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- (33j) Molecular Modeling of Nanoplastic-Binding Peptides for Polystyrene Capture
2025 AIChE Annual Meeting
(33j) Molecular Modeling of Nanoplastic-Binding Peptides for Polystyrene Capture
New materials and methods are needed to mitigate nanoplastic pollution, which arises from the
breakdown of larger plastic waste and poses significant health and environmental concerns.
Peptide-based materials are attractive candidates for targeting nanoplastics, due to their innate
ability to perform functions with highly specific molecular recognition. However, the vast design
space of amino acid sequences necessitates computational methods for screening, identifying,
and optimizing peptide sequences capable of selective binding to target plastics. We approach
this challenge by using molecular dynamics simulations with neural network-based enhanced
sampling methods to study the thermodynamics that underlie peptide-plastic binding and
identify key motifs in successful binding sequences. In this work, we focus on modeling multiple
plastic binding peptides (PBPs) that target nanoscale polystyrene. We present a series of free
energy calculations and analysis of binding configurations for these polystyrene-binding
candidates, establishing a fundamental understanding of successful polystyrene capture by
PBPs and informing future development and optimization of nanoplastic-sequestering materials.
breakdown of larger plastic waste and poses significant health and environmental concerns.
Peptide-based materials are attractive candidates for targeting nanoplastics, due to their innate
ability to perform functions with highly specific molecular recognition. However, the vast design
space of amino acid sequences necessitates computational methods for screening, identifying,
and optimizing peptide sequences capable of selective binding to target plastics. We approach
this challenge by using molecular dynamics simulations with neural network-based enhanced
sampling methods to study the thermodynamics that underlie peptide-plastic binding and
identify key motifs in successful binding sequences. In this work, we focus on modeling multiple
plastic binding peptides (PBPs) that target nanoscale polystyrene. We present a series of free
energy calculations and analysis of binding configurations for these polystyrene-binding
candidates, establishing a fundamental understanding of successful polystyrene capture by
PBPs and informing future development and optimization of nanoplastic-sequestering materials.