57 research outputs found
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
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