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Theory, Molecular, Mesoscopic Simulations, and Experimental Techniques of Aqueous Phase Adsorption
Published in Jayant K. Singh, Nishith Verma, Aqueous Phase Adsorption, 2018
Jayant K. Singh, Nishith Verma
An alternative to free energy perturbation calculations is thermodynamic integration [24,25], where the free energy difference between two systems (one characterized by H = HA or λ = 0 in equation (1.31) and the other by H = HB or λ = 1 in equation (1.31)) can be represented as: ∆G=∫λ=0λ=1〈∂H∂λ〉λdλ
Three-stage multiscale modelling of the NMDA neuroreceptor
Published in Molecular Physics, 2021
Francesco Di Palma, Sauro Succi, Fabio Sterpone, Marco Lauricella, Franck Pérot, Simone Melchionna
In allostery, the function of a receptor is modified by the interaction with its ligands, not only at the active site but also at a spatially distinct site of different specificity. In allostery, the interaction of the functional sites results in an altered affinity of ligand binding, thus depending on the dynamic interaction with the substrate. Ideally the conformational changes induced by the binding of the allosteric effector can be finely followed by brute force MD simulations at atomistic resolution. For instance, if the allosteric response path is of interest, starting from the substrate-free equilibrated structure it is possible to introduce the effector and follow in time its conformational changes and fluctuations. This is the strategy used in our approach. In other situations, where both the APO and HOLO states are available, the thermal fluctuations in each state, and possible state interconversion can be simulated with brute force MD or by enhanced sampling techniques (e.g. parallel tempering, thermodynamic integration, metadynamics, etc.).
Towards sustainable micro-pollutants’ removal from wastewaters: caffeine solubility, self-diffusion and adsorption studies from aqueous solutions into hydrochars
Published in Molecular Physics, 2018
S. Román, B. Ledesma, A. Álvarez, C. Herdes
Currently, the estimation of self-diffusion coefficients and free energies using molecular simulation techniques has attracted much interest in areas such as drug design and material science – it is worth noticing that this work solely refers to the diffusion of CAF as its self-diffusion coefficient. Given an appropriate description of the molecular interactions (i.e. the Hamiltonian), the diffusion of selected species can be calculated from molecular dynamics (MD) simulations by tracking the mean square displacement of such compounds as a function of time, without the limiting constraint of infinite dilution of experimental systems. Common free energy types include the solvation, transfer, binding and conformational free energy. The ability to calculate accurate estimates of the free energy from molecular simulations overcomes the difficult experimental measurement of these relevant thermodynamic properties of a system. Conversely, to obtain a reliable estimate of the free energy of a system from molecular simulations, some challenges must be met [15,16]. The most common methods to estimate free energy are thermodynamic integration, free energy perturbation, umbrella sampling and potential of mean force [15,16].
Effect of fluorination on the partitioning of alcohols
Published in Molecular Physics, 2019
Mohammad Soroush Barhaghi, Chloe Luyet, Jeffrey J. Potoff
In addition to using only uncorrelated samples, care must be taken to ensure that data used in the free energy calculation are collected from simulations that have reached equilibrium. Prior molecular dynamics simulations have shown, for example, challenges in converging liquid phase densities and free energies of solvation in 1-octanol [77]. In this work, NPT simulations of 3 × 107 MCS were used to equilibrate the system at each prior to the production run, ensuring stability of the density during free energy calculations, as shown in Figure S2 for perfluorooctanol in 1-octanol. Once free energy data were collected, convergence of the data were assessed by calculating free energies of hydration/solvation in both the forward and reverse directions with alchemical-analysis [72]. In the forward direction, the free energy was calculated using data in the order in which they were collected, while in the ‘reverse’ direction, the free energy was calculated from the data ordered in the reverse of which it was collected. As shown in Figure 2 for F2H6, the forward and reverse calculations match within the statistical uncertainty of the data, suggesting convergence of the free energy calculations [72,78]. Free energies were calculated from simulation data using a variety of thermodynamic integration methods (trapezoidal rule (TI) and cubic spline (TI-CUBIC)), and free energy perturbation techniques (Bennett acceptance ratio (BAR) and multi-state Bennett acceptance ratio (MBAR)). MBAR results are discussed in the body of the paper, while results for TI and BAR may be found in Table S5 of the supporting information. For simulations that have high quality sampling, and sufficient overlap between energy difference distributions, it is expected that all methods will produce similar results. As shown in Figure 3, good agreement for all intermediate states was achieved with all methods.