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In the Hamiltonian adaptive resolution simulation method (H–AdResS) it is possible to simulate coexisting atomistic (AT) and ideal gas representations of a physical system that belong to different subdomains within the simulation box. The Hamiltonian includes a field that bridges both models by smoothly switching on (off) the intermolecular potential as particles enter (leave) the AT region. In practice, external one-body forces are calculated and applied to enforce a reference density throughout the simulation box, and the resulting external potential adds up to the Hamiltonian. This procedure suggests an apparent dependence of the final Hamiltonian on the system’s thermodynamic state that challenges the method’s statistical mechanics consistency. In this paper, we explicitly include an external potential that depends on the switching function. Hence, we build a grand canonical potential for this inhomogeneous system to find the equivalence between H–AdResS and density functional theory (DFT). We thus verify that the external potential inducing a constant density profile is equal to the system’s excess chemical potential. Given DFT’s one-to-one correspondence between external potential and equilibrium density, we find that a Hamiltonian description of the system is compatible with the numerical implementation based on enforcing the reference density across the simulation box. In the second part of the manuscript, we focus on assessing our approach’s convergence and computing efficiency concerning various model parameters, including sample size and solute concentrations. To this aim, we compute the excess chemical potential of water, aqueous urea solutions and Lennard–Jones (LJ) mixtures. The results’ convergence and accuracy are convincing in all cases, thus emphasising the method’s robustness and capabilities.

The use of biomolecules as capping and reducing agents in the synthesis of metallic nanoparticles constitutes a promising framework to achieve desired functional properties with minimal toxicity. The system’s complexity and the large number of variables involved represent a challenge for theoretical and experimental investigations aiming at devising precise synthesis protocols. In this work, we use L-asparagine (Asn), an amino acid building block of large biomolecular systems, to synthesise gold nanoparticles (AuNPs) in aqueous solution at controlled pH. The use of Asn offers a primary system that allows us to understand the role of biomolecules in synthesising metallic nanoparticles. Our results indicate that AuNPs synthesised in acidic (pH 6) and basic (pH 9) environments exhibit somewhat different morphologies. We investigate these AuNPs via Raman scattering experiments and classical molecular dynamics simulations of zwitterionic and anionic Asn states adsorbing on (111)-, (100)-, (110)-, and (311)-oriented gold surfaces. A combined analysis suggests that the underlying mechanism controlling AuNPs geometry correlates with amine’s preferential adsorption over ammonium groups, enhanced upon increasing pH. Our simulations reveal that Asn (both zwitterionic and anionic) adsorption on gold (111) is essentially different from adsorption on more open surfaces. Water molecules strongly interact with the gold face-centred-cubic lattice and create traps, on the more open surfaces, that prevent the Asn from diffusing. These results indicate that pH is a relevant parameter in green-synthesis protocols with the capability to control the nanoparticle’s geometry, and pave the way to computational studies exploring the effect of water monolayers on the adsorption of small molecules on wet gold surfaces.

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We propose a mechanism for α-helix folding of polyalanine in aqueous urea that reconciles experimental and simulation studies. Over 15 μs long, all-atom simulations reveal that, upon dehydrating the protein's first solvation shell, a delicate balance between localized urea−residue dipole interactions and hydrogen bonds dictates polypeptide solvation properties and structure. Our work clarifies the experimentally observed tendency of these alanine-rich systems to form secondary structures at low and intermediate urea concentrations. Moreover, it is consistent with the commonly accepted hydrogen-bond-induced helix unfolding, dominant at high urea concentrations. These results establish a structure−property relationship highlighting the importance of microscopic dipole−dipole orientations/interactions for the operational understanding of macroscopic protein solvation.