Molecular Context of Dopa Influences Adhesion of Mussel-Inspired Peptides.
George D DegenKeila C CunhaZachary A LevineJ Herbert WaiteJoan-Emma SheaPublished in: The journal of physical chemistry. B (2021)
Improving adhesives for wet surfaces is an ongoing challenge. While the adhesive proteins of marine mussels have inspired many synthetic wet adhesives, the mechanisms of mussel adhesion are still not fully understood. Using surface forces apparatus (SFA) measurements and replica-exchange and umbrella-sampling molecular dynamics simulations, we probed the relationships between the sequence, structure, and adhesion of mussel-inspired peptides. Experimental and computational results reveal that peptides derived from mussel foot protein 3 slow (mfp-3s) containing 3,4-dihydroxyphenylalanine (Dopa), a post-translationally modified variant of tyrosine commonly found in mussel foot proteins, form adhesive monolayers on mica. In contrast, peptides with tyrosine adsorb as weakly adhesive clusters. We further considered simulations of mfp-3s derivatives on a range of hydrophobic and hydrophilic organic and inorganic surfaces (including silica, self-assembled monolayers, and a lipid bilayer) and demonstrated that the chemical character of the target surface and proximity of cationic and hydrophobic residues to Dopa affect peptide adsorption and adhesion. Collectively, our results suggest that conversion of tyrosine to Dopa in hydrophobic, sparsely charged peptides influences peptide self-association and ultimately dictates their adhesive performance.
Keyphrases
- molecular dynamics simulations
- biofilm formation
- amino acid
- aqueous solution
- ionic liquid
- molecular dynamics
- pseudomonas aeruginosa
- staphylococcus aureus
- molecular docking
- cell migration
- magnetic resonance
- randomized controlled trial
- escherichia coli
- candida albicans
- magnetic resonance imaging
- gene expression
- genome wide
- cystic fibrosis
- cell adhesion
- dna methylation
- high resolution
- water soluble
- monte carlo
- fatty acid
- meta analyses