Computational modeling was employed to achieve an optimal balance between accuracy and computational cost in studying oligomer-mineral interactions. The MM+ force field was selected for initial geometry optimization and molecular dynamics simulations due to its proven efficacy in modeling large, structured organic-inorganic interfaces. Its parametrization for potential energy calculations, including van der Waals forces, electrostatic interactions, and torsion energies, is particularly suitable for simulating the adsorption and adhesion of glycine oligomers onto the calcite (CaCO₃) surface, providing a robust structural foundation. Molecular dynamics further relaxed the system by sampling conformational space through atomic vibrations, helping to locate a global energy minimum and ensuring structural stability [[32]]. Subsequently, the PM3 semi-empirical method was applied to the optimized structures, as it incorporates quantum-mechanical electron effects at a feasible computational cost. This allows for the determination of molecular interaction sites and assessment of potential chemical reactivity by accounting for electron distribution and core repulsion, which is essential for understanding charge transfer and polarization at the oligomer-calcite interface. For both MM+ and PM3, the Polak-Ribiere conjugate gradient algorithm was used with a root mean square gradient of 0.001 kcal∙mol⁻¹. This combined methodology ensures both efficient conformational sampling and electronic insight, making it highly appropriate for systems where organic molecule-mineral surface interactions play a defining role.

Light is a form of electromagnetic radiation composed of photons. Therefore, it can be used to study the changes that occur when a material is exposed to a light source. To use polarized light, the polarizers adapted to the microscope (SMART-POL Drawell, Chongqing, China) are exchanged so that the birefringent effect exposes the characteristics of the studied materials. The microscope is coupled to a digital camera to obtain different images.

Heating was constant at a rate of 20˚C /min, in a static air atmosphere with aluminum crucibles. DSC’s purpose is to characterize the stability of compounds (ΔH, ec. 1) and induce the state of structural relaxation in molecules [[33]]. For sample analysis, the instrument (DSC-100 Tryte Technology, Hunan Development Co., Ltd, Yuhua District, Changsha, Hunan, China) has a heating cell containing two sensors where a reference crucible and a crucible with the sample are placed, in addition to a control panel where the parameters under which the sample will be analyzed are configured.

C p = ( Δ H Δ T ) p → Δ H = ∫ T 1 T 2 C p p , e x d T ①

Infrared spectroscopy determines the components and structure of molecular samples through their vibrational spectra, yielding bands corresponding to specific functional groups. As a non-destructive analysis tool, it allows samples to be recovered at different times during their analysis. A beam of light emitting in the entire infrared region is incident on a beam splitter that divides it into two beams of equivalent energy, one of which is incident on a movable mirror and the other on a fixed mirror. The beams are recombined, and the resulting beam is emitted towards the sample, which absorbs the wavelengths and emits them to the detector, producing a spectrogram with the bands emitted by the irradiated sample [[34]]. In this study, an ATR-FTIR PerkinElmer 100 FT-IR spectrometer (Shelton, CT, USA) equipped with universal fully attenuated reflectance sampling and a zinc selenide sample holder was used. IR spectra were recorded in the range 4000 cm⁻¹ to 650 cm⁻¹ with a resolution of 4 cm⁻¹ and four scans per sample.

The Second Derivative Method to Increase the Resolution of the Infrared Spectra

One way to gain insight into the signals in more detail from the FTIR spectra is by applying the second derivative (ec. 2), which can evidence small changes in the vibrational behavior from the education for derivatives:

d 2 T ( f ) d f 2 ≈ T ( f + Δ f ) − 2 T ( f ) + T ( f − Δ f ) ( Δ f ) ②

After using the second derivative, the small changes of the band will be revealed, showing the differences among bands [[35]]. These visual changes can provide information about the most reactive intervals in the spectrogram; therefore, we can focus on this to interpret the results.

Our computer simulations revealed varying energy levels associated with the formation of secondary structures, which are significant due to their emergent properties, particularly in catalysis and organic synthesis. The results indicate that the β-sheet exhibits a total energy of −44.964 kcal∙mol⁻¹, while the α-helix has an energy of −26.0187 kcal∙mol⁻¹. This suggests that the β-sheet is the more stable configuration, as it demonstrates lower energy after optimization through geometry and molecular dynamics. Such thermodynamic properties, which favor the β-sheet, could provide a foundation for synthesizing this structure with catalytic capabilities akin to those of a molecular machine [[36]] (Figure 1).

Figure 1.Secondarystructureofglycine(MM+)oligomers(A)β-sheetandalpha-helix(B).

The simulation of oligomer secondary structures was conducted using calcite and acetonitrile. Results indicate that structures incorporating calcite exhibit an energy weakening pattern, with energy increasing from 1Gly to 4Gly and decreasing in 5Gly, suggesting a stabilization effect. Conversely, for calcite with acetonitrile, the dipole moment shows an increase from 1Gly to 4Gly but decreases at 5Gly, highlighting differences in behavior compared to amino acids on the surfaces of these substances. The semiempirical PM3 method was employed after the MM+ simulations, utilizing a single-point method to maintain atomic positions, as shown in Table 1, Table 2, and Table 3.

Table 1.ValuesobtainedfromcomputationalsimulationsshowingthepotentialenergyvaluesanddipolemomentsinMM+andPM3methodsforcontrolglycines.

Table 2.ValuesobtainedfromthecomputationalsimulationsshowingthedipoleenergiesanddipolemomentsinMM+andPM3methodswithCaCO₃.

Table 3.ValuesobtainedfromthecomputationalsimulationsshowingthedipoleenergiesandmomentsinMM+andPM3methodswithCaCO₃andCH₃CN.

*Energy calculation without readjusting the structural optimization.

In the simulations of oligomerizations, the formation of one water molecule per peptide bond is accounted for, resulting in the generation of five water molecules in the hexaglycine model (Figure 2).

Figure 2.MM+computationalsimulationoftheinteractionofhexaglycine,calcite,andacetonitrilewithfivewatermolecules.Thevaluesforthissimulationare6.26kcal∙mol⁻¹energyand5.315Debyesdipolemoment.

Figure 3 illustrates a rhombohedral exfoliated CaCO₃ crystal, featuring distinct crystalline planes that facilitate its interaction with irradiated glycines. The images highlight unpolarized regions within the oligomers (Figure 4), indicating the presence of high-molecular-mass compounds.

Figure 3.SamplesofIcelandsparsinglecrystalsatdifferentscales.(A)Icelandsparwiththenakedeye,withvisiblelinearfractures(B),(C).OpticalmicroscopyviewofIcelandsparsampleshowingthecharacteristicrhombohedralfractureofcalcite.

Figure 4 depicts glycine, characterized by rounded edges and opacity under polarized light (4A). In contrast, Figure 4(B) identifies calcite by its angular edges and clear diaphaneity in polarized light. The addition of glycine to the carbonate is evident in Figure 4(C), where the 1Gly mixture allows light to penetrate various areas, revealing the distinct identities of calcite and glycine. Figure 4(D) shows 6Gly, illustrating a more pronounced interaction, with observable glycine adhering to the calcite crystal surface.

Figure 4.Dehydratedsampleswereanalyzedunderpolarizedlightmicroscopy.(A)Glycine;(B)CaCO₃;(C)CaCO₃+Glycine;(D)CaCO₃+6Glycine.Intheimage,theglassslidecorrespondsto(PO),calciteto(CAL),andglycinesto(1GLY,6GLY).

For the experiment in Differential Scanning Calorimetry (DSC) without exposure to UV-C irradiation (Figure 5), glycine samples 1 through 5 displayed endothermic curves, whereas hexaglycine exhibited three exothermic peaks, indicating distinct thermal behaviors. The enthalpy changes represented in the thermograms correspond to the relaxation, formation, or breakdown of the compounds, with endothermic processes (positive ∆H values) and exothermic processes (negative values). The thermal transitions of glycine up to pentaglycine show a relatively consistent increase, whereas hexaglycine’s exotherms suggest the presence of a secondary structure within the oligomer. The thermal transitions for glycine samples with CaCO₃ are noted, with hexaglycine showing all three exothermic values again. Interestingly, samples with CaCO₃ and CH₃CN exhibited endothermic transitions at lower temperatures, indicating a significant loss of stability as the thermal transitions decreased from approximately 300˚C to around 100˚C. Multiple curves were recorded per analysis, and averages were used for improved data management.

Figure 5.Differentialscanningcalorimetryplotsofthedifferentglycinesamplesareshownincoloredcurves,from1Glyto6Gly,correspondingtotheiroligomers,whereArepresentstheglycinesamples,BrepresentsthosewithaddedCaCO₃,andCrepresentsthosewithaddedCH₃CNtosimulateamolecularevolutionprocess.

The graphical representations of enthalpy and transition temperatures reveal significant findings. In Figure 6(A), negative values indicate low energy requirements for reactions, with the highest enthalpy observed in the mixtures of Gly with 4Gly and 5Gly.Figure 6(B) shows that the lowest thermal temperature occurs at 2Gly, while the highest is at 6Gly. Overall, Gly exhibits the highest thermal transition temperature, whereas the mixture of Gly + CaCO₃ + CH₃CN presents the lowest transition temperature.

Figure 6.Behaviorofenthalpies(A)andthermaltransitions(B)inthedifferentsamples.Thechangesinenthalpyforthecontrolglycineandthedecreaseinthermaltransitions(lowertemperatures)arenoticeablewhencarbonateisadded,andthiseffectismorepronouncedwithacetonitrile(inB).Generallyspeaking,thethermaltransitionsaremorestablewithincreasingmolecularmass.

On the other hand, the experiments in Differential Scanning Calorimetry (DSC) with exposure to UV-C irradiation (Figure 7) demonstrated significant changes in the transition temperature distribution of samples containing CH₃CN when exposed to UV-C radiation. Without UV-C, the endothermic transitions occurred between approximately 95˚C and 100˚C; however, exposure shifted this range to approximately 240˚C to 320˚C, suggesting that radiation enhances the synthesis of these materials. Notably, the samples with 5Gly exhibited atypical endothermic and exothermic behavior post-UV-C exposure. Additionally, the CH₃CN samples exhibited a destabilization effect upon UV-C irradiation (Figure 8), suggesting that acetonitrile may compromise the structural integrity, which has implications for the chemical evolution processes in glycines and carbonates in environments such as Titan and Early Earth. The distinct thermograms obtained from UV-C-exposed samples further support the notion that UV-C radiation can catalyze organic reactions.

Figure 7.Differentialscanningcalorimetryplotsofthedifferentglycinesamplesareshownincoloredcurves,from1Glyto6Gly,accordingtotheiroligomers(A),withCaCO₃(B),andCH₃CN(C)afterexposuretoUV-Cradiationovertwo3-hourintervals.Thermaltransitionsareobservedatlowerandlowertemperatures.ForgraphC,aboxisshownwhereathermaltransitionoutsidetheexpectedvaluesisobserved,asitoccursatapproximately125˚C,indicatinginstabilityofthereactionwithacetonitrile.

Figure 8.Behavioroftheenthalpies(A)andthermaltransitions(B)ofthesamplesexposedtoUV-Cradiation.ContrarytothebehaviorshowninFigure 6,thevaluesofenthalpychangesareconsiderablyhigherwhenacetonitrileisadded.Likewise,itcanbeobservedthatthethermaltransitionsdonotexhibitanabruptchangebetweenthoseexposedtoradiationandthosenotexposed,indicatingthatstabilityismaintained.

The study results, as determined by Fourier-Transform Infrared Spectroscopy (FTIR), are supported by Narayana Moolya etal. (2005), who identified various chemical groups in the samples, revealing the presence of new compounds following UV-C irradiation. Furthermore, infrared spectrogram analysis demonstrated a consistent increase in bands between 1700 cm⁻¹ and 1500 cm⁻¹, corresponding to amides I and II, indicating the oligomerization of amino acids in both control and irradiated samples. Additionally, a comparative analysis of the spectra revealed a significant increase in intensity, indicating higher molecular diversity in irradiated samples (Figure 9). The most important spectral bands were attributed to glycine in conjunction with calcium carbonate and acetonitrile.

Figure 9.FTIRspectraofcontrolandUV-C-irradiatedsamples.(A)Controlglycines.(B)Irradiatedglycins.(C)Controlcalciumcarbonateglycines.(D)Irradiatedcalciumcarbonateglycins.(E)Controlcalciumcarbonateandacetonitrileglycines.(F)Irradiatedcalciumcarbonateandacetonitrileglycines.

For this study, those compounds in the bands 3330 cm⁻¹ and 1700 - 1500 cm⁻¹ based on the absorption rate denoted in the band yielded by FTIR (Chandrajith & Marapana, 2018) are considered as the central vibrational frequency: 3300 - 3200 cm⁻¹ (indicate the O-H bond); 3000 - 2900 cm⁻¹ (correspond to C-H bonds); 1700 cm⁻¹ (attributed to C=O bonds); 1100 - 1000 cm⁻¹ (assign C-O bonds).

We could correlate the bands obtained for 5 Gly and 6 Gly (more stable) with the presence of the following compounds (Barth, 2007): 5 Gly [Band 1605 cm⁻¹] for arginine, lysine, aspartic acid [deprotonated], phenylalanine; 5 Gly [Band 1500 cm⁻¹] for alanine, lysine [crystalline state or salts], phenylalanine; 6 Gly [Band 1665 cm⁻¹] for Alanine and Proline [leaves], tryptophan, alanine and Proline [β-sheets], aspartic acid [salts]. These assignments are based on spectral similarities between the observed bands and characteristic vibrational modes reported for these amino acids.

It is crucial to consider the possible presence of lipids, as they, like proteins, are precursors to protein membranes. To find lipid bands in the FTIR results, we used the second derivative of the spectrogram of the samples with carbonate and acetonitrile once they had been subjected to UV-C radiation to identify the lipid bands present in the spectrum, as we had seen previously, which were identified in 3330 cm⁻¹ for C-H vibrations, 1700 cm⁻¹ to C=O bonds and 1000 cm⁻¹ for C-O bonds. The evidence of this change between non-irradiated and irradiated samples is shown in Figure 10, where the second derivatives demonstrate the intervals in the lipid bands. We can see a significant diversity of bands once irradiation is introduced.

Figure 10.Spectraofsampleswithcarbonateandacetonitrilewithoutirradiation(A)andwithirradiation(C),andtheircorrespondingsecondderivative.Incontrast,thesecondderivativeofnon-irradiatedsamples(B)showslessbanddiversitythanthesecondderivativewithradiation.