Advancing Rational Control of Peptide–Surface Complexes

Abstract

Understanding peptide−surface interactions is crucial for programming self-assembly of peptides at surfaces and in realizing their applications, such as biosensors and biomimetic materials. In this study, we developed insights into the dependence of a residue's interaction with a surface on its neighboring residue in a tripeptide using molecular dynamics simulations. This knowledge is integral for designing rational mutations to control peptide−surface complexes. Using graphene as our model surface, we estimated the free energy of adsorption (ΔA ads ) and extracted predominant conformations of 26 tripeptides with the motif LNR−CR−Gly, where LNR and CR are variable left-neighboring and central residues, respectively. We considered a combination of strongly adsorbing (Phe, Trp, and Arg) and weakly adsorbing (Ala, Val, Leu, Ser, and Thr) amino acids on graphene identified in a prior study to form the tripeptides. Our results indicate that ΔA ads of a tripeptide cannot be estimated as the sum of ΔA ads of each residue indicating that the residues in a tripeptide do not behave as independent entities. We observed that the contributions from the strongly adsorbing amino acids were dominant, which suggests that such residues could be used for strengthening peptide−graphene interactions irrespective of their neighboring residues. In contrast, the adsorption of weakly adsorbing central residues is dependent on their neighboring residues. Our structural analysis revealed that the dihedral angles of LNR are more correlated with that of CR in the adsorbed state than in bulk state. Together with ΔA ads trends, this implies that different backbone structures of a given CR can be accessed for a similar ΔA ads by varying the LNR. Therefore, incorporation of context effects in designing mutations can lead to desired peptide structure at surfaces. Our results also emphasize that these cooperative effects in ΔA ads and structure are not easily predicted a priori. The collective results have applications in guiding rational mutagenesis techniques to control orientation of peptides at surfaces and in developing peptide structure prediction algorithms in adsorbed state from its sequence.

Molecular Driving Force for Facet Selectivity of Sequence-Defined Amphiphilic Peptoids at Au–Water Interfaces

“…We note that each Ncp analogue contributes a difference of ∼10 kJ/mol ΔF ads , which constitutes about 1/6 of the difference in ΔF ads difference for a whole chain. Our observation is consistent with the work of Dasetty and Sarupria 58 which also found that the adsorption free energy of unstructured peptides on graphene is dominated by the strongly adsorbing amino acids. The preference of aromatic groups to close-packed metal surfaces via many-body dispersion has been documented in related ab initio studies 59,60 and is well captured by the GolP-CHARMM FF (cf.…”

Size Matters: Free-Energy Calculations of Amino Acid Adsorption over Pristine Graphene

“…Other authors have carried out studies of peptide absorption over graphene in the context of single amino acid Δ A ads . − They have found that (i) single amino acid affinities are not sufficient to predict adsorption of peptides as there are cooperative effects related to the amino acid molecular context and (ii) that the adsorption process involves conformational changes which expose stronger binders and that the surface selects certain conformations due to the latter. Quite interestingly, the ΔSASA ads is a descriptor that encompasses all these factors, as it depends on the protein configuration, which is in turn a function of the molecular context of each amino acid.…”

Modeling‐Led Materials‐Binding Peptide Design for Hexagonal Boron Nitride Interfaces

“…The use of tripeptides allows an exploration of how the immediate environment around each central residue, as influenced by the residues flanking it on either side, can modify the residue/surface contact in aqueous conditions. Such tripeptide MD simulation studies have been reported for materials such as graphene [ 42,43 ] and gold [ 44 ] surfaces. However, the use of these tripeptide data has not been used to directly inform materials‐binding sequence design.…”