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Enhanced sampling algorithms are indispensable when working with highly disconnected multimodal distributions. An important application of these is the conformational exploration of particular internal degrees of freedom of molecular systems. However, despite the existence of many commonly used enhanced sampling algorithms to explore these internal motions, they often rely on system-dependent parameters, which negatively impact efficiency and reproducibility. Here, we present fully adaptive simulated tempering (FAST), a variation of the irreversible simulated tempering algorithm, which continuously optimizes the number, parameters, and weights of intermediate distributions to achieve maximally fast traversal over a space defined by the change in a predefined thermodynamic control variable such as temperature or an alchemical smoothing parameter. This work builds on a number of previously published methods, such as sequential Monte Carlo, and introduces a novel parameter optimization procedure that can, in principle, be used in any expanded ensemble algorithms. This method is validated by being applied on a number of different molecular systems with high torsional kinetic barriers. We also consider two different soft-core potentials during the interpolation procedure and compare their performance. We conclude that FAST is a highly efficient algorithm, which improves simulation reproducibility and can be successfully used in a variety of settings with the same initial hyperparameters. [ABSTRACT FROM AUTHOR]

We design a geometric Brownian information engine by considering overdamped Brownian particles inside a two-dimensional monolobal confinement with irregular width along the transport direction. Under such detention, particles experience an effective entropic potential which has a logarithmic form. We employ a feedback control protocol as an outcome of error-free position measurement. The protocol comprises three stages: measurement, feedback, and relaxation. We reposition the center of the confinement to the measurement distance (xp) instantaneously when the position of the trapped particle crosses xp for the first time. Then, the particle is allowed for thermal relaxation. We calculate the extractable work, total information, and unavailable information associated with the feedback control using this equilibrium probability distribution function. We find the exact analytical value of the upper bound of extractable work as ( 5 3 − 2 l n 2) k B T. We introduce a constant force G downward to the transverse coordinate (y). A change in G alters the effective potential of the system and tunes the relative dominance of entropic and energetic contributions in it. The upper bound of the achievable work shows a crossover from ( 5 3 − 2 l n 2) k B T to 1 2 k B T when the system changes from an entropy-dominated regime to an energy-dominated one. Compared to an energetic analog, the loss of information during the relaxation process is higher in the entropy-dominated region, which accredits the less value in achievable work. Theoretical predictions are in good agreement with the Langevin dynamics simulation studies. [ABSTRACT FROM AUTHOR]

This article presents the application of the reactive step molecular dynamics simulation method [M. Biedermann, D. Diddens, and A. Heuer, J. Chem. Theory Comput. 17, 1074 (2021)] toward two different atomistic, chemically reactive systems. During reactive steps, transitions from reactant to product molecules are modeled according to physically correct transition probabilities based on quantum chemical information about the reactions such as molecular reaction rates via instant exchange of the employed force field and a subsequent, short relaxation of the structure. In the first application, we study the follow-up reactions of singly reduced ethylene carbonate (EC) radicals in EC solution, first, via extensive ab initio molecular dynamics simulations and, second, with the reactive step algorithm. A direct comparison of both simulation methods shows excellent agreement. Then, we employ the reactive step algorithm to simulate the enolate formation of 2-methylcyclopropanone with the base lithium diisopropylamine. Thereby, we can demonstrate that the reactive step algorithm is also capable of capturing effects from kinetic vs thermodynamic control of chemical reactions during simulation. [ABSTRACT FROM AUTHOR]

Water is at the heart of almost all biological phenomena, without which no life that we know of would have been possible. It is a misleadingly complex liquid that exists in near coexistence with the vapor phase under ambient conditions. Confinement within a hydrophobic cavity can tip this balance enough to drive a cooperative dewetting transition. For a nanometer-scale pore, the dewetting transition leads to a stable dry state that is physically open but impermeable to ions. This phenomenon is often referred to as hydrophobic gating. Numerous transmembrane protein ion channels have now been observed to utilize hydrophobic gating in their activation and regulation. Here, we review recent theoretical, simulation, and experimental studies that together have started to establish the principles of hydrophobic gating and discuss how channels of various sizes, topologies, and biological functions can utilize these principles to control the thermodynamic properties of water within their interior pores for gating and regulation. Exciting opportunities remain in multiple areas, particularly on direct experimental detection of hydrophobic dewetting in biological channels and on understanding how the cell may control the hydrophobic gating in regulation of ion channels. [ABSTRACT FROM AUTHOR]

Isotropic pairwise interactions that promote the self-assembly of complex particle morphologies have been discovered by inverse design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. The benefits of this approach are twofold. First, the structure and the thermodynamics associated with the optimized interaction can be controlled simultaneously. Second, by varying the pressure in the optimization, a family of interparticle potentials that all self-assemble the same structure can be systematically discovered, allowing for a deeper understanding of self-assembly of a given target structure and providing multiple assembly routes for its realization. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential. [ABSTRACT FROM AUTHOR]

Macromolecular crowding can influence polymer shapes, which is important for understanding the thermodynamic stability of polymer solutions and the structure and function of biopolymers (proteins, RNA, DNA) under confinement. We explore the influence of nanoparticle crowding on polymer shapes via Monte Carlo simulations and free-volume theory of a coarse-grained model of polymer-nanoparticle mixtures. Exploiting the geometry of random walks, we model polymer coils as effective penetrable ellipsoids, whose shapes fluctuate according to the probability distributions of the eigenvalues of the gyration tensor. Accounting for the entropic cost of a nanoparticle penetrating a larger polymer coil, we compute the crowding-induced shift in the shape distributions, radius of gyration, and asphericity of ideal polymers in a theta solvent. With increased nanoparticle crowding, we find that polymers become more compact (smaller, more spherical), in agreement with predictions of free-volume theory. Our approach can be easily extended to nonideal polymers in good solvents and used to model conformations of biopolymers in crowded environments. [ABSTRACT FROM AUTHOR]

Decahydroisoquinoline (DHIQ) appears to be a unique material--the only non-associated, simple liquid with dynamics deviating from density scaling. To examine whether this anomaly is real, the density, ρ, of DHIQ was measured at temperatures,T, as low as 214 K and pressures up to ∼1.2 GPa. This enabled the equation of state(EoS) to be determined, without extrapolation, over the range of thermodynamic conditions for which the relaxation times had been reported. Using this less ambiguous EoS, we find that within the precision of the available relaxation times, the latter are a function of T/ρ3.9, contrary to previous reports. Thus, the behavior of DHIQ is unexceptional; similar to every non-associated liquid tested to date, its dynamics comply with density scaling. [ABSTRACT FROM AUTHOR]