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Molecular dynamics (MD) is the method of choice for understanding the structure, function, and interactions of molecules. However, MD simulations are limited by the strong metastability of many molecules, which traps them in a single conformation basin for an extended amount of time. Enhanced sampling techniques, such as metadynamics and replica exchange, have been developed to overcome this limitation and accelerate the exploration of complex free energy landscapes. In this paper, we propose Vendi Sampling, a replica-based algorithm for increasing the efficiency and efficacy of the exploration of molecular conformation spaces. In Vendi sampling, replicas are simulated in parallel and coupled via a global statistical measure, the Vendi Score, to enhance diversity. Vendi sampling allows for the recovery of unbiased sampling statistics and dramatically improves sampling efficiency. We demonstrate the effectiveness of Vendi sampling in improving molecular dynamics simulations by showing significant improvements in coverage and mixing between metastable states and convergence of free energy estimates for four common benchmarks, including Alanine Dipeptide and Chignolin. [ABSTRACT FROM AUTHOR]

In this paper, we report results of using enhanced sampling and blind selection techniques for high-accuracy protein structural refinement. By combining a parallel continuous simulated tempering (PCST) method, previously developed by Zang et al. [J. Chem. Phys. 141, 044113 (2014)], and the structure based model (SBM) as restraints, we refined 23 targets (18 from the refinement category of the CASP10 and 5 from that of CASP12). We also designed a novel model selection method to blindly select high-quality models from very long simulation trajectories. The combined use of PCST-SBM with the blind selection method yielded final models that are better than initial models. For Top-1 group, 7 out of 23 targets had better models (greater global distance test total scores) than the critical assessment of structure prediction participants. For Top-5 group, 10 out of 23 were better. Our results justify the crucial position of enhanced sampling in protein structure prediction and refinement and demonstrate that a considerable improvement of low-accuracy structures is achievable with current force fields. [ABSTRACT FROM AUTHOR]

In the present paper we identify a rigorous property of a number of tempering-based Monte Carlo sampling methods, including parallel tempering as well as partial and infinite swapping. Based on this property we develop a variety of performance measures for such rare-event sampling methods that are broadly applicable, informative, and straightforward to implement. We illustrate the use of these performance measures with a series of applications involving the equilibrium properties of simple Lennard-Jones clusters, applications for which the performance levels of partial and infinite swapping approaches are found to be higher than those of conventional parallel tempering. [ABSTRACT FROM AUTHOR]

Using computer simulations to model the folding of proteins into their native states is computationally expensive due to the extraordinarily low degeneracy of the ground state. In this paper, we develop an efficient way to sample these folded conformations using Wang Landau sampling coupled with the configurational bias method (which uses an unphysical 'temperature' that lies between the collapse and folding transition temperatures of the protein). This method speeds up the folding process by roughly an order of magnitude over existing algorithms for the sequences studied. We apply this method to study the adsorption of intrinsically disordered hydrophobic polar protein fragments on a hydrophobic surface. We find that these fragments, which are unstructured in the bulk, acquire secondary structure upon adsorption onto a strong hydrophobic surface. Apparently, the presence of a hydrophobic surface allows these random coil fragments to fold by providing hydrophobic contacts that were lost in protein fragmentation. [ABSTRACT FROM AUTHOR]

An efficient time-dependent importance sampling method is developed for the Monte Carlo calculation of time correlation functions via the initial value representation (IVR) of semiclassical (SC) theory. A prefactor-free time-dependent sampling function weights the importance of a trajectory based on the magnitude of its contribution to the time correlation function, and global trial moves are used to facilitate the efficient sampling the phase space of initial conditions. The method can be generally applied to sampling rare events efficiently while avoiding being trapped in a local region of the phase space. Results presented in the paper for two system-bath models demonstrate the efficiency of this new importance sampling method for full SC-IVR calculations. [ABSTRACT FROM AUTHOR]

Over the last number of years several simulation methods have been introduced to study rare events such as nucleation. In this paper we examine the crystal nucleation rate of hard spheres using three such numerical techniques: molecular dynamics, forward flux sampling, and a Bennett-Chandler-type theory where the nucleation barrier is determined using umbrella sampling simulations. The resulting nucleation rates are compared with the experimental rates of Harland and van Megen [Phys. Rev. E 55, 3054 (1997)], Sinn et al. [Prog. Colloid Polym. Sci. 118, 266 (2001)], Schätzel and Ackerson [Phys. Rev. E 48, 3766 (1993)], and the predicted rates for monodisperse and 5% polydisperse hard spheres of Auer and Frenkel [Nature 409, 1020 (2001)]. When the rates are examined in units of the long-time diffusion coefficient, we find agreement between all the theoretically predicted nucleation rates, however, the experimental results display a markedly different behavior for low supersaturation. Additionally, we examined the precritical nuclei arising in the molecular dynamics, forward flux sampling, and umbrella sampling simulations. The structure of the nuclei appears independent of the simulation method, and in all cases, the nuclei contains on average significantly more face-centered-cubic ordered particles than hexagonal-close-packed ordered particles. [ABSTRACT FROM AUTHOR]

The mechanical model based on beads and springs, which we recently proposed to study nonspecific DNA-protein interactions [J. Chem. Phys. 130, 015103 (2009)], was improved by describing proteins as sets of interconnected beads instead of single beads. In this paper, we first compare the results obtained with the updated model with those of the original one and then use it to investigate several aspects of the dynamics of DNA sampling, which could not be accounted for by the original model. These aspects include the effect on the speed of DNA sampling of the regularity and/or randomness of the protein charge distribution, the charge and location of the search site, and the shape and deformability of the protein. We also discuss the efficiency of facilitated diffusion, that is, the extent to which the combination of 1D sliding along the DNA and 3D diffusion in the cell can lead to faster sampling than pure 3D diffusion of the protein. [ABSTRACT FROM AUTHOR]

The thermodynamics and kinetics of a many-body system can be described in terms of a potential energy landscape in multidimensional configuration space. The partition function of such a landscape can be written in terms of a density of states, which can be computed using a variety of Monte Carlo techniques. In this paper, a new self-consistent Monte Carlo method for computing density of states is described that uses importance sampling and a multiplicative update factor to achieve rapid convergence. The technique is then applied to compute the equilibrium quench probability of the various inherent structures (minima) in the landscape. The quench probability depends on both the potential energy of the inherent structure and the volume of its corresponding basin in configuration space. Finally, the methodology is extended to the isothermal-isobaric ensemble in order to compute inherent structure quench probabilities in an enthalpy landscape. [ABSTRACT FROM AUTHOR]

This paper describes a new Monte Carlo method based on a novel stochastic potential switching algorithm. This algorithm enables the equilibrium properties of a system with potential V to be computed using a Monte Carlo simulation for a system with a possibly less complex stochastically altered potential V. By proper choices of the stochastic switching and transition probabilities, it is shown that detailed balance can be strictly maintained with respect to the original potential V. The validity of the method is illustrated with a simple one-dimensional example. The method is then generalized to multidimensional systems with any additive potential, providing a framework for the design of more efficient algorithms to simulate complex systems. A near-critical Lennard-Jones fluid with more than 20 000 particles is used to illustrate the method. The new algorithm produced a much smaller dynamic scaling exponent compared to the Metropolis method and improved sampling efficiency by over an order of magnitude. [ABSTRACT FROM AUTHOR]

Random structure searching has been proved to be a powerful approach to search and find the global minimum and the metastable structures. A true random sampling is in principle needed yet it would be highly time-consuming and/or practically impossible to find the global minimum for the complicated systems in their high-dimensional configuration space. Thus the implementations of reasonable constraints, such as adopting system symmetries to reduce the independent dimension in structural space and/or imposing chemical information to reach and relax into low-energy regions, are the most essential issues in the approach. In this paper, we propose the concept of “object” which is either an atom or composed of a set of atoms (such as molecules or carbonates) carrying a symmetry defined by one of the Wyckoff positions of space group and through this process it allows the searching of global minimum for a complicated system to be confined in a greatly reduced structural space and becomes accessible in practice. We examined several representative materials, including Cd3As2 crystal, solid methanol, high-pressure carbonates (FeCO3), and Si(111)-7 × 7 reconstructed surface, to demonstrate the power and the advantages of using “object” concept in random structure searching. [ABSTRACT FROM AUTHOR]

Many processes important to chemistry, materials science, and biology cannot be described without considering electronic and nuclear-level dynamics and their coupling to slower, cooperative motions of the system. These inherently multiscale problems require computationally efficient and accurate methods to converge statistical properties. In this paper, a method is presented that uses data directly from condensed phase ab initio simulations to develop reactive molecular dynamics models that do not require predefined empirical functions. Instead, the interactions used in the reactive model are expressed as linear combinations of interpolating functions that are optimized by using a linear least-squares algorithm. One notable benefit of the procedure outlined here is the capability to minimize the number of parameters requiring nonlinear optimization. The method presented can be generally applied to multiscale problems and is demonstrated by generating reactive models for the hydrated excess proton and hydroxide ion based directly on condensed phase ab initio molecular dynamics simulations. The resulting models faithfully reproduce the water-ion structural properties and diffusion constants from the ab initio simulations. Additionally, the free energy profiles for proton transfer, which is sensitive to the structural diffusion of both ions in water, are reproduced. The high fidelity of these models to ab initio simulations will permit accurate modeling of general chemical reactions in condensed phase systems with computational efficiency orders of magnitudes greater than currently possible with ab initio simulation methods, thus facilitating a proper statistical sampling of the coupling to slow, large-scale motions of the system. [ABSTRACT FROM AUTHOR]