Optimal Reaction Coordinate Research Articles

On committor functions in milestoning.

As an optimal one-dimensional reaction coordinate, the committor function not only describes the probability of a trajectory initiated at a phase space point first reaching the product state before reaching the reactant state but also preserves the kinetics when utilized to run a reduced dynamics model. However, calculating the committor function in high-dimensional systems poses significant challenges. In this paper, within the framework of milestoning, exact expressions for committor functions at two levels of coarse graining are given, including committor functions of phase space point to point (CFPP) and milestone to milestone (CFMM). When combined with transition kernels obtained from trajectory analysis, these expressions can be utilized to accurately and efficiently compute the committor functions. Furthermore, based on the calculated committor functions, an adaptive algorithm is developed to gradually refine the transition state region. Finally, two model examples are employed to assess the accuracy of these different formulations of committor functions.

Optimal Reaction Coordinates and Kinetic Rates from the Projected Dynamics of Transition Paths.

Finding optimal reaction coordinates and predicting accurate kinetic rates for activated processes are two of the foremost challenges of molecular simulations. We introduce an algorithm that tackles the two problems at once: starting from a limited number of reactive molecular dynamics trajectories (transition paths), we automatically generate with a Monte Carlo approach a sequence of different reaction coordinates that progressively reduce the kinetic rate of their projected effective dynamics. Based on a variational principle, the minimal rate accurately approximates the exact one, and it corresponds to the optimal reaction coordinate. After benchmarking the method on an analytic double-well system, we apply it to complex atomistic systems: the interaction of carbon nanoparticles of different sizes in water.

Local Ion Densities can Influence Transition Paths of Molecular Binding.

Improper reaction coordinates can pose significant problems for path-based binding free energy calculations. Particularly, omission of long timescale motions can lead to over-estimation of the energetic barriers between the bound and unbound states. Many methods exist to construct the optimal reaction coordinate using a pre-defined basis set of features. Although simulations are typically conducted in explicit solvent, the solvent atoms are often excluded by these feature sets—resulting in little being known about their role in reaction coordinates, and ultimately, their role in determining (un)binding rates and free energies. In this work, analysis is done on an extensive set of host-guest unbinding trajectories, working to characterize differences between high and low probability unbinding trajectories with a focus on solvent-based features, including host-ion interactions, guest-ion interactions and location-dependent ion densities. We find that differences in ion densities as well as guest-ion interactions strongly correlate with differences in the probabilities of reactive paths that are used to determine free energies of (un)binding and play a significant role in the unbinding process.

Learning reaction coordinates via cross-entropy minimization: Application to alanine dipeptide

We propose a cross-entropy minimization method for finding the reaction coordinate from a large number of collective variables in complex molecular systems. This method is an extension of the likelihood maximization approach describing the committor function with a sigmoid. By design, the reaction coordinate as a function of various collective variables is optimized such that the distribution of the committor pB * values generated from molecular dynamics simulations can be described in a sigmoidal manner. We also introduce the L2-norm regularization used in the machine learning field to prevent overfitting when the number of considered collective variables is large. The current method is applied to study the isomerization of alanine dipeptide in vacuum, where 45 dihedral angles are used as candidate variables. The regularization parameter is determined by cross-validation using training and test datasets. It is demonstrated that the optimal reaction coordinate involves important dihedral angles, which are consistent with the previously reported results. Furthermore, the points with pB *∼0.5 clearly indicate a separatrix distinguishing reactant and product states on the potential of mean force using the extracted dihedral angles.

Microcanonical coarse-graining of the kinetic Ising model.

We propose a scheme for coarse-graining the dynamics of the 2-D kinetic Ising model onto the microcanonical ensemble. At subcritical temperatures, 2-D and higher-dimensional Ising lattices possess two basins of attraction separated by a free energy barrier. Projecting onto the microcanonical ensemble has the advantage that the dependence of the crossing rate constant on environmental conditions can be obtained from a single Monte Carlo trajectory. Using various numerical methods, we computed the forward rate constants of coarse-grained representations of the Ising model and compared them with the true value obtained from brute force simulation. While coarse-graining preserves detailed balance, the computed rate constants for barrier heights between 5 kT and 9 kT were consistently 50% larger than the true value. Markovianity testing revealed loss of dynamical memory, which we propose accounts for coarse-graining error. Committor analysis did not support the alternative hypothesis that microcanonical projection is incompatible with an optimal reaction coordinate. The correct crossing rate constant was obtained by spectrally decomposing the diffusion coefficient near the free energy barrier and selecting the slowest (reactive) component. The spectral method also yielded the correct rate constant in the 3-D Ising lattice, where coarse-graining error was 6% and memory effects were diminished. We conclude that microcanonical coarse-graining supplemented by spectral analysis of short-term barrier fluctuations provides a comprehensive kinetic description of barrier crossing in a non-inertial continuous-time jump process.

Orthogonal order parameters to model the reaction coordinate of an enzyme catalyzed reaction

The choice of suitable collective variables in formulating an optimal reaction coordinate is a challenging task for activated transitions between a pair of stable states especially when dealing with biochemical changes such as enzyme catalyzed reactions. A detailed benchmarking study is carried out on the choice of collective variables that can distinguish between the stable states unambiguously. We specifically address the issue if these variables may be directly used to model the optimal reaction coordinate, or if it would be better to use their orthogonalized counterparts. The proposed computational scheme is applied to the rate determining intramolecular proton transfer step in the enzyme human carbonic anhydrase II. The optimum reaction coordinate is determined with and without orthogonalization of the collective variables pertinent to a key conformational fluctuation and the actual proton transfer step at the active site of the enzyme. Suitability of the predicted reaction coordinates in different processes is examined in terms of the free energy profile projected along the reaction coordinate, the rate constant of transition and the underlying molecular mechanism of barrier crossing. Our results indicate that a better agreement with earlier simulation and experimental data is obtained when the orthogonalized collective variables are used to model the reaction coordinate.

Reaction Coordinate, Free Energy, and Rate of Intramolecular Proton Transfer in Human Carbonic Anhydrase II.

The role of structure and dynamics of an enzyme has been investigated at three different stages of its function including the chemical event it catalyzes. A one-pot computational method has been designed for each of these stages on the basis of classical and/or quantum mechanical-molecular mechanical molecular dynamics and transition path sampling simulations. For a pair of initial and final states A and B separated by a high free-energy barrier, using a two-stage selection process, several collective variables (CVs) are identified that can delineate A and B. However, these CVs are found to exhibit strong cross-coupling over the transition paths. A set of mutually orthogonal order parameters is then derived from these CVs and an optimal reaction coordinate, r, determined applying half-trajectory likelihood maximization along with a Bayesian information criterion. The transition paths are also used to project the multidimensional free energy surface and barrier crossing dynamics along r. The proposed scheme has been applied to the rate-determining intramolecular proton transfer reaction of the well-known enzyme human carbonic anhydrase II. The potential of mean force, F( r), in the absence of the chemical step is found to reproduce earlier results on the equilibrium population of two side-chain orientations of key residue His-64. Estimation of rate constants, k, from mean first passage times for the three different stages of catalysis shows that the rate-determining step of intramolecular proton transfer occurs with k ≃ 1.0 × 106 s-1, in close agreement with known experimental results.

Predicting reaction coordinates in energy landscapes with diffusion anisotropy.

We consider a range of model potentials with metastable states undergoing molecular dynamics coupled to a thermal bath in the high friction regime and consider how the optimal reaction coordinate depends on the diffusion anisotropy. For this we use our recently proposed method "spectral gap optimization of order parameters (SGOOP)" [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)]. We show how available information about dynamical observables in addition to static information can be incorporated into SGOOP, which can then be used to accurately determine the "best" reaction coordinate for arbitrary anisotropies. We compare our results with transmission coefficient calculations and published benchmarks wherever applicable or available, respectively.

Calculating Iso-Committor Surfaces as Optimal Reaction Coordinates with Milestoning.

Reaction coordinates are vital tools for qualitative and quantitative analysis of molecular processes. They provide a simple picture of reaction progress and essential input for calculations of free energies and rates. Iso-committor surfaces are considered the optimal reaction coordinate. We present an algorithm to compute efficiently a sequence of isocommittor surfaces. These surfaces are considered an optimal reaction coordinate. The algorithm analyzes Milestoning results to determine the committor function. It requires only the transition probabilities between the milestones, and not transition times. We discuss the following numerical examples: (i) a transition in the Mueller potential; (ii) a conformational change of a solvated peptide; and (iii) cholesterol aggregation in membranes.

How wet should be the reaction coordinate for ligand unbinding?

We use a recently proposed method called Spectral Gap Optimization of Order Parameters (SGOOP) [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)], to determine an optimal 1-dimensional reaction coordinate (RC) for the unbinding of a bucky-ball from a pocket in explicit water. This RC is estimated as a linear combination of the multiple available order parameters that collectively can be used to distinguish the various stable states relevant for unbinding. We pay special attention to determining and quantifying the degree to which water molecules should be included in the RC. Using SGOOP with under-sampled biased simulations, we predict that water plays a distinct role in the reaction coordinate for unbinding in the case when the ligand is sterically constrained to move along an axis of symmetry. This prediction is validated through extensive calculations of the unbinding times through metadynamics and by comparison through detailed balance with unbiased molecular dynamics estimate of the binding time. However when the steric constraint is removed, we find that the role of water in the reaction coordinate diminishes. Here instead SGOOP identifies a good one-dimensional RC involving various motional degrees of freedom.

Structural Determinants of the IF-OF Transition in Human Glucose Transporter GLUT1

Glucose transporters (GLUTs) are membrane proteins that facilitate the diffusion of glucose across the plasma membrane. Recently, the crystal structures of human GLUTs (e.g., GLUT1 and GLUT3) have been resolved in the inward-facing (IF) and outward-facing (OF) states, enabling a detailed study of their transport mechanism.In this work, we aim to characterize the IF-OF transition of GLUT1, the major glucose transporter in the human body. Starting from the GLUT1 IF state, we performed an extensive search for an optimal reaction coordinate for the transition. Employing non-equilibrium simulations, we induced the reorientation of multiple combinations of transmembrane (TM) helices of GLUT1 to trigger the transition to the OF state for each TM combination. The relevance of the reaction coordinates was then assessed by the non-equilibrium work required for the transition, as well as the induced structural rearrangement of GLUT1. As a starting point for the transitions, an OF target model of GLUT1 was first generated based on available structures of its close homologue OF-GLUT3, and further refined once the optimal reaction coordinate was obtained. Based on the minimum non-equilibrium work required to drive the IF-OF transition, we identified a specific set of TM helices whose motion is required to reach the OF state. Using this reaction coordinate, we were able to obtain previously uncharacterized stable GLUT1 OF state, and characterize multiple intermediate states connecting the IF and OF states, allowing us to identify important interhelical interactions and the gating helices suggesting a local gating mechanism apart from global large scale transition involving a proline-rich TM segment that mediates the conformational transition in GLUT1. Given the structural similarity among GLUTs, we expect that the our detailed description of the GLUT1 transition will provide a basis to study other human GLUTs.

Projected metastable Markov processes and their estimation with observable operator models.

The determination of kinetics of high-dimensional dynamical systems, such as macromolecules, polymers, or spin systems, is a difficult and generally unsolved problem - both in simulation, where the optimal reaction coordinate(s) are generally unknown and are difficult to compute, and in experimental measurements, where only specific coordinates are observable. Markov models, or Markov state models, are widely used but suffer from the fact that the dynamics on a coarsely discretized state spaced are no longer Markovian, even if the dynamics in the full phase space are. The recently proposed projected Markov models (PMMs) are a formulation that provides a description of the kinetics on a low-dimensional projection without making the Markovianity assumption. However, as yet no general way of estimating PMMs from data has been available. Here, we show that the observed dynamics of a PMM can be exactly described by an observable operator model (OOM) and derive a PMM estimator based on the OOM learning.

Bézier curve string method for the study of rare events in complex chemical systems.

We present a new string method for finding the most probable transition pathway and optimal reaction coordinate in complex chemical systems. Our approach evolves an analytic parametric curve, known as a Bézier curve, to the most probable transition path between metastable regions in configuration space. In addition, we demonstrate that the geometric properties of the Bézier curve can be used to construct the optimal reaction coordinate near the most probable reaction path, and can further be used to devise a ranking vector capable of identifying precisely which collective variables are most important for governing the transition between metastable states. We discuss the algorithmic details of the Bézier curve string method, analyze its stability, accuracy and efficiency, and illustrate its capabilities using model potential energy functions. In particular, we use the degree elevation property of Bézier curves to develop an algorithm that adaptively learns the degree polynomial necessary to accurately represent the most probable transition path. Subsequently, we apply our method to the isomerization of alanine dipeptide, and demonstrate that the reaction coordinate obtained from the Bézier curve string method is in excellent agreement with the optimal reaction coordinate constructed from an aimless shooting and maximum likelihood procedure. Finally, we apply our method to a large complex system and study the homogenous nucleation of benzene from the melt. In these two examples, we illustrate that the ranking vector correctly identifies which collective variables govern these chemical transitions.

Numerical Construction of the pfold (Committor) Reaction Coordinate for a Markov Process

To simplify the description of a complex multidimensional dynamical process, one often projects it onto a single reaction coordinate. In protein folding studies, the folding probability p(fold) is an optimal reaction coordinate which preserves many important properties of the dynamics. The construction of the coordinate is difficult. Here, an efficient numerical approach to construct the p(fold) reaction coordinate for a Markov process (satisfying the detailed balance) is described. The coordinate is obtained by optimizing parameters of a chosen functional form to make a generalized cut-based free energy profile the highest. The approach is illustrated by constructing the p(fold) reaction coordinate for the equilibrium folding simulation of FIP35 protein reported by Shaw et al. (Science 2010, 330, 341-346).

Free-Energy-Based Methods for Binding Profile Determination in a Congeneric Series of CDK2 Inhibitors

Free-energy pathway methods show great promise in computing the mode of action and the free energy profile associated with the binding of small molecules with proteins, but are generally very computationally demanding. Here we apply a novel approach based on metadynamics and path collective variables. We show that this combination is able to find an optimal reaction coordinate and the free energy profile of binding with explicit solvent and full flexibility, while minimizing human intervention and computational costs. We apply it to predict the binding affinity of a congeneric series of 5 CDK2 inhibitors. The predicted binding free energy profiles are in accordance with experiment.

Reaction Coordinates and the Transition-Vector Approximation to the IRC.

The appearance of a reaction profile or potential energy surface (PES) associated with the reaction path (defined as the path of steepest descent from the saddle point) depends on the choice of reaction coordinate onto which the intrinsic reaction coordinate is projected. This provides one with the freedom, but also the problem, of choosing the optimal perspective (i.e., the optimal reaction coordinate) for revealing what is essential for understanding the reaction. Here, we address this issue by analyzing a number of different reaction coordinates for the same set of model reactions, namely, prototypical oxidative addition reactions of C-X bonds to palladium. We show how different choices affect the appearance of the PES, and we discuss which qualities make a particular reaction coordinate most suitable for comparing and analyzing the reactions. Furthermore, we show how the transition vector (i.e., the normal mode associated with a negative force constant that leads from the saddle point to the steepest descent paths) can serve as a useful and computationally much more efficient approximation (designated TV-IRC) for full IRC computations, in the decisive region around the transition state.