How Amino Acid Sequence Impacts Peptide Adsorption to Hydrophobic Surfaces

Abstract Solid-binding peptides (SBPs) are useful for developing new biotechnology and biomaterials. Understanding how a peptide’s amino acid sequence relates to its affinity for the solid and its adsorbed conformations could facilitate SBP discovery and the development of new biotechnology. Here, we investigate this relationship by using molecular dynamics simulations to characterize the adsorption of peptides with blocky and alternating arrangements of hydrophobic (H) and hydrophilic (P) amino acids to a hydrophobic surface, polyethylene. Evaluating peptides ranging from 4 to 12 residues in length with various sets of H and P reveals that blocky and alternating arrangements generally have different adsorption free energies, stable adsorbed conformations, and tendencies for individual amino acids to be adsorbed. The differences between alternating and blocky arrangements depend on the selection of H and P; neither arrangement consistently leads to stronger peptide binding than the other arrangement. The dependence on the choice of H and P derives from amino acids competing among each other to adsorb to the surface, which depends on the bulkiness and flexibility of the amino acid side chains. Arranging the amino acid sequence to increase the peptide’s conformational freedom reduces competition between amino acids and increases peptide affinity. We thus provide insight into how a peptide’s amino acid sequence relates to its adsorption, which may aid the discovery of SBPs for polyethylene and possibly other hydrophobic plastics. Our procedure may be applied to study how sequence impacts peptide adsorption to other materials.

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Publication Details

Journal
Langmuir
Published
2026-09-28
DOI
https://doi.org/10.1021/acs.langmuir.6c03700
Primary Topic
Polymer Surface Interaction Studies
Type
article
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article

How Amino Acid Sequence Impacts Peptide Adsorption to Hydrophobic Surfaces

Carol K. Hall, Michael T. Bergman
Langmuir
Polymer Surface Interaction Studies
article

How Amino Acid Sequence Impacts Peptide Adsorption to Hydrophobic Surfaces

Carol K. Hall, Michael T. Bergman
article en

Abstract

Abstract Solid-binding peptides (SBPs) are useful for developing new biotechnology and biomaterials. Understanding how a peptide’s amino acid sequence relates to its affinity for the solid and its adsorbed conformations could facilitate SBP discovery and the development of new biotechnology. Here, we investigate this relationship by using molecular dynamics simulations to characterize the adsorption of peptides with blocky and alternating arrangements of hydrophobic (H) and hydrophilic (P) amino acids to a hydrophobic surface, polyethylene. Evaluating peptides ranging from 4 to 12 residues in length with various sets of H and P reveals that blocky and alternating arrangements generally have different adsorption free energies, stable adsorbed conformations, and tendencies for individual amino acids to be adsorbed. The differences between alternating and blocky arrangements depend on the selection of H and P; neither arrangement consistently leads to stronger peptide binding than the other arrangement. The dependence on the choice of H and P derives from amino acids competing among each other to adsorb to the surface, which depends on the bulkiness and flexibility of the amino acid side chains. Arranging the amino acid sequence to increase the peptide’s conformational freedom reduces competition between amino acids and increases peptide affinity. We thus provide insight into how a peptide’s amino acid sequence relates to its adsorption, which may aid the discovery of SBPs for polyethylene and possibly other hydrophobic plastics. Our procedure may be applied to study how sequence impacts peptide adsorption to other materials.

Langmuir
North Carolina State University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 27%
Polymer Surface Interaction Studies
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How Amino Acid Sequence Impacts Peptide Adsorption to Hydrophobic Surfaces — Carol K. Hall, Michael T. Bergman · Langmuir (2026) | TGRS Research Map | TGRS