Comparative study of materials-binding peptide interactions with gold and silver surfaces and nanostructures : A thermodynamic basis for biological selectivity of inorganic materials

Controllable 3D assembly of multicomponent inorganic nanomaterials by precisely positioning two or more types of nanoparticles to modulate their interactions and achieve multifunctionality remains a major challenge. The diverse chemical and structural features of biomolecules can generate the compositionally specific organic/inorganic interactions needed to create such assemblies. Toward this aim, we studied the materials-specific binding of peptides selected based upon affinity for Ag (AgBP1 and AgBP2) and Au (AuBP1 and AuBP2) surfaces, combining experimental binding measurements, advanced molecular simulation, and nanomaterial synthesis. This reveals, for the first time, different modes of binding on the chemically similar Au and Ag surfaces. Molecular simulations showed flatter configurations on Au and a greater variety of 3D adsorbed conformations on Ag, reflecting primarily enthalpically driven binding on Au and entropically driven binding on Ag. This may arise from differences in the interfacial solvent structure. On Au, direct interaction of peptide residues with the metal surface is dominant, while on Ag, solvent-mediated interactions are more important. Experimentally, AgBP1 is found to be selective for Ag over Au, while the other sequences have strong and comparable affinities for both surfaces, despite differences in binding modes. Finally, we show for the first time the impact of these differences on peptide mediated synthesis of nanoparticles, leading to significant variation in particle morphology, size, and aggregation state. Because the degree of contact with the metal surface affects the peptide's ability to cap the nanoparticles and thereby control growth and aggregation, the peptides with the least direct contact (AgBP1 and AgBP2 on Ag) produced relatively polydispersed and aggregated nanoparticles. Overall, we show that thermodynamically different binding modes at metallic interfaces can enable selective binding on very similar inorganic surfaces and can provide control over nanoparticle nucleation and growth. This supports the promise of bionanocombinatoric approaches that rely upon materials recognition.

Surface behaviour and lipid interaction of Alzheimer beta-amyloid peptide 1-42: a membrane-disrupting peptide

Amyloid aggregates, found in patients that suffer from Alzheimer's disease, are composed of fibril-forming peptides in a β-sheet conformation. One of the most abundant components in amyloid aggregates is the β-amyloid peptide 1–42 (Aβ 1–42). Membrane alterations may proceed to cell death by either an oxidative stress mechanism, caused by the peptide and synergized by transition metal ions, or through formation of ion channels by peptide interfacial self-aggregation. Here we demonstrate that Langmuir films of Aβ 1–42, either in pure form or mixed with lipids, develop stable monomolecular arrays with a high surface stability. By using micropipette aspiration technique and confocal microscopy we show that Aβ 1–42 induces a strong membrane destabilization in giant unilamellar vesicles composed of palmitoyloleoyl-phosphatidylcholine, sphingomyelin, and cholesterol, lowering the critical tension of vesicle rupture. Additionally, Aβ 1–42 triggers the induction of a sequential leakage of low- and high-molecular-weight markers trapped inside the giant unilamellar vesicles, but preserving the vesicle shape. Consequently, the Aβ 1–42 sequence confers particular molecular properties to the peptide that, in turn, influence supramolecular properties associated to membranes that may result in toxicity, including: 1), an ability of the peptide to strongly associate with the membrane; 2), a reduction of lateral membrane cohesive forces; and 3), a capacity to break the transbilayer gradient and puncture sealed vesicles.

First-principles based force-field for the interaction of proteins with Au(100)(5 x 1): an extension of GolP-CHARMM

Noncovalent recognition between peptides and inorganic materials is an established phenomenon. Key to exploiting these interactions in a wide range of materials self-assembly applications would be to harness the facet-selective control of peptide binding onto these materials. Fundamental understanding of what drives facet-selectivity in peptide binding is developing, but as yet is not sufficient to enable design of predictable facet-specific sequences. Computational simulation of the aqueous peptide-gold interface, commonly used to understand the mechanisms driving adsorption at an atomic level, has thus far neglected the role that surface reconstruction might play in facet specificity. Here the polarizable GolP-CHARMM suite of force fields is extended to include the reconstructed Au(100) surface. The force field, compatible with the bio-organic force field CHARMM, is parametrized using first-principles data. Our extended force field is tailored to reproduce the heterogeneity of weak chemisorbing N and S species to specific locations in the Au(100)(5 × 1) surface identified from the first-principles calculations. We apply our new model to predict and compare the three-dimensional structure of liquid water at Au(111), Au(100)(1 × 1), and Au(100)(5 × 1) interfaces. Using molecular dynamics simulations, we predict an increased likelihood for water-mediated peptide adsorption at the aqueous-Au(100)(1 × 1) interface compared with the Au(100)(5 × 1) interface. Therefore, our findings suggest that peptide binding can discriminate between the native and reconstructed Au(100) interfaces and that the role of reconstruction on binding at the Au(100) interface should not be neglected. © 2013 American Chemical Society.

Peptide-based biosensors

Peptides have been used as components in biological analysis and fabrication of novel biosensors for a number of reasons, including mature synthesis protocols, diverse structures and as highly selective substrates for enzymes. Bio-conjugation strategies can provide an efficient way to convert interaction information between peptides and analytes into a measurable signal, which can be used for fabrication of novel peptide-based biosensors. Many sensitive fluorophores can respond rapidly to environmental changes and stimuli manifest as a change in spectral characteristics, hence environmentally-sensitive fluorophores have been widely used as signal markers to conjugate to peptides to construct peptide-based molecular sensors. Additionally, nanoparticles, fluorescent polymers, graphene and near infrared dyes are also used as peptide-conjugated signal markers. On the other hand, peptides may play a generalist role in peptide-based biosensors. Peptides have been utilized as bio-recognition elements to bind various analytes including proteins, nucleic acid, bacteria, metal ions, enzymes and antibodies in biosensors. The selectivity of peptides as an enzymatic substrate has thus been utilized to construct enzyme sensors or enzyme-activity sensors. In addition, progress on immobilization and microarray techniques of peptides has facilitated the progress and commercial application of chip-based peptide biosensors in clinical diagnosis.

What makes a good graphene-binding peptide? Adsorption of amino acids and peptides at aqueous graphene interfaces

Investigation of the non-covalent interaction of biomolecules with aqueous graphene interfaces is a rapidly expanding area. However, reliable exploitation of these interfaces in many applications requires that the links between the sequence and binding of the adsorbed peptide structures be clearly established. Molecular dynamics (MD) simulations can play a key role in elucidating the conformational ensemble of peptides adsorbed at graphene interfaces, helping to elucidate these rules in partnership with experimental characterisation. We apply our recently-developed polarisable force-field for biomolecule-graphene interfaces, GRAPPA, in partnership with advanced simulation approaches, to probe the adsorption behaviour of peptides at aqueous graphene. First we determine the free energy of adsorption of all twenty naturally occurring amino acids (AAs) via metadynamics simulations, providing a benchmark for interpreting peptide-graphene adsorption studies. From these free energies, we find that strong-binding amino acids have flat and/or compact side chain groups, and we relate this behaviour to the interfacial solvent structuring. Second, we apply replica exchange with solute tempering simulations to efficiently and widely sample the conformational ensemble of two experimentally-characterised peptide sequences, P1 and its alanine mutant P1A3, in solution and adsorbed on graphene. For P1 we find a significant minority of the conformational ensemble possesses a helical structure, both in solution and when adsorbed, while P1A3 features mostly extended, random-coil conformations. In solution this helical P1 configuration is stabilised through favourable intra-peptide interactions, while the adsorbed structure is stabilised via interaction of four strongly-binding residues, identified from our metadynamics simulations, with the aqueous graphene interface. Our findings rationalise the performance of the P1 sequence as a known graphene binder.

Sequence-dependent structure/function relationships of catalytic peptide-enabled gold nanoparticles generated under ambient synthetic conditions

Peptide-enabled nanoparticle (NP) synthesis routes can create and/or assemble functional nanomaterials under environmentally friendly conditions, with properties dictated by complex interactions at the biotic/abiotic interface. Manipulation of this interface through sequence modification can provide the capability for material properties to be tailored to create enhanced materials for energy, catalysis, and sensing applications. Fully realizing the potential of these materials requires a comprehensive understanding of sequence-dependent structure/function relationships that is presently lacking. In this work, the atomic-scale structures of a series of peptide-capped Au NPs are determined using a combination of atomic pair distribution function analysis of high-energy X-ray diffraction data and advanced molecular dynamics (MD) simulations. The Au NPs produced with different peptide sequences exhibit varying degrees of catalytic activity for the exemplar reaction 4-nitrophenol reduction. The experimentally derived atomic-scale NP configurations reveal sequence-dependent differences in structural order at the NP surface. Replica exchange with solute-tempering MD simulations are then used to predict the morphology of the peptide overlayer on these Au NPs and identify factors determining the structure/catalytic properties relationship. We show that the amount of exposed Au surface, the underlying surface structural disorder, and the interaction strength of the peptide with the Au surface all influence catalytic performance. A simplified computational prediction of catalytic performance is developed that can potentially serve as a screening tool for future studies. Our approach provides a platform for broadening the analysis of catalytic peptide-enabled metallic NP systems, potentially allowing for the development of rational design rules for property enhancement.