Exploring High Dimensional Free Energy Landscapes: Temperature Accelerated Sliced Sampling

Biased sampling of collective variables is widely used to accelerate rare events in molecular simulations and to explore free energy surfaces. However, computational efficiency of these methods decreases with increasing number of collective variables, which severely limits the predictive power of the enhanced sampling approaches. Here we propose a method called Temperature Accelerated Sliced Sampling (TASS) that combines temperature accelerated molecular dynamics with umbrella sampling and metadynamics to sample the collective variable space in an efficient manner. The presented method can sample a large number of collective variables and is advantageous for controlled exploration of broad and unbound free energy basins. TASS is also shown to achieve quick free energy convergence and is practically usable with ab initio molecular dynamics techniques

Sampling Free Energy Surfaces as Slices by Combining Umbrella Sampling and Metadynamics

Metadynamics (MTD) is a very powerful technique to sample high-dimensional free energy landscapes, and due to its self-guiding property, the method has been successful in studying complex reactions and conformational changes. MTD sampling is based on filling the free energy basins by biasing potentials and thus for cases with flat, broad and unbound free energy wells, the computational time to sample them becomes very large. To alleviate this problem, we combine the standard Umbrella Sampling (US) technique with MTD to sample orthogonal collective variables (CVs) in a simultaneous way. Within this scheme, we construct the equilibrium distribution of CVs from biased distributions obtained from independent MTD simulations with umbrella potentials. Reweighting is carried out by a procedure that combines US reweighting and Tiwary-Parrinello MTD reweighting within the Weighted Histogram Analysis Method (WHAM). The approach is ideal for a controlled sampling of a CV in a MTD simulation, making it computationally efficient in sampling flat, broad and unbound free energy surfaces. This technique also allows for a distributed sampling of a high-dimensional free energy surface, further increasing the computational efficiency in sampling. We demonstrate the application of this technique in sampling high-dimensional surface for various chemical reactions using ab initio and QM/MM hybrid molecular dynamics simulations. Further, in order to carry out MTD bias reweighting for computing forward reaction barriers in ab initio or QM/MM simulations, we propose a computationally affordable approach that does not require recrossing trajectories

Computational Study of pKa shift of Aspartate residue in Thioredoxin: Role of Configurational Sampling and Solvent Model

Alchemical free energy calculations are widely used in predicting pKa, and binding free energy calculations in biomolecular systems. These calculations are carried out using either Free Energy Perturbation (FEP) or Thermodynamic Integration (TI). Numerous efforts have been made to improve the accuracy and efficiency of such calculations, especially by boosting conformational sampling. In this paper, we use a technique that enhances the conformational sampling by temperature acceleration of collective variables for alchemical transformations and applies it to the prediction of pKa of the buried Asp 26 residue in thioredoxin protein. We discuss the importance of enhanced sampling in the pKa calculations. The effect of the solvent models in the computed pKa values is also presented.Comment: 29 pages with 13 figure

Challenges in modelling homogeneous catalysis : new answers from ab initio molecular dynamics to the controversy over the Wacker process

The controversial reaction mechanism considering experimental results and theoretical treatment from static to ab initio molecular dynamic simulations is reviewed.</p

Mechanism and kinetics of Aztreonam hydrolysis catalyzed by class-C β-lactamase : a temperature-accelerated sliced sampling study

Enhanced sampling of large number of collective variables (CVs) is inevitable in molecular dynamics (MD) simulations of complex chemical processes such as enzymatic reactions. Because of the computational overhead of hybrid quantum mechanical/molecular mechanical (QM/MM)-based MD simulations, especially together with density functional theory, predictions of reaction mechanism, and estimation of free-energy barriers have to be carried out within few tens of picoseconds. We show here that the recently developed temperature-accelerated sliced sampling method allows one to sample large number of CVs, thereby enabling us to obtain rapid convergence in free-energy estimates in QM/MM MD simulation of enzymatic reactions. Moreover, the method is shown to be efficient in exploring flat and broad free-energy basins that commonly occur in enzymatic reactions. We demonstrate this by studying deacylation and reverse acylation reactions of aztreonam drug catalyzed by a class-C β lactamase (CBL) bacterial enzyme. Mechanistic details and nature of kinetics of aztreonam hydrolysis by CBL are elaborated here. The results of this study point to characteristics of the aztreonam drug that are responsible for its slow hydrolysis