A novel path sampling method for the calculation of rate constants

Computing stationary distributions in equilibrium and nonequilibrium systems with forward flux sampling

We present a method for computing stationary distributions for activated processes in equilibrium and nonequilibrium systems using forward flux sampling. In this method, the stationary distributions are obtained directly from the rate constant calculations for the forward and backward reactions; there is no need to perform separate calculations for the stationary distribution and the rate constant. We apply the method to the nonequilibrium rare event problem proposed by Maier and Stein, to nucleation in a 2-dimensional Ising system, and to the flipping of a genetic switch.

Potential energy and free energy landscapes

Familiar concepts for small molecules may require reinterpretation for larger systems. For example, rearrangements between geometrical isomers are usually considered in terms of transitions between the corresponding local minima on the underlying potential energy surface, V. However, transitions between bulk phases such as solid and liquid, or between the denatured and native states of a protein, are normally addressed in terms of free energy minima. To reestablish a connection with the potential energy surface we must think in terms of representative samples of local minima of V, from which a free energy surface is projected by averaging over most of the coordinates. The present contribution outlines how this connection can be developed into a tool for quantitative calculations. In particular, stepping between the local minima of V provides powerful methods for locating the global potential energy minimum, and for calculating global thermodynamic properties. When the transition states that link local minima are also sampled we can exploit statistical rate theory to obtain insight into global dynamics and rare events. Visualizing the potential energy landscape helps to explain how the network of local minima and transition states determines properties such as heat capacity features, which signify transitions between free energy minima. The organization of the landscape also reveals how certain systems can reliably locate particular structures on the experimental time scale from among an exponentially large number of local minima. Such directed searches not only enable proteins to overcome Levinthal's paradox but may also underlie the formation of "magic numbers" in molecular beams, the self-assembly of macromolecular structures, and crystallization.

Folding kinetics of a lattice protein via a forward flux sampling approach

We implement a forward flux sampling approach [R. J. Allen et al., J. Chem. Phys. 124, 194111 (2006)] for calculating transition rate constants and for sampling paths of protein folding events. The algorithm generates trajectories for the transition between the unfolded and folded states as chains of partially connected paths, which can be used to obtain the transition-state ensemble and the properties that characterize these intermediates. We apply this approach to Monte Carlo simulations of a model lattice protein in open space and in confined spaces of varying dimensions. We study the effect of confinement on both protein thermodynamic stability and folding kinetics; the former by mapping free-energy landscapes and the latter by the determination of rate constants and mechanistic details of the folding pathway. Our results show that, for the range of temperatures where the native state is stable, confinement of a protein destabilizes the unfolded state by reducing its entropy, resulting in increased thermodynamic stability of the folded state. Relative to the folding in open space, we find that the kinetics can be accelerated at temperatures above the temperature at which the unconfined protein folds fastest and that the rate constant increases with the number of constrained dimensions. By examining the statistical properties of the transition-state ensemble, we detect signs of a classical nucleation folding mechanism for a core of native contacts formed at an early stage of the process. This nucleus acts as folding foci and is composed of those residues that have higher probability to form native contacts in the transition-state intermediates, which can vary depending on the confinement conditions of the system.

Evidence for out-of-equilibrium crystal nucleation in suspensions of oppositely charged colloids

We report a numerical study of the rate of crystal nucleation in a binary suspension of oppositely charged colloids. Two different crystal structures compete in the thermodynamic conditions under study. We find that the crystal phase that nucleates is metastable and, more surprisingly, its nucleation free-energy barrier is not the lowest one. This implies that, during nucleation, there is insufficient time for subcritical nuclei to relax to their lowest free-energy structure. Such behavior is in direct contradiction with the common assumption that the phase that crystallizes most readily is the one with the lowest free-energy barrier for nucleation. The phenomenon that we describe should be relevant for crystallization experiments where competing solid structures are not connected by an easy transformation.

Bias annealing: a method for obtaining transition paths de novo

Computational studies of dynamics in complex systems require means for generating reactive trajectories with minimum knowledge about the processes of interest. Here, we introduce a method for generating transition paths when an existing one is not already available. Starting from biased paths obtained from steered molecular dynamics, we use a Monte Carlo procedure in the space of whole trajectories to shift gradually to sampling an ensemble of unbiased paths. Application to basin-to-basin hopping in a two-dimensional model system and nucleotide-flipping by a DNA repair protein demonstrates that the method can efficiently yield unbiased reactive trajectories even when the initial steered dynamics differ significantly. The relation of the method to others and the physical basis for its success are discussed.

Reaction rate calculation by parallel path swapping

The efficiency of path sampling simulations can be improved considerably using the approach of path swapping. For this purpose, we devise a new algorithmic procedure based on the transition interface sampling technique. In the same spirit of parallel tempering, paths between different ensembles are swapped, but the role of temperature is here played by the interface position. We test the method on the denaturation transition of DNA using the Peyrard-Bishop-Dauxois model. We find that the new algorithm gives a reduction of the computational cost by a factor of 20.

Sampling the kinetic pathways of a micelle fusion and fission transition

The mechanism and kinetics of micellar breakup and fusion in a dilute solution of a model surfactant are investigated by path sampling techniques. Analysis of the path ensemble gives insight in the mechanism of the transition. For larger, less stable micelles the fission/fusion occurs via a clear neck formation, while for smaller micelles the mechanism is more direct. In addition, path analysis yields an appropriate order parameter to evaluate the fusion and fission rate constants using stochastic transition interface sampling. For the small, stable micelle (50 surfactants) the computed fission rate constant is a factor of 10 lower than the fusion rate constant. The procedure opens the way for accurate calculation of free energy and kinetics for, e.g., membrane fusion, and wormlike micelle endcap formation.

Coarse master equation from Bayesian analysis of replica molecular dynamics simulations

We use Bayesian inference to derive the rate coefficients of a coarse master equation from molecular dynamics simulations. Results from multiple short simulation trajectories are used to estimate propagators. A likelihood function constructed as a product of the propagators provides a posterior distribution of the free coefficients in the rate matrix determining the Markovian master equation. Extensions to non-Markovian dynamics are discussed, using the trajectory "paths" as observations. The Markovian approach is illustrated for the filling and emptying transitions of short carbon nanotubes dissolved in water. We show that accurate thermodynamic and kinetic properties, such as free energy surfaces and kinetic rate coefficients, can be computed from coarse master equations obtained through Bayesian inference.

Extending molecular dynamics time scales with milestoning: example of complex kinetics in a solvated peptide

A recently introduced computational algorithm to extend time scales of atomically detailed simulations is illustrated. The algorithm, milestoning, is based on partitioning the dynamics to a sequence of trajectories between "milestones" and constructing a non-Markovian model for the motion along a reaction coordinate. The kinetics of a conformational transition in a blocked alanine is computed and shown to be accurate, more efficient than straightforward molecular dynamics by a factor of about 9, and nonexponential. A general scaling argument predicts a linear speedup with the number of milestones for diffusive processes and an exponential speedup for transitions over barriers. The algorithm is also trivial to parallelize. As a side result, milestoning also produces the free energy profile along the reaction coordinate and is able to describe nonequilibrium motions along one (or a few) degrees of freedom.

Molecular simulation of loading-dependent diffusion in nanoporous materials using extended dynamically corrected transition state theory

A dynamically corrected transition state theory method is presented that is capable of computing quantitatively the self-diffusivity of adsorbed molecules in confined systems at nonzero loading. This extension to traditional transition state theory is free of additional assumptions and yields a diffusivity identical to that obtained by conventional molecular-dynamics simulations. While molecular-dynamics calculations are limited to relatively fast diffusing molecules, our approach extends the range of accessible time scales significantly beyond currently available methods. We show results for methane, ethane, and propane in LTL- and LTA-type zeolites over a wide range of temperatures and loadings, and demonstrate the extensibility of the method to mixtures.

Transition-event durations in one-dimensional activated processes

Despite their importance in activated processes, transition-event durations--which are much shorter than first passage times--have not received a complete theoretical treatment. The authors therefore study the distribution rhob(t) of durations of transition events over a barrier in a one-dimensional system undergoing overdamped Langevin dynamics. The authors show that rhob(t) is determined by a Fokker-Planck equation with absorbing boundary conditions and obtain a number of results, including (i) the analytic form of the asymptotic short-time transient behavior, which is universal and independent of the potential function; (ii) the first nonuniversal correction to the short-time behavior leading to an estimate of a key physical time scale; (iii) following previous work, a recursive formulation for calculating, exactly, all moments of rhob based solely on the potential function-along with approximations for the distribution based on a small number of moments; and (iv) a high-barrier approximation to the long-time (t-->infinity) behavior of rhob(t). The authors also find that the mean event duration does not depend simply on the barrier-top frequency (curvature) but is sensitive to details of the potential. All of the analytic results are confirmed by transition-path-sampling simulations implemented in a novel way. Finally, the authors discuss which aspects of the duration distribution are expected to be general for more complex systems.

A coarse graining method for the identification of transition rates between molecular conformations

The coarse graining method to be advocated in this paper consists of two main steps. First, the propagation of an ensemble of molecular states is described as a Markov chain by a transition probability matrix in a finite state space. Second, we obtain metastable conformations by an aggregation of variables via Robust Perron Cluster Analysis (PCCA+). Up to now, it has been an open question as to how this coarse graining in space can be transformed to a coarse graining of the Markov chain while preserving the essential dynamic information. In this article, we construct a coarse matrix that is the correct propagator in the space of conformations. This coarse graining procedure carries over to rate matrices and allows to extract transition rates between molecular conformations. This approach is based on the fact that PCCA+ computes molecular conformations as linear combinations of the dominant eigenvectors of the transition matrix.

Prospects of transition interface sampling simulations for the theoretical study of zeolite synthesis

The transition interface sampling (TIS) technique allows large free energy barriers to be overcome within reasonable simulation time, which is impossible for straightforward molecular dynamics. Still, the method does not impose an artificial driving force, but it surmounts the timescale problem by an importance sampling of true dynamical pathways. Recently, it was shown that the efficiency of TIS when calculating reaction rates is less sensitive to the choice of reaction coordinate than those of the standard free energy based techniques. This could be an important advantage in complex systems for which a good reaction coordinate is usually very difficult to find. We explain the principles of this method and discuss some of the promising applications related to zeolite formation.

Efficiency analysis of reaction rate calculation methods using analytical models I: The two-dimensional sharp barrier

We analyze the efficiency of different methods for the calculation of reaction rates in the case of a simple two-dimensional analytical benchmark system. Two classes of methods are considered: the first is based on the free energy calculation along a reaction coordinate and the calculation of the transmission coefficient, the second on the sampling of dynamical pathways. We give scaling rules for how this efficiency depends on barrier height and width, and we hand out simple optimization rules for the method-specific parameters. We show that the path sampling methods, using the transition interface sampling technique, become exceedingly more efficient than the others when the reaction coordinate is not the optimal one.

Sampling the multiple folding mechanisms of Trp-cage in explicit solvent

We investigate the kinetic pathways of folding and unfolding of the designed miniprotein Trp- cage in explicit solvent. Straightforward molecular dynamics and replica exchange methods both have severe convergence problems, whereas transition path sampling allows us to sample unbiased dynamical pathways between folded and unfolded states and leads to deeper understanding of the mechanisms of (un)folding. In contrast to previous predictions employing an implicit solvent, we find that Trp-cage folds primarily (80% of the paths) via a pathway forming the tertiary contacts and the salt bridge, before helix formation. The remaining 20% of the paths occur in the opposite order, by first forming the helix. The transition states of the rate-limiting steps are solvated native-like structures. Water expulsion is found to be the last step upon folding for each route. Committor analysis suggests that the dynamics of the solvent is not part of the reaction coordinate. Nevertheless, during the transition, specific water molecules are strongly bound and can play a structural role in the folding.

Obtaining reaction coordinates by likelihood maximization

We present a new approach for calculating reaction coordinates in complex systems. The new method is based on transition path sampling and likelihood maximization. It requires fewer trajectories than a single iteration of existing procedures, and it applies to both low and high friction dynamics. The new method screens a set of candidate collective variables for a good reaction coordinate that depends on a few relevant variables. The Bayesian information criterion determines whether additional variables significantly improve the reaction coordinate. Additionally, we present an advantageous transition path sampling algorithm and an algorithm to generate the most likely transition path in the space of collective variables. The method is demonstrated on two systems: a bistable model potential energy surface and nucleation in the Ising model. For the Ising model of nucleation, we quantify for the first time the role of nuclei surface area in the nucleation reaction coordinate. Surprisingly, increased surface area increases the stability of nuclei in two dimensions but decreases nuclei stability in three dimensions.

Forward flux sampling-type schemes for simulating rare events: Efficiency analysis

We analyze the efficiency of several simulation methods which we have recently proposed for calculating rate constants for rare events in stochastic dynamical systems in or out of equilibrium. We derive analytical expressions for the computational cost of using these methods and for the statistical error in the final estimate of the rate constant for a given computational cost. These expressions can be used to determine which method to use for a given problem, to optimize the choice of parameters, and to evaluate the significance of the results obtained. We apply the expressions to the two-dimensional nonequilibrium rare event problem proposed by Maier and Stein [Phys. Rev. E 48, 931 (1993)]. For this problem, our analysis gives accurate quantitative predictions for the computational efficiency of the three methods.

Simulating rare events in equilibrium or nonequilibrium stochastic systems

We present three algorithms for calculating rate constants and sampling transition paths for rare events in simulations with stochastic dynamics. The methods do not require a priori knowledge of the phase-space density and are suitable for equilibrium or nonequilibrium systems in stationary state. All the methods use a series of interfaces in phase space, between the initial and final states, to generate transition paths as chains of connected partial paths, in a ratchetlike manner. No assumptions are made about the distribution of paths at the interfaces. The three methods differ in the way that the transition path ensemble is generated. We apply the algorithms to kinetic Monte Carlo simulations of a genetic switch and to Langevin dynamics simulations of intermittently driven polymer translocation through a pore. We find that the three methods are all of comparable efficiency, and that all the methods are much more efficient than brute-force simulation.

Interplay between structure and size in a critical crystal nucleus

We study the kinetics of crystal nucleation of an undercooled Lennard-Jones liquid using various path-sampling methods. We obtain the rate constant and elucidate the pathways for crystal nucleation. Analysis of the path ensemble reveals that crystal nucleation occurs along many different pathways, in which critical solid nuclei can be small, compact, and face centered cubic, but also large, less ordered, and more body centered cubic. The reaction coordinate thus includes, besides the cluster size, also the quality of the crystal structure.

Rate of homogeneous crystal nucleation in molten NaCl

We report a numerical simulation of the rate of crystal nucleation of sodium chloride from its melt at moderate supercooling. In this regime nucleation is too slow to be studied with "brute force" molecular-dynamics simulations. The melting temperature of ("Tosi Fumi") NaCl is approximately 1060 K. We studied crystal nucleation at T = 800 and 825 K. We observe that the critical nucleus formed during the nucleation process has the crystal structure of bulk NaCl. Interestingly, the critical nucleus is clearly faceted, the nuclei have a cubical shape. We have computed the crystal-nucleation rate using two completely different approaches, one based on an estimate of the rate of diffusive crossing of the nucleation barrier, the other based on the forward flux sampling and transition interface sampling methods. We find that the two methods yield the same result within an order of magnitude. However, when we compare the extrapolated simulation data with the only available experimental results for NaCl nucleation, we observe a discrepancy of nearly five orders of magnitude. We discuss the possible causes for this discrepancy.

Simultaneous computation of free energies and kinetics of rare events

We introduce a method to evaluate simultaneously the reaction rate constant and the free energy profile of a process in a complex environment. The method employs the partial path transition interface sampling technique we recently developed for the calculation of rate constants in diffusive systems. We illustrate the applicability of the technique by studying a simple dimer in a repulsive fluid, and show that the free energy can be obtained at no additional computational cost.

Sampling rare switching events in biochemical networks

Bistable biochemical switches are widely found in gene regulatory networks and signal transduction pathways. Their switching dynamics are difficult to study, however, because switching events are rare, and the systems are out of equilibrium. We present a simulation method for predicting the rate and mechanism of the flipping of these switches. We apply it to a genetic switch and find that it is highly efficient. The path ensembles for the forward and reverse processes do not coincide. The method is widely applicable to rare events and nonequilibrium processes.

Tools for channels: moving towards molecular calculations of gating and permeation in ion channel biophysics

Recent X-ray structures of voltage gated potassium channels provide an exciting opportunity to connect molecular structures with measured biological function. Two of the most important connections for these channels are: first, to the molecular basis behind selectivity and the associated free energy profile underlying ionic current flow and, second, to a true molecular understanding of the large-scale conformational transitions that underlie voltage dependent gating. But, existing computational tools need to be further developed to reach these goals. In this contribution to the symposia on sampling methods we outline our dynamic importance sampling method for sampling large-scale conformational transitions as well as our studies with non-equilibrium work events and equilibrium overlap sampling (OS) methods for sampling events related to the calculation of relative free energies.

Kinetic pathways of beta-hairpin (un)folding in explicit solvent

We examine the dynamical (un)folding pathways of the C-terminal beta-hairpin of protein G-B1 at room temperature in explicit solvent, by employing transition path sampling algorithms. The path ensembles contain information on the folding kinetics, including solvent motion. We determine the transition state ensembles for the two main transitions: 1), the hydrophobic collapse; and 2), the backbone hydrogen bond formation. In both cases the transition state ensembles are characterized by a layer (1) or a strip (2) of water molecules in between the two hairpin strands, supporting the hypothesis of the solvent as lubricant in the folding process. The transition state ensembles do not correspond with saddle points in the equilibrium free-energy landscapes. The kinetic pathways are thus not completely determined by the free-energy landscape. This phenomenon can occur if the order parameters obey different timescales. Using the transition interface sampling technique, we calculate the rate constants for (un)folding and find them in reasonable agreement with experiments, thus supporting the validation of using all-atom force fields to study protein folding.

Folding of the GB1 hairpin peptide from discrete path sampling

The discrete path sampling technique is used to calculate folding pathways of the 16-amino acid beta hairpin-forming sequence from residues 41-56 of the B1 domain of protein G. The folding time is obtained using master equation dynamics and kinetic Monte Carlo simulations, and the time evolution of different order parameters and occupation probabilities of groups of minima are calculated and used to characterize intermediates on the folding pathway.

Computing time scales from reaction coordinates by milestoning

An algorithm is presented to compute time scales of complex processes following predetermined milestones along a reaction coordinate. A non-Markovian hopping mechanism is assumed and constructed from underlying microscopic dynamics. General analytical analysis, a pedagogical example, and numerical solutions of the non-Markovian model are presented. No assumption is made in the theoretical derivation on the type of microscopic dynamics along the reaction coordinate. However, the detailed calculations are for Brownian dynamics in which the velocities are uncorrelated in time (but spatial memory remains).

Rate constants for diffusive processes by partial path sampling

We introduce a path sampling method for the computation of rate constants for complex systems with a highly diffusive character. Based on the recently developed transition interface sampling (TIS) algorithm this procedure increases the efficiency by sampling only parts of complete transition trajectories. The algorithm assumes the loss of memory for diffusive progression along the reaction coordinate. We compare the new partial path technique to the TIS method for a simple diatomic system and show that the computational effort of the new method scales linearly, instead of quadratically, with the width of the diffusive barrier. The validity of the memory loss assumption is also discussed.

From transition paths to transition states and rate coefficients

Transition states are defined as points in configuration space with the highest probability that trajectories passing through them are reactive (i.e., form transition paths between reactants and products). In the high-friction (diffusive) limit of Langevin dynamics, the resulting ensemble of transition states is shown to coincide with the separatrix formed by points of equal commitment (or splitting) probabilities for reaching the product and reactant regions. Transition states according to the new criterion can be identified directly from equilibrium trajectories, or indirectly by calculating probability densities in the equilibrium and transition-path ensembles using umbrella and transition-path sampling, respectively. An algorithm is proposed to calculate rate coefficients from the transition-path and equilibrium ensembles by estimating the frequency of transitions between reactants and products.

Using path sampling to build better Markovian state models: Predicting the folding rate and mechanism of a tryptophan zipper beta hairpin

We propose an efficient method for the prediction of protein folding rate constants and mechanisms. We use molecular dynamics simulation data to build Markovian state models (MSMs), discrete representations of the pathways sampled. Using these MSMs, we can quickly calculate the folding probability (P(fold)) and mean first passage time of all the sampled points. In addition, we provide techniques for evaluating these values under perturbed conditions without expensive recomputations. To demonstrate this method on a challenging system, we apply these techniques to a two-dimensional model energy landscape and the folding of a tryptophan zipper beta hairpin.

Atomistic understanding of kinetic pathways for single base-pair binding and unbinding in DNA

We combine free-energy calculations and molecular dynamics to elucidate a mechanism for DNA base-pair binding and unbinding in atomic detail. Specifically, transition-path sampling is used to overcome computational limitations associated with conventional techniques to harvest many trajectories for the flipping of a terminal cytosine in a 3-bp oligomer in explicit water. Comparison with free-energy projections obtained with umbrella sampling reveals four coordinates that separate true dynamic transition states from stable reactant and product states. Unbinding proceeds via two qualitatively different pathways: one in which the flipping base breaks its intramolecular hydrogen bonds before it unstacks and another in which it ruptures both sets of interactions simultaneously. Both on- and off-pathway intermediates are observed. The relation of the results to coarse-grained models for DNA-based biosensors is discussed.

Transition-path sampling of beta-hairpin folding

We examine the dynamical folding pathways of the C-terminal beta-hairpin of protein G-B1 in explicit solvent at room temperature by means of a transition-path sampling algorithm. In agreement with previous free-energy calculations, the resulting path ensembles reveal a folding mechanism in which the hydrophobic residues collapse first followed by backbone hydrogen-bond formation, starting with the hydrogen bonds inside the hydrophobic core. In addition, the path ensembles contain information on the folding kinetics, including solvent motion. Using the recently developed transition interface sampling technique, we calculate the rate constant for unfolding of the protein fragment and find it to be in reasonable agreement with experiments. The results support the validation of using all-atom force fields to study protein folding.