The interactions between nanoparticles and biological systems hold significant promise for medical applications, but understanding these complex interactions remains a major challenge. This study presents a computational biology approach utilizing GPU-accelerated simulations to investigate nanoparticle interactions in biological systems. By leveraging graphics processing units (GPUs), we developed highly scalable and efficient molecular dynamics simulations to model nanoparticle-biomolecule interactions. Our results provide novel insights into the dynamics of nanoparticle-cell membrane interactions, proteinnanoparticle binding, and nanoparticle-mediated drug delivery. The GPU-accelerated simulations demonstrate significant performance enhancements (up to 10x) compared to traditional CPU-based methods. This work has important implications for optimizing nanoparticle design, predicting toxicity, and enhancing therapeutic efficacy. Our computational framework offers a valuable tool for researchers in nanomedicine, enabling rapid exploration of nanoparticle properties and behavior in biological environments.