Computational Characterization of Aptamer-Based Molecular Recognition of RNA Binding Motif Protein 47 (RBM47) Protein as a Diagnostic Biomarker in Glioma

Abstract

Glioma is a highly aggressive form of brain tumor arising from glial cells, which provide structural and functional support to neurons. RNA-binding motif protein 47 (RBM47) has been reported to be overex- pressed in glioma cells and may serve as a potential biomarker for disease detection. The expression levels of RBM47 have been correlated with glioma progression, suggesting its diagnostic significance. In this study, we aimed to computationally model the three-dimensional structure of RBM47 and evaluate its interaction with RNA-based aptamers for the purpose of early glioma detection. We hypothesized that the positively charged regions of RBM47 may facilitate binding to negatively charged RNA aptamers, enabling selective recognition of this protein. To investigate this, a comprehensive in silico workflow was employed, including protein structure prediction, aptamer modeling, molecular docking, and protein–aptamer interaction analysis. The molecular docking simulations identified Aptamer 2 as exhibiting the highest binding affinity to RBM47 among the candidates tested. These findings suggest that Aptamer 2 holds strong potential for use in early-stage glioma diagnostics and targeted therapeutic development. Moreover, the ability to detect RBM47 with high specificity may aid in prognostic assessments and con- tribute to more personalized treatment strategies.