Investigation of Glutamic acid adsorption on Silica

Get Complete Project Material File(s) Now! »

Significance of the vibrational spectroscopy of amino acids

Infrared spectroscopy is one of the classical methods for obtaining molecular structures and observing conformational changes of small molecules. This is due to its sensitivity to the chemical composition and architecture of the molecules. The IR spectrum is mainly separated into 3 different regions; (i) the higher-energy near-IR region, approximately 14000-4000 cm-1 (0.7-2.5 µm wavelength) where overtone or combination modes of molecular vibrations are observed ; (ii) the mid—IR region from 4000-400 cm-1 (2.5-25 µm) which is generally used to study the fundamental vibrations and the associated rotational-vibrational structure ; (iii) the far-IR region, approximately from 400-10 cm-1 (25-1000 µm) whose low energy corresponds to rotational spectroscopy and low frequency vibrations.
Fourier transform infrared (FTIR) spectroscopy is also relevant for biological systems. This makes IR spectroscopy a valuable tool e.g. for the investigation of protein structures.154,155 For the determination of the secondary and tertiary structure, the individual properties of amino acids are of great importance. Recently, there has been a great deal of interest in understanding the specific vibrations of amino acids, especially amino acid side chains which play a fundamental role in stabilizing protein structures and catalyzing enzymatic reactions. These side chains vibrate at similar wavenumbers as amides vibrations I, II and III, that are dependent on the formation of the polypeptide backbone in proteins. It is estimated though that 10 to 30 % of the vibrations occurring in that region come from the side chain vibrations (Chirgadze et al156., 1975; Venyaminov and Kalnin157, 1990; Rahmelow et al158., 1998). Investigations are often restricted to the 1800-1500 cm-1 spectral region and not to the whole mid IR region. (Goormaghtigh et al159., 1994; Wright and Vanderkooni160). When studying unpolymerized amino acids, this region is of utmost importance because it carries information regarding the carboxyl and the amine vibrations found within them. Hence, peptide bond formation, and protein folding, can be investigated using IR spectroscopy.161

Literature on vibrational spectroscopy of amino acids on silica

IR spectroscopy of amino acid adsorption on surfaces started to gain interest in the 1970s, when it was observed that surface-supported amino acids induced vibrations, different from the reference bulk162 ones. Furthermore, amino acid polycondensation has been studied with this technique by a number of authors who were interested in the prebiotic synthesis of peptides, generally in the bulk.163– 165 These two lines of research came together in the work of Basiuk et al., already cited in § I.4. In this work, mid-IR spectroscopy recorded in situ on supported amino acids and the products of their thermal treatment constituted the main characterization tool.
These authors interpreted the IR data of individual amino acids on inorganic surfaces such as silica by the formation of specific hydrogen bonds between amino acid and the surface, but also of covalent bonds of the “surface ester” (Si-O-CO-R) type. While some of their interpretations may be challenged, these publications contain a wealth of data on the spectroscopic properties of supported amino acids.
Literature about the IR of amino acid adsorption on surfaces, and more particularly on silica, can be separated into two main parts: (i) those where amino acids were deposited from an aqueous phase – they were zwitterionic before adsorption on the surface, with recognizable – COO- and –NH3+ groups; (ii) those where amino acids sublimate to a vapor upon heating under reduced pressure, and thus are deposited from the gas phase where they were in the neutral form (with COOH and –NH2 groups).
To the latter category belong the studies of Basiuk et al., already mentioned, but also the high-quality data of Martra et al.
Previous work at LRS belongs to the first category, where IR was applied in the transmission mode after drying of the impregnated powder,84,86,92 as do studies by Holland et al.97 Kitadai et al.174 used a different setting, with IR in the ATR mode, allowing to characterize the adsorption process in the presence of the aqueous phase.
The two preparation techniques gave very different results. When amino acids are adsorbed in the hydrated form, they remain zwitterionic until essentially all water is removed from the silica surface (definitely above 100°C), and only then do they condense to peptides.84,86,175 In contrast, when they are adsorbed from the gas phase onto a dehydrated silica surface, the slight heating by the IR beam (around 50°C) is enough to cause condensation167. In summary, surface hydration, acido-basic AA speciation (zwitterionic vs. neutral) and peptidic condensation seem deeply connected.

Principles of ab-initio geometry optimization

Based on the existing literature, before calculation of any electronic properties, atomic positions of biomolecules as small as amino acids190 and as large as proteins191 need to be relaxed to the ground state by geometry optimization. More specifically, it has been reported previously that, prior to the calculation of NMR parameters, it is necessary to perform some optimization of the geometry in order to minimize the forces acting upon the atoms.
The starting point of the optimization of a model may be obtained from a specific structure that has been already obtained by X-ray diffraction, derived from Bragg diffraction experiments (on systems such as single-crystal, powder X-ray diffraction or neutron diffraction)193. It is well known however that sometimes X-ray diffraction is not able to locate every atom in a configuration, such as hydrogen, isoelectronic atoms or those that are in the presence of heavier elements. Moreover, in the case of amorphous or aperiodic systems, atoms cannot be easily located by diffraction techniques. In these cases, the alternative is to simply construct the structure and then perform optimization.
Geometry optimization reduces the stresses caused by external and internal forces in a given molecule for example, in modifying the relative atomic positions.
In general, there are two possible types of molecular structures, the equilibrium geometry characterized as Req and the transition state geometry Rts, both corresponding to a stationary point located on the potential energy surface (PES) (Figure 1.12) (molecular energy E(R) as a function of nuclear positions R= (R1, R2…)), our main focus however was towards the equilibrium geometry characterized as Req.

DFT modeling of amino acid adsorption on mineral (mainly silica) surface

When modeling amino acids adsorption, two criteria need to be taken into account: (i) the amount of hydroxyl (OH) groups located on the surface, which can easily give rise to more local H-bonding with the surface; (ii) the nature of the amino acid, i.e. the chemical moieties of the side chain. Amino acids having a non-polar side chain show a common path of adsorption on silica surfaces via the ammonium -NH3+ group while the carboxylate ending pends back in the solution.
Rimola et al. contributed a lot to studies on interactions between amino acids and hydroxylated silica. Many of their studies used models derived from one crystalline silica form, edingtonite. They first used limited clusters, then 1-D and 2-D slabs in a periodic approach. Their edingtonite (001) surface model exhibits a net 2.2 OH groups per nm2 and they have compared the bonding of most biological amino acids on this surface, providing adsorption energies113. Many of their other published works, mentioned in §I.3 above, are concerned with elucidating the mechanism of peptide bond formation upon thermal activation, either with Glycine or smaller, model molecules. Later on, they also used clusters derived from zeolitic structures205 and slabs of-quartz (010). Edingtonite206,207 and quartz208 were also chosen by other authors who wanted to explore the effect of regular silanols networks on bonding with amino acids, as well as cristobalite.
At the LRS, different models were used successively to represent the silica surface. The first attempts used isolated small clusters.101,102 Later on, a slab representing a hydroxylated amorphous surface with 7.66 OH/nm2 was developed and tested for Glycine adsorption210. However, this surface hydroxylation level was doubtlessly higher than that of the commercial Aerosil 380 non-porous silica used in most of the experimental studies (about OH/nm2): it would rather constitute a relevant model for precipitation silicas, which have hardly been tested experimentally for amino acids adsorption and condensation. Finally, the work of Folliet et al.
made use of the previously developed model of amorphous fumed silica that we are also using in the present thesis. Silica surface cannot sum up the entire prebiotic chemistry, hence many other oxide surfaces107,211 were simulated in the past decades showing signs of peptide bond formation possibilities.106 A whole protein is challenging to simulate, but small peptide can be adsorbed on different mineral surfaces.

READ  The Laplace Beltrami operator (¢S)

NMR Calculation by Quantum Espresso (QE)

Quantum ESPRESSO (QE) is the major open source code for quantum materials modeling using the plane-wave pseudopotential method, it has been the development platform for important methodological approach for computational systems.
Moreover, in the field of solid state NMR, a fundamental breakthrough has been made over the past decade by using the density functional theory method with a periodic approach. Hence using the PAW and GIPAW methods216, it is possible to calculate the electric field tensors (EFT), CSA (Chemical shift Anisotropy) of all magnetically active nuclei of a given structure. The simple periodic approach of the DFT enables in obtaining a good description of the material, and further optimizing the pseudopotentials used, the calculation becomes relatively favored for large number of isotopes. The shielding tensor is computed using the GIPAW216 approach which permits the reproduction of the results of a fully converged all-electron calculation. The PBE generalized gradient was used and the valence electrons were described by norm conserving pseudopotentials240 in the Kleinman-Bylander form241. The core definition for O, C, and N is 1s2 and 1s22s22p6 for Si. The core radii are 1.2 a.u. for H, 1.5 a.u. for O, 1.6 a.u. for C, 1.45 a.u. for N, and 2.0 au for Si. The wave functions were expanded on a plane wave basis set with a kinetic energy cutoff of 1088 eV. The integral over the first Brillouin zone was performed using a Monkhorst-Pack (1×1×1) k-point grid for the charge density and chemical shift tensor calculation for the adsorbed models. The isotropic chemical shift δiso is defined as δiso = − [iso −iso(ref)], whereiso is the isotropic magnetic shielding andiso(ref) is the isotropic magnetic shielding of the same nucleus in a reference compound. In the present case, referencing of the NMR chemical shield was accomplished by plotting a fit of the linear correlation between the experimental δiso and the calculatediso values of 5 relaxed structures of amino acids :-Glycine242, L-Alanine243, L-Leucine244,-Glutamic acid245,-Glutamic acid246, enabled the determination of the relation between δiso and calculatediso for the 13C and 15N nuclei (Figure 2.7). It should be noticed that the difference between the experimental chemical shifts and the regression line is at most 0.4 ppm in the case of 13C and a bit more (1 ppm) in the case of 15N, indicating a better accuracy of the calculations in the case of the carbon nucleus. The calculated Carbon and Nitrogen chemical shifts for the previously mentioned amino acids are shown in Table 2-2 and Table 2-3.

Table of contents :

1. Chapter Ⅰ : Origins of Life
I.1 Origin of small biomolecules; amino acids
I.1.1 The origins of Amino Acids
I.1.2 The ‘RNA World’ and the origins of nucleotides
I.1.3 Other primordial biomolecules : lipids
I.2 The next step: formation of biopolymers, towards peptides and proteins
I.2.1 Temperature increase
I.2.2 “Polymerization on the rocks”
I.3 Mineral surfaces at the origins of life
I.3.1 Clay Minerals
I.3.2 Pyrite and other sulfides
I.3.3 Chirality of the surface
I.4 Amino Acid polymerization on oxide surfaces
I.5 Molecular-level characterization of adsorbed biomolecules
I.5.1 Solid state NMR spectroscopy
I.5.2 Study of Organic/Inorganic interactions by ss-NMR spectroscopy
I.5.3 Literature examples of NMR investigation of amino acid adsorption on mineral surfaces
I.5.4 Some general conclusions on NMR studies
I.6 IR Spectroscopy
I.6.1 Significance of the vibrational spectroscopy of amino acids
I.6.2 Literature on vibrational spectroscopy of amino acids on silica
I.7 Other experimental techniques
I.7.1 X-Ray Diffraction
I.8 Computational Modeling
I.8.1 Theoretical Method
I.8.2 Principles of periodic DFT simulation
I.8.3 Principles of ab-initio geometry optimization
I.8.4 Description of the silica surface
I.8.5 DFT modeling of amino acid adsorption on mineral (mainly silica) surface
I.8.6 NMR Calculations
2. Chapter Ⅱ Materials and Methods
II.1 Materials
II.3 Experimental
II.3.1 Experimental approach
II.5 Molecular modeling methods
II.5.1 Structural Models
II.5.2 NMR Calculation by Quantum Espresso (QE)
3. Chapter Ⅲ: Investigation of Leucine adsorption on Silica
III.1 Introduction
III.2 Macroscopic Characterization
III.2.1 X-Ray Diffraction
III.2.2 Thermogravimetric Analysis
III.3 Spectroscopic Characterization
III.3.1 Infrared Spectroscopy
III.3.2 Solid-state NMR spectroscopy
III.4 Computational approach
III.4.1 Adsorption Energies and molecular configurations
III.5 Conclusions on the Leu/SiO2 system
4. Chapter Ⅳ: Investigation of Glutamic acid adsorption on Silica
IV.1 Introduction
IV.2 Macroscopic Characterization
IV.2.1 X-ray Diffraction
IV.2.2 Thermogravimetric Analysis
IV.3 Spectroscopic Characterization
IV.3.1 Infrared Spectroscopy
IV.3.2 Solid State Nuclear Magnetic Resonance Spectroscopy
IV.4 Computational Approach
IV.4.1 Adsorption energies and molecular configurations
IV.4.2 Calculation of NMR chemical shift values
IV.5 Conclusions on the Glu/SiO2 system
5. Chapter Ⅴ: Thermal activation of amino acids on the SiO2 surface
V.1 Thermal activation of Leu/SiO2
V.1.1 IR study of the activation of a low-loading 1% Leu/SiO2
V.1.2 IR study of the rehydration of activated forms
V.1.3 Deuterium and thermal activation
V.1.4 13C NMR of thermally activated samples
V.1.5 Activating the linear dimer H-Leu-Leu-OH on silica
V.2 Thermal activation of Glutamic acid on SiO2
V.2.1 IR study of the activation of a low-loading 1% Glu/SiO2
V.2.2 IR study of PyroGlu/SiO2
V.2.3 IR study of H-Glu-Glu-OH/SiO2
V.3 Thermal treatment of co-adsorbed systems: Glu+Leu/SiO2
V.3.1 IR study of the activation of 3%Glu+Leu/SiO2
V.4 13C solid-state NMR of co-adsorbed systems (Glu+Leu)/SiO2
V.4.1 13C NMR
V.4.2 15N NMR
V.4.3 1H – 13C 2D HETCOR
V.4.4 1H – 15N 2D HETCOR
V.5 Conclusion and perspectives
General Conclusion


Related Posts