Oncological diseases are a major focus in medicine, with millions diagnosed each year, leading researchers to seek new diagnostic and treatment methods. One promising avenue is the development of targeted therapies and rapid diagnostic tests using recognition molecules. The pharmaceutical industry is increasingly exploring nucleic acid-based therapeutics. However, producing long oligonucleotides, especially aptamers, poses significant production challenges. This study aims to demonstrate the efficacy of using molecular modeling, supported by experimental procedures, for altering aptamer nucleotide sequences while maintaining their binding capabilities. The focus is on reducing production costs and enhancing binding dynamics by removing nonfunctional regions and minimizing nonspecific binding. A molecular modeling approach was employed to elucidate the structure of a DNA aptamer, Gli-55, facilitating the truncation of nonessential regions in the Gli-55 aptamer, which selectively binds to glioblastoma (GBM). This process aimed to produce a truncated aptamer, Gli-35, capable of forming similar structural elements to the original sequence with reduced nonspecific binding. The efficiency of the truncation was proved by flow cytometry, fluorescence polarization (FP), and confocal microscopy. The molecular design indicated that the new truncated Gli-35 aptamer retained the structural integrity of Gli-55. In vitro studies showed that Gli-35 had a binding affinity comparable to the initial long aptamer while the selectivity increased. Gli-35 internalized inside the cell faster than Gli-55 and crossed the blood-brain barrier (BBB), as demonstrated in an in vitro model. The success of this truncation approach suggests its potential applicability in scenarios where molecular target information is limited. The study highlights a strategic and resource-efficient methodology for aptamer development. By employing molecular modeling and truncation, researchers can reduce production costs and avoid trial and error in sequence selection. This approach is promising for enhancing the efficiency of therapeutic agent development, particularly in cases lacking detailed molecular target insights.