Multivalent interactions are crucial mechanisms employed by cells to respond to their environment, often leading to superselectivity phenomena. Extensive experimental and theoretical efforts have been made to understand the variables controlling superselectivity, but challenges persist in achieving precise control over receptor and ligand numbers in biological systems. To address this, the Laan lab developed a model system using DNA origami, enabling precise manipulation of receptor and ligand numbers at the nanoscale. These nanoscopic (~15 nm) structures can mimic the receptors of a target surface, and the extracellular ligands are represented by a branched star-shaped DNA origami structure in solution. Both structures hold a fluorophore, allowing visualization using total internal reflection microscopy (TIRF) by measuring intensity values of the DNA nanostars absorbed into target surface. In this study, we investigated the effects of altering binding strength and flexibility in DNA nanostar structures on superselectivity. We found that experimental results for replicating previous experiments using the same DNA nanostars (Design A) exhibited minor variations within expected ranges, validating the reliability of the experimental protocol. However, sensitivity analysis highlighted the influence of data points on superselectivity interpretation, emphasizing the need for careful data analysis. Our study also evaluated the impact of introducing sequence mismatches on binding affinity (Design A*), revealing that modifications reducing binding affinity do not necessarily enhance superselective behavior for this system. Additionally, our investigation into the effects of increased flexibility (Design C) revealed unexpected behaviors in bound fraction and cluster formation, suggesting a potential relationship between cluster formation, intensity values registered, and the flexibility of the structure mediated by phase separation. These findings underscore the complexity of DNA nanostar behavior and stress the need for further research to elucidate the factors influencing superselectivity in DNA nanostars. By providing more understanding into how to develop highly selective particles, therapeutic molecules could sharply distinguish between healthy and corrupt cells, leading to customizable treatments with higher efficacy.