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One of the challenges in the area of molecular simulation of biointerfaces is to ensure that the interatomic potentials used to describe such interfaces capture the essential chemistry and physics of the system. The compatibility of the force-fields that describe the inorganic and biomolecular components of the system, components that correspond to very different types of matter, is essential to the successful incorporation of a descrip- tion of biomolecules and inorganic matter. Although the silica force-field used in this

work1wasdesignedto be compatible with common biomolecular force-fields, such as

CHARMM and AMBER, this is not always the case. Galeet. al. recently developed a

flexible force-field for calcium carbonate and chose the flexible SPC/Fw potential as the

corresponding water model.101 In order to reliably model the protein-mediated control

ible with established biomolecular force-fields, for example, CHARMM or AMBER,

force-fields that are traditionally used with the TIP3P model for water.102

The Importance of the Water Model to the Potential Energy Landscape (PEL)

In their biological environment, non-membrane-bound proteins are typically surrounded by water. It has long been acknowledged that the medium of liquid water has a signif- icant impact on the three-dimensional protein structure (secondary and tertiary), with the most energetically favourable arrangements being those in which the hydrophobic

residues are sequestered to the protein interior.103 Such structures are typically found

as the lowest minima of the potential energy landscape (PEL), with exceptions fore.g.

intrinsically disordered proteins. The influence of water on the protein PEL also has an impact on the frictional and random forces experienced by proteins, affecting pro-

tein dynamics.104 Considering the influence of water on both the PEL and dynamics

of proteins, it follows that in the field of molecular simulation, the means by which we describe the liquid water is of crucial importance to the results obtained from a simula- tion.

Computational Representation of Water

The large number of water molecules typically needed to keep the protein in a biolog- ically relevant state requires that the computational representation of solvent be imple- mented as economically as possible to ensure that calculations remain feasible. One option is to treat the water as a continuum dielectric, as is done in implicit solvent

models.105, 106, 107, 108 However, the approximations inherent to this approach may miss

important microscopic physical details, particularly where molecular recognition of/by the protein is important. Water could also be represented explicitly using electronic structure methods; however, the significant computational cost heavily restricts the ac- cessible system sizes and simulation timescales. A compromise is atomistic molecular dynamics (MD) used in partnership with molecular mechanics force-fields, an approach that provides an explicit treatment of water molecules within viable timescales. The molecular mechanics approach for describing interatomic potentials in itself covers a

range of complexity, including the incorporation of atomic polarisation.109

intermolecular potential functions used to describe the system. It is testimony to the importance and complexity of water that a range of force-fields have been developed

to model it. As it is a challenge to adequately represent allproperties of water on an

equal footing, different water models have been devised to possess different strengths, with most better at capturing some properties of water over others. Thus, the water model should be chosen appropriately, considering which properties are relevant to the

scientific questions under investigation. The most popular models, such as TIP3P102

and SPC,110are rigid body and have three interaction sites.

Compatibility of Biomolecular and Water Force-Fields

When modelling biomolecules in aqueous solution, the force-field to describe water

must be used in combination with a biomolecule force-field, such as CHARMM,111, 112

AMBER,113, 114 OPLS115, 116 or GROMOS.117, 118 The combination of TIP3P102 (and

TIPS3P, a modified version119) with CHARMM and AMBER is successful and widely

documented in the literature. Furthermore, several studies have already directly inves- tigated the impact of the choice of the water potential on the biomolecular system by simulating a particular protein/peptide (described by a certain biomolecule force-field)

with different water models.120, 121, 122, 123, 124, 125 However, some of the more recently

developed force-fields are yet to be extensively employed in conjunction with common biomolecule potentials, as compatibility of these models with the biomolecular com- ponent has not yet been established. SPC/Fw, a more recent flexible variant of the

rigid SPC water model, is one such water force-field.126 The model has been opti-

mised to better reflect the dynamical and dielectric properties of bulk water. We note

that Takemura and Kitao125 have previously evaluated the effect of water model (in-

cluding SPC/Fw) in combination with a biomolecule force-field (AMBER), but with an exclusive focus on the dynamical properties of proteins, such as diffusion and time- correlation functions. These authors reported that SPC/Fw reproduced both the transla- tional and rotational motion of their protein relatively well.

1.6.2

The Silica/Pure Water Interface

Although a large number of studies, both experimental and computational have investi- gated the adsorption of small organic molecules and biomolecules at the aqueous silica

interface, few have explored how this adsorption is influenced by electrolyte concen-

tration.20, 29, 57 The potential of mean force (PMF) approach (defined in section 2.1.1)

has been used to predict the adsorption strength of several amino acid analogues to dif-

ferent facets of hydroxylated α-quartz in pure water using molecular dynamics (MD)

simulations.3, 127 Schneider and Colombi Ciacchi employed metadynamics (defined in

section 2.1.1) with replica exchange with solute tempering (REST) (defined in section 2.1.1 and steered MD simulations in which you apply an external force to one or more atoms to study the binding behavior of a hexapeptide, RKLPDA, to an oxidised silicon

surface.22 Their results showed quantitive agreement with data from atomic force mi-

croscopy (AFM) experiments. In a more recent 2015 study, Colombi Ciacchi employed

the same approach to study the adsorption of theGCRLtetrapeptide at the amorphous

silica/pure water interface.128 Recently, Meissneret. al. used modelling to predict the

loss of helicity upon peptide adsorption to silica.129 Heinz and co-workers developed a

force-field for silica with a focus on improving the accuracy of the computation of inter-

facial properties.82 A major conclusion from these studies is that solvent structuring at

the solid interface exerts a strong influence over molecule-surface adsorption. It follows that factors that alter the binding environment, either directly by their presence in the interfacial region, or indirectly through their effect on this interfacial solvent structure, could play a critical role in influencing adsorption beheviour.

Indeed, it has been demonstrated that the binding environment impacts adsorp- tion properties. It is well-known that the presence of surfactant inhibits the adsorption

of oil and certain proteins on silica.130 Adsorption inhibition is thought to result from

the change in character of the silica surface after surfactant adsorption and the forma- tion of surfactant complexes with protein or oil components. Solution pH can also alter the nature of the surface and protein adsorbates through change in the protonation state. In an experimental study, Puddu and Perry observed that adsorption of charged and uncharged peptides to amorphous silica nanoparticles was highly sensitive to pH as hydronium ions mediated peptide and nanoparticle charge state and thus electrostatic,

hydrophobic and hydrogen bonding interactions.131 Surface functionalisation of silica

nanoparticles was also a factor that if slightly altered could lead to dramatic changes in

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