Interactions at the Peptide/Silicon Surfaces: Evidence of Peptide Multilayer Assembly.

Selective deposition of peptides from liquid solutions to n- and p-doped silicon has been demonstrated. The selectivity is governed by peptide/silicon adhesion differences. A noninvasive, fast characterization of the obtained peptide layers is required to promote their application for interfacing silicon-based devices with biological material. In this study we show that spectroscopic ellipsometry-a method increasingly used for the investigation of biointerfaces-can provide essential information about the amount of adsorbed peptide material and the degree of coverage on silicon surfaces. We observed the formation of peptide multilayers for a strongly binding adhesion peptide on p-doped silicon. Application of the patterned layer ellipsometric evaluation method combined with Sellmeier dispersion led to physically consistent results, which describe well the optical properties of peptide layers in the visible spectral range. This evaluation allowed the estimation of surface coverage, which is an important indicator of adsorption quality. The ellipsometric findings were well supported by atomic force microscopy results.

Engineered Adhesion Peptides for Improved Silicon Adsorption.

Engineering peptides that present selective recognition and high affinity for a material is a major challenge for assembly-driven elaboration of complex systems with wide applications in the field of biomaterials, hard-tissue regeneration, and functional materials for therapeutics. Peptide-material interactions are of vital importance in natural processes but less exploited for the design of novel systems for practical applications because of our poor understanding of mechanisms underlying these interactions. Here, we present an approach based on the synthesis of several truncated peptides issued from a silicon-specific peptide recovered via phage display technology. We use the photonic response provided by porous silicon microcavities to evaluate the binding efficiency of 14 different peptide derivatives. We identify and engineer a short peptide sequence (SLVSHMQT), revealing the highest affinity for p(+)-Si. The molecular recognition behavior of the obtained peptide fragment can be revealed through mutations allowing identification of the preferential affinity of certain amino acids toward silicon. These results constitute an advance in both the engineering of peptides that reveal recognition properties for silicon and the understanding of biomolecule-material interactions.

Design rules for metal binding biomolecules: understanding of amino acid adsorption on platinum crystallographic facets from density functional calculations.

Understanding the mechanism of biomolecules' interaction with inorganic surfaces might pave the way for the design of material interfaces with controlled and highly predictable properties. Here we have focused on the adsorption mechanism of facet-specific amino acids in the sequence of peptides selected for programmed synthesis of Pt(111) and Pt(100) nanocrystals. Using the first principles calculations we have demonstrated that the specific surface recognition of amino acid side chains occurs due to the combination of multiple processes: electron exchange, partial charge transfer and/or dispersive effects providing a high binding affinity to both polar and non-polar residues against both Pt facets. Our approach points towards promising novel routes for controlled design of material-specific linkers for future materials engineering.

Molecular mechanism of selective binding of peptides to silicon surface.

Despite extensive recent research efforts on material-specific peptides, the fundamental problem to be explored yet is the molecular interactions between peptides and inorganic surfaces. Here we used computer simulations (density functional theory and classical molecular dynamics) to investigate the adsorption mechanism of silicon-binding peptides and the role of individual amino acids in the affinity of peptides for an n-type silicon (n(+)-Si) semiconductor. Three silicon binding 12-mer peptides previously elaborated using phage display technology have been studied. The peptides' conformations close to the surface have been determined and the best-binding amino acids have been identified. Adsorption energy calculations explain the experimentally observed different degrees of affinity of the peptides for n(+)-Si. Our residual scanning analysis demonstrates that the binding affinity relies on both the identity of the amino acid and its location in the peptide sequence.

Insights on the facet specific adsorption of amino acids and peptides toward platinum.

Engineering shape-controlled bionanomaterials requires comprehensive understanding of interactions between biomolecules and inorganic surfaces. We explore the origin of facet-selective binding of peptides adsorbed onto Pt(100) and Pt(111) crystallographic planes. Using molecular dynamics simulations, we show that upon adsorption the peptides adopt a predictable conformation. We compute the binding energies of the amino acids constituting two adhesion peptides for Pt, S7, and T7 and demonstrate that peptides' surface recognition behavior that makes them unique among populations originates from differential adsorption of their building blocks. We find that the degree of peptide binding is mainly due to polar amino acids and the molecular architecture of the peptides close to the Pt facets. Our analysis is a first step in the prediction of enhanced affinity between inorganic materials and a peptides, toward the synthesis of novel nanomaterials with programmable shape, structure, and properties.