The generic unfolding of a biomimetic polymer during force spectroscopy.

With the help of force spectroscopy, several analytical theories aim at estimating the rate coefficient of folding for various proteins. Nevertheless, a chief bottleneck lies in the fact that there is still no perfect consensus on how does a force generally perturb the crystal-coil transition. Consequently, the goal of our work is in clarifying the generic behavior of most proteins in force spectroscopy; in other words, what general signature does an arbitrary protein exhibit for its rate coefficient as a function of the applied force? By employing a biomimetic polymer in molecular simulations, we focus on evaluating its respective activation energy for unfolding, while pulling on various pairs of its monomers. Above all, we find that in the vicinity of the force-free scenario, this activation energy possesses a negative slope and a negative curvature as a function of the applied force. Our work is in line with the most recent theories for unfolding, which suggest that such a signature is expected for most proteins, and thus, we further reiterate that many of the classical formulae, that estimate the rate coefficient of the crystal-coil transition, are inadequate. Besides, we also present here an analytical expression which experimentalists can use for approximating the activation energy for unfolding; importantly, it is based on measurements for the mean and variance of the distance between the beads which are being pulled. In summary, our work presents an interesting view for protein folding in force spectroscopy.

Relative resolution: A hybrid formalism for fluid mixtures.

We show here that molecular resolution is inherently hybrid in terms of relative separation. While nearest neighbors are characterized by a fine-grained (geometrically detailed) model, other neighbors are characterized by a coarse-grained (isotropically simplified) model. We notably present an analytical expression for relating the two models via energy conservation. This hybrid framework is correspondingly capable of retrieving the structural and thermal behavior of various multi-component and multi-phase fluids across state space.

Relative Resolution: An Analysis with the Kullback-Leibler Entropy.

A novel type of a multiscale approach, called Relative Resolution (RelRes), can correctly retrieve the behavior of various nonpolar liquids while speeding up molecular simulations by almost an order of magnitude. In this approach in a single system, molecules switch their resolution in terms of their relative separation, with near neighbors interacting via fine-grained potentials, yet far neighbors interacting via coarse-grained potentials; notably, these two potentials are analytically parametrized by a multipole approximation. Our current work focuses on analyzing RelRes by relating it with the Kullback-Leibler (KL) entropy, which is a useful metric for multiscale errors. In particular, we thoroughly examine the exact and approximate versions of this informatic measure for several alkane systems. By analyzing its dependency on the system size, we devise a formula for predicting the exact KL entropy of an "infinite" system via the computation of the approximate KL entropy of an "infinitesimal" system. Demonstrating that the KL entropy can holistically capture many multiscale errors, we settle bounds for the KL entropy that ensure a sufficient representation of the structural and thermal behavior by the RelRes algorithm. This, in turn, allows the scientific community to readily determine the ideal switching distance for an arbitrary RelRes system.

Coarse-graining errors and numerical optimization using a relative entropy framework.

The ability to generate accurate coarse-grained models from reference fully atomic (or otherwise "first-principles") ones has become an important component in modeling the behavior of complex molecular systems with large length and time scales. We recently proposed a novel coarse-graining approach based upon variational minimization of a configuration-space functional called the relative entropy, S(rel), that measures the information lost upon coarse-graining. Here, we develop a broad theoretical framework for this methodology and numerical strategies for its use in practical coarse-graining settings. In particular, we show that the relative entropy offers tight control over the errors due to coarse-graining in arbitrary microscopic properties, and suggests a systematic approach to reducing them. We also describe fundamental connections between this optimization methodology and other coarse-graining strategies like inverse Monte Carlo, force matching, energy matching, and variational mean-field theory. We suggest several new numerical approaches to its minimization that provide new coarse-graining strategies. Finally, we demonstrate the application of these theoretical considerations and algorithms to a simple, instructive system and characterize convergence and errors within the relative entropy framework.

Relative Resolution: A Computationally Efficient Implementation in LAMMPS.

Recently, a novel type of multiscale simulation, called Relative Resolution (RelRes), was introduced. In a single system, molecules switch their resolution in terms of their relative separation, with near neighbors interacting via fine-grained potentials yet far neighbors interacting via coarse-grained potentials; notably, these two potentials are analytically parametrized by a multipole approximation. This multiscale approach is consequently able to correctly retrieve across state space the structural and thermal, as well as static and dynamic, behavior of various nonpolar mixtures. Our current work focuses on the practical implementation of RelRes in LAMMPS, specifically for the commonly used Lennard-Jones potential. By examining various correlations and properties of several alkane liquids, including complex solutions of alternate cooligomers and block copolymers, we confirm the validity of this automated LAMMPS algorithm. Most importantly, we demonstrate that this RelRes implementation gains almost an order of magnitude in computational efficiency, as compared with conventional simulations. We thus recommend this novel LAMMPS algorithm for anyone studying systems governed by Lennard-Jones interactions.

Tetrahedrality and structural order for hydrophobic interactions in a coarse-grained water model.

The hydrophobic interaction manifests two separate regimes in terms of size: Small nonpolar bodies exhibit a weak oscillatory force (versus distance) while large nonpolar surfaces exhibit a strong monotonic one. This crossover in hydrophobic behavior is typically explained in terms of water's tetrahedral structure: Its tetrahedrality is enhanced near small solutes and diminished near large planar ones. Here, we demonstrate that water's tetrahedral correlations signal this switch even in a highly simplified, isotropic, "core-softened" water model. For this task, we introduce measures of tetrahedrality based on the angular distribution of water's nearest neighbors. On a quantitative basis, the coarse-grained model of course is only approximate: (1) While greater than simple Lennard-Jones liquids, its bulk tetrahedrality remains lower than that of fully atomic models; and (2) the decay length of the large-scale hydrophobic interaction is less than has been found in experiments. Even so, the qualitative behavior of the model is surprisingly rich and exhibits numerous waterlike hydrophobic behaviors, despite its simplicity. We offer several arguments for the manner in which it should be able to (at least partially) reproduce tetrahedral correlations underlying these effects.

Length-scale crossover of the hydrophobic interaction in a coarse-grained water model.

It has been difficult to establish a clear connection between the hydrophobic interaction among small molecules typically studied in molecular simulations (a weak, oscillatory force) and that found between large, macroscopic surfaces in experiments (a strong, monotonic force). Here, we show that both types of interaction can emerge with a simple, core-softened water model that captures water's unique pairwise structure. As in hydrophobic hydration, we find that the hydrophobic interaction manifests a length-scale dependence, exhibiting distinct driving forces in the molecular and macroscopic regimes. Moreover, the ability of this simple model to capture both regimes suggests that several features of the hydrophobic force can be understood merely through water's pair correlations.

Relative entropy as a universal metric for multiscale errors.

We show that the relative entropy, Srel, suggests a fundamental indicator of the success of multiscale studies, in which coarse-grained (CG) models are linked to first-principles (FP) ones. We demonstrate that Srel inherently measures fluctuations in the differences between CG and FP potential energy landscapes, and develop a theory that tightly and generally links it to errors associated with coarse graining. We consider two simple case studies substantiating these results, and suggest that Srel has important ramifications for evaluating and designing coarse-grained models.

The search for the hydrophobic force law.

After nearly 30 years of research on the hydrophobic interaction, the search for the hydrophobic force law is still continuing. Indeed, there are more questions than answers, and the experimental data are often quite different for nominally similar conditions, as well as, apparently, for nano-, micro-, and macroscopic surfaces. This has led to the conclusion that the experimentally observed force-distance relationships are either a combination of different 'fundamental' interactions, or that the hydrophobic force-law, if there is one, is complex--depending on numerous parameters. The only unexpectedly strong attractive force measured in all experiments so far has a range of D approximately 100-200 angstroms, increasing roughly exponentially down to approximately 10-20 angstroms and then more steeply down to adhesive contact at D = 0 or, for power-law potentials, effectively at D approximately 2 angstroms. The measured forces in this regime (100-200 angstroms) and especially the adhesive forces are much stronger, and have a different distance-dependence from the continuum VDW force (Lifshitz theory) for non-conducting dielectric media. We suggest a three-regime force-law for the forces observed between hydrophobic surfaces: In the first, from 100-200 angstroms to thousands of angstroms, the dominating force is created by complementary electrostatic domains or patches on the apposing surfaces and/or bridging vapour cavities; a 'pure' but still not well-understood 'long-range hydrophobic force' dominates the second regime from approximately 150 to approximately 15 angstroms, possibly due to an enhanced Hamaker constant associated with the 'proton-hopping' polarizability of water; while below approximately 10-15 anstroms to contact there is another 'pure short-range hydrophobic force' related to water structuring effects associated with surface-induced changes in the orientation and/or density of water molecules and H-bonds at the water-hydrophobic interface. We present recent SFA and other experimental results, as well as a simplified model for water based on a spherically-symmetric potential that is able to capture some basic features of hydrophobic association. Such a model may be useful for theoretical studies of the HI over the broad range of scales observed in SFA experiments.

Anomalous waterlike behavior in spherically-symmetric water models optimized with the relative entropy.

Recent efforts have attempted to understand many of liquid water's anomalous properties in terms of effective spherically-symmetric pairwise molecular interactions entailing two characteristic length scales (so-called "core-softened" potentials). In this work, we examine the extent to which such simple descriptions of water are representative of the true underlying interactions by extracting coarse-grained potential functions that are optimized to reproduce the behavior of an all-atom model. To perform this optimization, we use a novel procedure based upon minimizing the relative entropy, a quantity that measures the extent to which a coarse-grained configurational ensemble overlaps with a reference all-atom one. We show that the optimized spherically-symmetric water models exhibit notable variations with the state conditions at which they were optimized, reflecting in particular the shifting accessibility of networked hydrogen bonding interactions. Moreover, we find that water's density and diffusivity anomalies are only reproduced when the effective coarse-grained potentials are allowed to vary with state. Our results therefore suggest that no state-independent spherically-symmetric potential can fully capture the interactions responsible for water's unique behavior; rather, the particular way in which the effective interactions vary with temperature and density contributes significantly to anomalous properties.