Bionanocombinatorics is an emerging field that aims to use combinations of positionally encoded biomolecules and nanostructures to create materials and devices with unique properties or functions. The full potential of this new paradigm could be accessed by exploiting specific noncovalent interactions between diverse palettes of biomolecules and inorganic nanostructures. Advancement of this paradigm requires peptide sequences with desired binding characteristics that can be rationally designed, based upon fundamental, molecular-level understanding of biomolecule-inorganic nanoparticle interactions. Here, we introduce an integrated method for building this understanding using experimental measurements and advanced molecular simulation of the binding of peptide sequences to gold surfaces. From this integrated approach, the importance of entropically driven binding is quantitatively demonstrated, and the first design rules for creating both enthalpically and entropically driven nanomaterial-binding peptide sequences are developed. The approach presented here for gold is now being expanded in our laboratories to a range of inorganic nanomaterials and represents a key step toward establishing a bionanocombinatorics assembly paradigm based on noncovalent peptide-materials recognition.
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.
The molecular simulation of biomolecules adsorbed at noble metal interfaces can assist in the development of bionanotechnology applications. In line with advances in polarizable force fields for adsorption at aqueous gold interfaces, there is scope for developing a similar force field for silver. One way to accomplish this is via the generation of in vacuo adsorption energies calculated using first-principles approaches for a wide range of different but biologically relevant small molecules, including water. Here, we present such first-principles data for a comprehensive range of bio-organic molecules obtained from plane-wave density functional theory calculations using the vdW-DF functional. As reported previously for the gold force field, GolP-CHARMM (Wright, L. B.; Rodger, P. M.; Corni, S.; Walsh, T. R. GolP-CHARMM: first-principles based force-fields for the interaction of proteins with Au(111) and Au(100). J. Chem. Theory Comput. 2013, 9, 1616-1630), we have used these data to construct a a new force field, AgP-CHARMM, suitable for the simulation of biomolecules at the aqueous Ag(111) and Ag(100) interfaces. This force field is derived to be consistent with GolP-CHARMM such that adsorption on Ag and Au can be compared on an equal footing. Our force fields are used to evaluate the water overlayer stability on both silver and gold, finding good agreement with known behaviors. We also calculate and compare the structuring (spatial and orientational) of liquid water adsorbed at both silver and gold. Finally, we report the adsorption free energy of a range of amino acids at both the Au(111) and Ag(111) aqueous interfaces, calculated using metadynamics. Stronger adsorption on gold was noted in most cases, with the exception being the carboxylate group present in aspartic acid. Our findings also indicate differences in the binding free energy profile between silver and gold for some amino acids, notably for His and Arg. Our analysis suggests that the relatively stronger structuring of the first water layer on silver, relative to gold, could give rise to these differences.
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.
To fully harness the enormous potential offered by interfaces between graphitic nanostructures and biomolecules, detailed connections between adsorbed conformations and adsorption behaviour are needed. To elucidate these links, a key approach, in partnership with experimental techniques, is molecular simulation. For this, a force-field (FF) that can appropriately capture the relevant physics and chemistry of these complex bio-interfaces, while allowing extensive conformational sampling, and also supporting inter-operability with known biological FFs, is a pivotal requirement. Here, we present and apply such a force-field, GRAPPA, designed to work with the CHARMM FF. GRAPPA is an efficiently implemented polarisable force-field, informed by extensive plane-wave DFT calculations using the revPBE-vdW-DF functional. GRAPPA adequately recovers the spatial and orientational structuring of the aqueous interface of graphene and carbon nanotubes, compared with more sophisticated approaches. We apply GRAPPA to determine the free energy of adsorption for a range of amino acids, identifying Trp, Tyr and Arg to have the strongest binding affinity and Asp to be a weak binder. The GRAPPA FF can be readily incorporated into mainstream simulation packages, and will enable large-scale polarisable biointerfacial simulations at graphitic interfaces, that will aid the development of biomolecule-mediated, solution-based graphene processing and self-assembly strategies.
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