Progress in the atomic-scale modelling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomic forces that work by either solving the electronic structure problem explicitly, or by computing accurate approximations of the solution and by the development of techniques that use the Born-Oppenheimer (BO) forces to move the atoms on the BO potential energy surface. As a consequence of these developments it is now possible to identify stable or metastable states, to sample configurations consistent with the appropriate thermodynamic ensemble, and to estimate the kinetics of reactions and phase transitions. All too often, however, progress is slowed down by the bottleneck associated with implementing new optimization algorithms and/or sampling techniques into the many existing electronic-structure and empirical-potential codes. To address this problem, we are thus releasing a new version of the i-PI software. This piece of software is an easily extensible framework for implementing advanced atomistic simulation techniques using interatomic potentials and forces calculated by an external driver code. While the original version of the code[1] was developed with a focus on path integral molecular dynamics techniques, this second release of i-PI not only includes several new advanced path integral methods, but also offers other classes of algorithms. In other words, i-PI is moving towards becoming a universal force engine that is both modular and tightly coupled to the driver codes that evaluate the potential energy surface and its derivatives.

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Most of the current understanding of structure-property relations at the molecular and the supramolecular scales can be formulated in terms of the stability of and the interactions between a limited number of recurring structural motifs (e.g., H-bonds, coordination polyhedra, and protein secondary structure). Here we demonstrate an algorithm to automatically recognize such patterns, based on the identification of local maxima in the probability distributions observed in atomistic computer simulations, which is robust to the dimensionality and the sparsity of the reference atomistic data. We first discuss its main features, demonstrating some on artificial data sets, and then show how it can be applied to identify coordination environments in Lennard-Jones clusters and to recognize secondary-structure patterns in the simulation of an oligopeptide. To assess the applicability of this algorithm for motifs that involve several interdependent degrees of freedom, we also employ it to identify groups of conformers of the cluster and the polypeptide, considered in their entirety. The motifs identified by analyzing atomistic simulations can be used to interpret and rationalize the stability and behavior of the system at hand, and also as a tool to accelerate sampling, in association with biased molecular dynamics schemes.

We present a set of Coulomb point charges and van der Waals parameters for molecular dynamics simulations of interfaces between natively deprotonated amorphous SiO2 surfaces and liquid water, to be used in combination with standard biomolecular force fields. We pay particular attention to the extent of negative charge delocalisation in the solid that follows the deprotonation of terminal silanol groups, as revealed by extensive Bader analysis of electronic densities computed by density functional theory (DFT). The absolute charge values in our force field are determined from best‐fitting to the electrostatic potential computed ab initio (ESP charges). Our proposed parameter set is found to reproduce the energy landscape of single water molecules over neutral and deprotonated amorphous SiO2 surfaces and, after a minor adjustment, over thin oxide films on Si. Our analysis reveals a certain degree of arbitrariness in the choice of the DFT scheme used as the reference for the force‐field optimisation procedure, highlighting its intrinsic limits. Interaction between a water molecule and an oxidised Si surface calculated with several DFT and force‐field schemes, and delocalisation of the negative charge upon deprotonation of an amorphous SiO2 surface.

Circular dichroism (CD) spectroscopy is one of the few experimental techniques sensitive to the structural changes that peptides undergo when they adsorb on inorganic material surfaces, a problem of deep significance in medicine, biotechnology, and materials science. Although the theoretical calculation of the CD spectrum of a molecule in a given conformation can be routinely performed, the inverse problem of extracting atomistic structural details from a measured spectrum is not uniquely determined. Especially complicated is the case of oligopeptides, whose folding/unfolding energy landscapes are often very broad and shallow. This means that the CD spectra measured for either dissolved or adsorbed peptides arise from a multitude of different structures, each present with a probability dictated by their relative free-energy variations, according to Boltzmann statistics. Here we present a modeling method based on replica exchange with solute tempering in combination with metadynamics, which allows us to predict both the helicity loss of a small peptide upon interaction with silica colloids in water and to compute the full CD spectra of the adsorbed and dissolved states, in quantitative agreement with experimental measurements. In our method, the CD ellipticity Θ for any given wavelength λ is calculated as an external collective variable by means of reweighting the biased trajectory obtained using the peptide-SiO2 surface distance and the structural helicity as two independent, internal collective variables. Our results also provide support for the often-employed hypothesis that the Θ intensity at λ = 222 nm is linearly correlated with the peptides' fractional helicity.