Clare McCabe

SAFT-VR modelling of the phase equilibrium of long-chain n-alkanes

The statistical associating fluid theory for potentials of variable attractive range (SAFT-VR) has been used in the calculation of the phase equilibria for long-chain n-alkanes and their mixtures. We treat the molecules as chains formed from united-atom hard-sphere segments, with a square-well potential of variable attractive range to describe the dispersive forces. A empirical relationship derived in earlier work is used to determine the number of such segments in relation to the carbon number for each member of the homologous series. Simple linear relationships between the potential model parameters and molecular weight have been determined enabling predictions of the fluid phase equilibria of heavier n-alkane molecules for which no experimental data are available. This is illustrated by a comparison with simulation data from the literature for the coexisting densities of n-octatetracontane (C48H98). Additionally we have examined binary mixtures of methane+n-hexadecane (C16H34) and hexane+n-tetradecane (C14H30) with the SAFT-VR approach, using simple Lorentz–Berthelot combining rules to determine the unlike interaction parameters. This study will allow an extension of the SAFT-VR approach to polymeric systems.

Multiple Functions of Aromatic-Carbohydrate Interactions in a Processive Cellulase Examined with Molecular Simulation

Background: Aromatic residues line glycoside hydrolase active sites mediating ligand binding. Results: Binding affinity is significantly altered upon tryptophan to alanine mutation, although relative to the location in the active site. Conclusion: Aromatic-carbohydrate interactions are employed in a variety of functionalities within the purview of ligand binding. Significance: Understanding the functional role of aromatic residues in the active site is necessary for the rational design of new carbohydrate-active enzymes. Proteins employ aromatic residues for carbohydrate binding in a wide range of biological functions. Glycoside hydrolases, which are ubiquitous in nature, typically exhibit tunnels, clefts, or pockets lined with aromatic residues for processing carbohydrates. Mutation of these aromatic residues often results in significant activity differences on insoluble and soluble substrates. However, the thermodynamic basis and molecular level role of these aromatic residues remain unknown. Here, we calculate the relative ligand binding free energy by mutating tryptophans in the Trichoderma reesei family 6 cellulase (Cel6A) to alanine. Removal of aromatic residues near the catalytic site has little impact on the ligand binding free energy, suggesting that aromatic residues immediately upstream of the active site are not directly involved in binding, but play a role in the glucopyranose ring distortion necessary for catalysis. Removal of aromatic residues at the entrance and exit of the Cel6A tunnel, however, dramatically impacts the binding affinity, suggesting that these residues play a role in chain acquisition and product stabilization, respectively. The roles suggested from differences in binding affinity are confirmed by molecular dynamics and normal mode analysis. Surprisingly, our results illustrate that aromatic-carbohydrate interactions vary dramatically depending on the position in the enzyme tunnel. As aromatic-carbohydrate interactions are present in all carbohydrate-active enzymes, these results have implications for understanding protein structure-function relationships in carbohydrate metabolism and recognition, carbon turnover in nature, and protein engineering strategies for biomass utilization. Generally, these results suggest that nature employs aromatic-carbohydrate interactions with a wide range of binding affinities for diverse functions.

Coarse-grained molecular models of water: a review

Coarse-grained (CG) models have proven to be very effective tools in the study of phenomena or systems involving large time- and length-scales. By decreasing the degrees of freedom in the system and using softer interactions than seen in atomistic models, larger time steps can be used and much longer simulation times can be studied. CG simulations are widely used to study systems of biological importance that are beyond the reach of atomistic simulation, necessitating a computationally efficient and accurate CG model for water. In this review, we discuss the methods used for developing CG water models and the relative advantages and disadvantages of the resulting models. In general, CG water models differ with regard to how many waters each CG group or bead represents, whether analytical or tabular potentials have been used to describe the interactions, and how the model incorporates electrostatic interactions. How the models are parameterised, which typically depends on their application, is also discussed.

THE THERMODYNAMICS OF HETERONUCLEAR MOLECULES FORMED FROM BONDED SQUARE-WELL (BSW) SEGMENTS USING THE SAFT-VR APPROACH

We broaden the scope of the statistical associating fluid theory for potentials of variable attractive range (SAFT-VR) to treat heteron uclear chain molecules formed from bonded square-well (BSW) segments. The ideas of the bonded hard sphere (BHS) treatment for distributed-site models composed of hard-sphere segments are applied to square-well sites with the SAFT-VR approach. The results of isothermal—isobaric Monte Carlo simulations are reported for heteronuclear square-well diatomics with different sets of energy and range parameters. The SAFT-VR approach provides an excellent description of the equation of state of the diatomic systems for a wide range of densities. The goal of the work is to provide a rigorous treatment of distributed-site models of fluids, and to establish a framework for a group contribution approach with SAFT-VR.

Computational Investigation of Glycosylation Effects on a Family 1 Carbohydrate-binding Module

Background: Family 1 carbohydrate-binding modules (CBMs) are often components of cellulases for binding to cellulose. Results: Family 1 CBM binding affinity is dramatically affected by the presence of O-glycosylation near the CBM binding face. Conclusion: Glycosylation should be accounted for in CBM binding affinity studies. Significance: Glycosylation can be harnessed to tune cellulase binding affinity, which is known to affect activity. Carbohydrate-binding modules (CBMs) are ubiquitous components of glycoside hydrolases, which degrade polysaccharides in nature. CBMs target specific polysaccharides, and CBM binding affinity to cellulose is known to be proportional to cellulase activity, such that increasing binding affinity is an important component of performance improvement. To ascertain the impact of protein and glycan engineering on CBM binding, we use molecular simulation to quantify cellulose binding of a natively glycosylated Family 1 CBM. To validate our approach, we first examine aromatic-carbohydrate interactions on binding, and our predictions are consistent with previous experiments, showing that a tyrosine to tryptophan mutation yields a 2-fold improvement in binding affinity. We then demonstrate that enhanced binding of 3–6-fold over a nonglycosylated CBM is achieved by the addition of a single, native mannose or a mannose dimer, respectively, which has not been considered previously. Furthermore, we show that the addition of a single, artificial glycan on the anterior of the CBM, with the native, posterior glycans also present, can have a dramatic impact on binding affinity in our model, increasing it up to 140-fold relative to the nonglycosylated CBM. These results suggest new directions in protein engineering, in that modifying glycosylation patterns via heterologous expression, manipulation of culture conditions, or introduction of artificial glycosylation sites, can alter CBM binding affinity to carbohydrates and may thus be a general strategy to enhance cellulase performance. Our results also suggest that CBM binding studies should consider the effects of glycosylation on binding and function.

Predicting the High-Pressure Phase Equilibria of Binary Mixtures of n -Alkanes Using the SAFT-VR Approach

The phase behavior of selected alkane binary mixtures is studied using SAFT-VR, a version of the statistical associating fluid theory for potentials of variable attractive range (SAFT). We treat the n-alkane molecules as chains formed from united-atom hard-sphere segments with square-well potentials of variable range to describe the attractive interactions. We use a simple relationship between the number of carbon atoms in the n-alkane molecule and the number of segments in the united atom chains in order to predict the phase behavior of n-butane with other n-alkanes. The calculated vapor pressures and saturated liquid densities of the pure components are fitted to experimental data from the triple point to the critical point. These optimized parameters are rescaled by the respective experimental critical points and used to determine the critical lines and phase behavior of the mixtures. We use the Lorentz-Berthelot combining rule for the unlike interactions. We predict the phase behavior of n-butane + n-alkane binary mixtures, concentrating mainly on the critical region. The gas-liquid critical lines predicted by SAFT-VR for the n-alkane mixtures are in excellent agreement with the experimental data, and improve significantly on the results obtained with the simpler SAFT-HS approach where the attractive interactions are treated at the mean-field level.

Derivation of coarse-grained potentials via multistate iterative Boltzmann inversion.

In this work, an extension is proposed to the standard iterative Boltzmann inversion (IBI) method used to derive coarse-grained potentials. It is shown that the inclusion of target data from multiple states yields a less state-dependent potential, and is thus better suited to simulate systems over a range of thermodynamic states than the standard IBI method. The inclusion of target data from multiple states forces the algorithm to sample regions of potential phase space that match the radial distribution function at multiple state points, thus producing a derived potential that is more representative of the underlying interactions. It is shown that the algorithm is able to converge to the true potential for a system where the underlying potential is known. It is also shown that potentials derived via the proposed method better predict the behavior of n-alkane chains than those derived via the standard IBI method. Additionally, through the examination of alkane monolayers, it is shown that the relative weight given to each state in the fitting procedure can impact bulk system properties, allowing the potentials to be further tuned in order to match the properties of reference atomistic and/or experimental systems.

Molecular dynamics study of the nano-rheology of n-dodecane confined between planar surfaces

Realistic molecular simulations agree with previously published surface force experiments that n-dodecane confined between mica surfaces displays shear-thinning starting at shear rate orders of magnitude less than in the bulk fluid. We probe the origin of this behavior by studying rotational and diffusional relaxations in the simulated fluid and find a freezing-out of the rotational degrees of freedom and a power-law diffusional relaxation, resulting in over seven orders of magnitude increase in the relaxation time.

Tribological durability of silane monolayers on silicon.

We report the frictional performance and long-term tribological stability of various alkyl silane monolayer films on silicon by using pin-on-disk tribometry at ambient conditions. We show that the durability of monolayers derived from n-alkyltrichlorosilanes on silicon increases exponentially with the chain length of the silane precursor, which we relate to the cohesive energy of these monolayers through molecular dynamics simulations. X-ray photoelectron spectroscopy (XPS) was used to show that tribological damage consisted of the loss of molecular components that could be partially replaced upon exposure to a solution containing perfluorinated silane precursors. For monolayers derived from n-octadecyltrichlorosilane, a critical load was identified to be approximately 250 mN (200 MPa), above which failure of films occurred within 100 cycles of testing. Monolayers with hydroxyl surfaces exhibited reduced stabilities due to stronger tip-surface interactions. Monolayers with the capability for cross-linking exhibited much greater stabilities than monolayers where cross-linking was limited or prevented. Collectively, these results demonstrate that the mechanical durability of monolayers when subjected to a tribological load is greatly enhanced by maximizing dispersional interactions and cross-linking and minimizing tip-surface interactions.

On the investigation of coarse-grained models for water: balancing computational efficiency and the retention of structural properties.

Developing accurate models of water for use in computer simulations is important for the study of many chemical and biological systems, including lipid bilayer self-assembly. The large temporal and spatial scales needed to study such self-assembly have led to the development and application of coarse-grained models for the lipid-lipid, lipid-solvent, and solvent-solvent interactions. Unfortunately, popular center-of-mass-based coarse-graining techniques are limited to modeling water with one water per be ad. In this work, we have utilized the K-means algorithm to determine the optimal clustering of waters to allow the mapping of multiple waters to single coarse-grained beads. Through the study of a simple mixture between water and an amphiphilic solute (1-pentanol), we find a four-water bead model has the optimal balance between computational efficiency and accurate solvation and structural properties when compared to water models ranging from one to nine waters per bead. The four-water model was subsequently utilized in studies of the solvation of hexadecanoic acid and the structure, as measured via radial distribution functions, for the hydrophobic tails and the bulk water phase were found to agree well with experimental data and their atomistic target.