Among these mutate aptamers M4 binds strongly to the protein and can potentially aid in developing TNF-α biomarkers. The current investigation work will facilitate the development of rapid and highly sensitive diagnostic tools for the early detection and monitoring of cardiac diseases using aptamers.