CORDIS Project
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This project develops a computational framework using Graph Neural Networks to predict peptide co-assembly behaviors. By leveraging machine learning and molecular dynamics simulations, it aims to uncover new materials and design rules for peptide-based systems, enhancing applications in drug delivery and biomaterials.
Supramolecular self-assembly is a fundamental process abundantly utilized by nature and emerging functional materials technologies ranging from drug delivery to soft semiconductor devices.
Recently, an increased focus has been placed on the multicomponent peptide co-assembly as they often display unique emergent properties that can dramatically expand the functional utility of peptide-based materials.
Still, the full potential is hindered by the combinatorial complexity of peptide-based material…
TECHNISCHE UNIVERSITAET MUENCHEN
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