ESTUDIO FINANCIERO

Like their experimental counterparts, the results of computational studies of the biomolecule-silica interface are highly dependent on the nature of the surface mod- eled and the conditions used–in vacuo or aqueous. Several groups have used DFT to calculate the binding affinities of amino-acids and their analogs to various silica surfacesin vacuo[Han et al. [2008]; Han and Sholl [2009, 2010]; Rimola et al. [2008, 2009]]. Although these studies are interesting, their findings cannot easily be ex- trapolated to shed light on the mechanisms governing peptide adsorption onto silica under aqueous conditions. As mentioned in Sections 1.2.3 and 1.2.4, the reasons for this are two-fold: first the absence of liquid water–thought to play an important role in biomolecule adsorption [Skelton et al. [2009]; Jena and Hore [2010]; Schneider and Ciacchi [2012]]; and second the potential for an amino-acid to adopt a binding geometry not possible for a residue part of a longer peptide chain. Only the first of these issues has previously been addressed at the first-principles level of theory [Costa et al. [2008]; Nonella and Seeger [2008]; Zhao et al. [2011]]. In Chapter 4 the

results of first-principles simulations of ammonium and ethanoate adsorbed at the aqueous (100) α-quartz interface are presented. This work was carried out in an attempt to addressbothof the problems commonly associated with interfacial DFT simulations and applied to the aqueous quartz (the specific form of silica studied herein) interface for the first time. By simulating the adsorption of small molecules featuring the same functional groups present in peptides, rather than the whole amino-acid, it was possible to model residue side-chain adsorption specifically.

Force-field (FF) based (rather than first-principles) simulations have been used in the majority of the work carried out in this thesis. Several interfacial FFs exist for silica [Brodka and Zerda [1996]; Lopes et al. [2006]; Cygan et al. [2004]; Lorenz et al. [2008]; Hassanali and Singer [2007]; Hassanali et al. [2010]; Patwardhan et al. [2012]], although only a small proportion of these have been specifically pa- rameterized to be biomolecule compatible [Lopes et al. [2006]; Lorenz et al. [2008]; Butenuth et al. [2012]; Patwardhan et al. [2012]]. Out of the second subset, the silica FF derived by Lopeset al. was specifically parameterized for charge-neutral hydrox- ylated quartz interfaces [Lopes et al. [2006]], while those developed by Butenuthet al. and Patwardhan et al. were designed for modeling amorphous silica [Butenuth et al. [2012]] and β-cristoballite [Patwardhan et al. [2012]] surfaces, respectively, both of which feature deprotonated silanol groups. Since the simulations reported in this thesis were performed at the aqueous quartz interface, it was appropriate to use the first FF [Lopes et al. [2006]], herein denoted ‘LFF’. LFF was comprehen- sively parameterised following the CHARMM methodology [MacKerell et al. [1998]] and contains terms which reasonably reproduce the structure of the bulk substrate, as well as the surface, thus permitting fully flexible-solid simulations.

Due to its important role in biomolecule adsorption, interfacial water struc- turing can be used to benchmark a FF. Recently, the performance of three interfa- cial silica FFs–LFF [Lopes et al. [2006]], CLAYFF [Cygan et al. [2004]] and CWCA [Lorenz et al. [2008]]–relative to both first-principles simulation (AIMD) and exper- iment was assessed at the aqueous (101) [Skelton et al. [2011a]] and (100) [Skelton et al. [2011b]] α-quartz surfaces. Both studies found that CLAYFF [Cygan et al. [2004]] was better able than LFF to reproduce the degree to which water was struc- tured at the silica interface observed in AIMD simulation. On the other hand, LFF was more apt for accurately modeling the structure of the quartz interface itself. In light of these findings, the ability of LFF and CLAYFF to model the charac- teristics of the two functional groups present in all peptides–NH+₃ and -COO−– on binding was assessed in Reference Wright and Walsh [2012b]. The FF results were benchmarked against CPMD simulations at the aqueous (100) α-quartz interface.

(It must be noted however, that the specific combination of LJ mixing rules and water model used in the parameterisation of CLAYFF is not also employed by any existing biomolecular FF calling into question its use in biointerfacial simulations.) Taken together with the results from previous MD simulations of the aqueous quartz interface using LFF [Lopes et al. [2006]; Notman and Walsh [2009]], all these find- ings suggest that LFF is at present the best FF with which to model peptide-quartz adsorption. Work by Latour andco-workersto extend their interfacial, dual param- eter set FF [Snyder et al. [2012]] to the aqueous quartz interface may lead to a more accurate description of the system in the future.

Unlike other aqueous bio-interfaces, relatively few reports of silica adsorption FF-based simulations exist in the literature. The most recent modeled the adsorp- tion of the N-terminus hexapeptide of TBP-1 [Schneider and Ciacchi [2012]], and sequences 11 (wild-type and mutated) and 13 [Patwardhan et al. [2012]] in Table 1.1 to an oxidized silicon and cristoballite surfaces, respectively. In both cases the in- terface featured unprotonated silanols, and hence carried an overall negative charge. As a consequence, the predominantly positively-charged peptides studied were ob- served to bind to the surface by electrostatics. In contrast, Orenet al. found that the hydrophobic residues of QBP-1 and sequence 19 in Table 1.1 bound strongly to the charge-neutral hydroxylated (100)α-quartz surface when they performed simu- lations at this interface [Oren et al. [2010]]. The latter results are consistent with the calculated free energies of adsorption of both amino-acid analogs [Notman and Walsh [2009]; Wright and Walsh [2012a]] (see Chapter 3).

In this thesis, two aspects of the aqueous peptide-quartz interface have been addressed by MD simulation for the first time: the potential for individual residues to energetically or spatially discriminate between different crystallographic planes of quartz on adsorption (Chapter 3); and the selectivity of QBP-1 to bind to quartz over gold (Chapter 7).