4.5 Article

In Silico Design and Analysis of Plastic-Binding Peptides

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JOURNAL OF PHYSICAL CHEMISTRY B
卷 127, 期 39, 页码 8370-8381

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AMER CHEMICAL SOC
DOI: 10.1021/acs.jpcb.3c04319

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This work presents a computational, physics-based approach to design peptides that can bind to inorganic materials, specifically focusing on common plastics. The modified algorithm successfully discovers peptides with improved scores compared to the original method, and the best designs exhibit bulky side chains and specific hydrophobic and hydrophilic patches dependent on the adsorbed conformation.
Peptides that bind to inorganic materials can be used to functionalize surfaces, control crystallization, or assist in interfacial self-assembly. In the past, inorganic-binding peptides have been found predominantly through peptide library screening. While this method has successfully identified peptides that bind to a variety of materials, an alternative design approach that can intelligently search for peptides and provide physical insight for peptide affinity would be desirable. In this work, we develop a computational, physics-based approach to design inorganic-binding peptides, focusing on peptides that bind to the common plastics polyethylene, polypropylene, polystyrene, and poly(ethylene terephthalate). The PepBD algorithm, a Monte Carlo method that samples peptide sequence and conformational space, was modified to include simulated annealing, relax hydration constraints, and an ensemble of conformations to initiate design. These modifications led to the discovery of peptides with significantly better scores compared to those obtained using the original PepBD. PepBD scores were found to improve with increasing van der Waals interactions, although strengthening the intermolecular van der Waals interactions comes at the cost of introducing unfavorable electrostatic interactions. The best designs are enriched in amino acids with bulky side chains and possess hydrophobic and hydrophilic patches whose location depends on the adsorbed conformation. Future work will evaluate the top peptide designs in molecular dynamics simulations and experiment, enabling their application in microplastic pollution remediation and plastic-based biosensors.

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