Molecular Context of Dopa Influences Adhesion of Mussel-Inspired Peptides.

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.

Assessing protein conformational sampling and structural stability via de novo design and molecular dynamics simulations.

Molecular dynamics and de novo techniques, associated to quality parameter sets, have excelled at determining the structure of small proteins with high accuracy. To achieve a detailed description of protein conformations, these methods must critically assess the thermodynamic features of the molecular ensembles. Here, a comparison of the conformational ensemble generated by molecular dynamics and de novo techniques were carried out for six Top7-based proteins carrying gp41 HIV-1 epitopes. The native Top7, a highly stable computationally designed protein, was used as benchmark. Structural stability, flexibility, and secondary structure content were assessed. The consistency of the latter was compared to experimental circular dichroism spectra for all proteins. While both methods are capable to identify the stable from unstable chimeric proteins, the sampled conformational space and flexibility differ significantly in both methods. Molecular dynamics simulations seem to better describe secondary structure content and identify regions responsible for conformational instability. The de novo method, as implemented in Rosetta-a prime tool for protein design, overestimates secondary structure content. On the other hand, its empirical energy function is capable to predict the threshold for protein stability.