Abstract

The stochastic tunneling-basin hopping method (STUN-BH) was utilized to obtain the most stable peptide S7 configuration (Ac-Ser-Ser-Phe-Pro-Gln-Pro-Asn-CONH2) adsorbed on Au(111) facet. After the most stable S7 configuration was found, molecular dynamics (MD) simulation was conducted to investigate the thermal stability between S7 and Au facet at 300 K in both vacuum and water environment. Moreover, further design sets of peptide sequences on Au(111) facet were used to compare with S7. All molecular simulations were carried out by the large-scale atomic/molecular massively parallel simulator (LAMMPS). The Amber99sb-ILDN force field was employed for modeling the interatomic interaction of peptides, and the TIP3P water was used for the water environment. The CHARMM-METAL force field was introduced to model the S7, PF8 (Ac-Pro-Phe-Ser-Pro-Phe-Ser-Pro-Phe-CONH2) and FS8 (Ac-Phe-Ser-Phe-Ser-Phe-Ser-Phe-Ser-CONH2) interactions with Au(111). The MD simulation results demonstrate that the morphology of Pro affects the adsorption stability of Phe. Therefore, we designed two sequences, PF8 and FS8, to confirm our simulation result through experiment. The present study also develops a novel low-temperature plasma synthesis method to evaluate the facet selecting performance of the designed peptide sequences of S7, PF8, and FS8. The experimental results suggest that the reduced Au atom seed is captured with the designed peptide sequences and slowing growing under room temperature for 72 hours. The experimental results are in the excellent agreement with the simulation finding that the Pro in the designed peptide sequences plays a critical role in the facet selection for Au atom stacking.

Highlights

  • Due to continuous progress in nanotechnology, nanoscale-sized catalysts with improved performance compared to their bulk counterparts have been identified

  • Peptides having fine-designed amino acid sequences may allow for accurate recognition of specific metal facets as well as having the benefit

  • For finding the mechanism S7 binds more strongly to Pt(111) and T7 binds more strongly to Pt(100)[15], Ramakrishnan used the molecular dynamics (MD) simulation to study the affinity of an individual amino acid comprised of peptides S7 and T7 attached to the Pt(111) and (100) facets

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Summary

Introduction

Due to continuous progress in nanotechnology, nanoscale-sized catalysts with improved performance compared to their bulk counterparts have been identified. The peptide interaction mechanism with unique metal facet by a numerical method is a feasible alternative to design the appropriate capping agent. For finding the mechanism S7 binds more strongly to Pt(111) and T7 binds more strongly to Pt(100)[15], Ramakrishnan used the molecular dynamics (MD) simulation to study the affinity of an individual amino acid comprised of peptides S7 and T7 attached to the Pt(111) and (100) facets. An MD and experimental study by Ruan[17] found the residue geometries, as well as their functional groups, that significantly affect the peptide interaction strength with the metal surface. By Heinz’s MD simulation results[19], it showed an amino acid OH group displays a stronger affinity to Pt(100); in contrast, the oxygen atom more strongly interacts with the Pt(111) surface. We expand the simulation results into designing two new peptide capping agents, PF8 and FS8, for Au(111) facet and confirm the feasibility of these two capping agents by both simulation and experimental approaches without repeating the experimental trial-and-error process[12]

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