Researchers at the University of Jyväskylä have used machine learning and supercomputer simulations to explore how gold nanoparticles interact with blood proteins. By leveraging molecular dynamics data, graph theory, and neural networks, the team developed a method to predict binding sites on proteins such as serum albumin and immunoglobulin, achieving validation through atomistic simulations. This work highlights the potential of gold nanoparticles in precision nanomedicine, including targeted drug delivery and cancer therapy. The findings pave the way for new computational approaches to study nano-bio interfaces and optimize nanoparticle designs for therapeutic and diagnostic applications. The research is supported by advanced computing resources and is set to continue under new projects focused on dynamic interactions at the nanoscale.
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