{"paper_id":"acac2a06-b580-4cab-8fae-843770a87b16","body_text":"Secondary conformation of MERS-CoV, SARS-CoV and SARS-CoV-2 Spike Proteins revealed by Infrared Vibrational Spectroscopy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Secondary conformation of MERS-CoV, SARS-CoV and SARS-CoV-2 Spike Proteins revealed by Infrared Vibrational Spectroscopy Annalisa D'Arco, Marta Di Fabrizio, Tiziana Mancini, Rosanna Mosetti, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2245843/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract All coronaviruses are characterized by spike glycoproteins whose S1 subunit contains the receptor binding domain anchoring the virus to the host cellular membrane and regulating virus transmissibility and infectious process. Although the protein/receptor interaction depends on the spike secondary-conformation, in particular to its S1 unit, few is known about the secondary-structure of different coronaviruses. In this paper the S1 conformation is investigated for MERS-CoV, SARS-CoV and SARS-CoV-2 in serological condition, by measuring their Amide I infrared vibrational absorption bands. The SARS-CoV-2 secondary structure reveals a strong difference in comparison to MERS-CoV and SARS-CoV ones, with a higher amount of intermolecular β-sheet content. Moreover, the conformation of SARS-CoV-2 S1 shows a significant change by moving from serological pH and mild acidic to alkaline pH conditions close to the bat ecological niche. Both results suggest a huge capability of SARS-CoV-2 S1 glycoprotein to adapt its secondary structure to different environments. Biological sciences/Biophysics/Molecular biophysics Health sciences/Biomarkers/Diagnostic markers Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The global emergency, due to COVID-19 pandemic, poses a grave threat to public health, security and economy, imposing a severe burden on our society ( 1 , 2 ). The virus responsible for COVID-19 disease is a new member of the Coronaviridae family, SARS-CoV-2 ( 2 – 4 ). Like SARS-CoV-2, other two coronaviruses (CoVs) are known to cause deadly pneumonia. These are severe acute respiratory syndrome coronavirus (SARS-CoV) ( 5 , 6 ) and Middle East respiratory syndrome coronavirus (MERS-CoV) ( 7 ) that determined the previous pandemics occurred in 2002 and 2012, respectively ( 8 , 9 ). These viruses have different transmissibility, hospitalization and case fatality rates. SARS-CoV-2 is less deadly than SARS-CoV and, in particular of MERS-CoV, and it is considered the third highly infective CoV ( 2 , 3 ). However, a nodal point of any pandemic is the viral transmissibility, quantified by the virus reproductive rate parameter R 0 ; if R 0 is greater than 1, the pandemic is assumed to be in a growing phase. For SARS-CoV-2, R 0 in the early months of pandemic has been estimated between 2 and 5 ( 1 , 10 ), when the containment measures were not introduced, yet ( 11 – 13 ). This value is higher than those of SARS-CoV ( 2 – 3 ) ( 14 , 15 ) and MERS-CoV (0.9) ( 10 ). CoVs are spherical viruses, with diameters ranging between 60–150 nm, as shown by Cryo-electron tomography and microscopy studies ( 16 , 17 ). They contain a non-segmented positive-sense RNA (+ ssRNA), which acts as an mRNA for translation of the replicase polyproteins, encoding the genetic content accessory and structural proteins, such as Spike (S) glycoproteins. Spike is a I-th class fusion protein ( 18 ) protruding from the surface of mature virions (see Fig. 1 A). and plays a crucial role both in infection process ( 19 ) and viral pathogenesis ( 20 , 21 ), including the virus released to various human host cells. Mature S glycoproteins weigh about 150 kDa and are synthetized in terms of 1300 amino acids polypeptide chains, which associate as heavily glycosylated trimers (see Fig. 1 B). Each S protein is composed by two subunits (S1 and S2). The surface S1 subunit contains an N-terminal domain (NTD) and the receptor binding domain (RBD). Here, the receptor binding motif (RBM) part is responsible for anchoring the host cellular membrane through its receptors ( 21 , 22 ). Therefore, S-protein/cellular-receptor interaction is the primary factor regulating the infectious process. Following receptor binding, viruses gain entry inside the host human cell cytosol. This process is mediated by the membrane fusion S2 unit, which matches host and viral membranes. Another structural feature of S proteins is their extensive glycosylation ( 23 – 26 ). The CoV S glycoproteins are densely decorated by heterogeneous N-linked glycans, that are used by viral fusion proteins as a shield to counteract the host immune response ( 23 , 27 – 33 ), participating in the S folding ( 34 – 36 ) and working as recognition sites ( 37 ). The transmissibility and pathogenicity of viruses are determined by both viral and host factors, such as the combination of immune evasion, the conformational masking of binding domains and glycan shielding, and the extent of the human receptor binding affinity and specificity. As all CoVs present S glycoproteins, their different peculiarities, such as transmissibility, could be related to different secondary S protein conformation ( 2 , 3 , 20 ). In addition, the efficient viral propagation within a biological host and/or ecological niche is also mediated by the pH. The pH could affect the S protein secondary conformation, inducing a refolding of the viral proteins, modulating the virus entry and engaging the hACE2 receptor. High pH values could result in viral protein inactivation, as it happens in the multifunctional hemagglutinin protein of the influenza virus ( 38 , 39 ). In light of the relevant role of the S protein and in particular of its S1 unit, is absolutely mandatory to investigate its secondary conformation in serological condition in different families of CoVs and also to study the secondary conformation stability as a function of pH. In this manuscript, we perform for the first time, at the best of our knowledge, a comparative infrared spectroscopic study of S1 unit glycoproteins of MERS-CoV, SARS-CoV and SARS-CoV-2, with the purpose of investigating their complex secondary structure in serological ambient. In particular, the secondary structure of MERS-CoV, SARS-CoV and SARS-CoV-2 S1 units has been determined through a spectral component analysis of the protein Amide I vibrational band ( 40 – 44 ). Through these measurements, we experimentally demonstrate that the three S1 glycoproteins have different secondary conformations. Notably, SARS-CoV-2 glycoprotein S1 unit reveals a strong difference in conformational secondary structure in comparison to the MERS-CoV and SARS-CoV ones, having a higher amount of intermolecular β-sheet structure. This difference indicates that the binding of the virus to the human receptor is correlated to the spike protein secondary conformation ( 45 , 46 ). We have also observed strong changes in the conformation of SARS-CoV-2 S1 unit by moving from neutral pH, which characterize the human serological environment, to endosomal pHs (mildly acidic) and finally to alkaline environments characterizing the ecological niche of bats. These results indicate a huge capability of SARS-CoV-2 S1 glycoprotein to rapidly adapt its secondary structure to different environments facilitating virus transmissibility, demonstrating that infrared vibrational spectroscopy is a valuable tool for the investigation of spike secondary conformation structure, and for identifying different coronavirus families. Results Amide I: Protein secondary structure Figure 2 shows the absorbances A(ω) vs. frequency (ω) of the S1 glycoprotein of MERS-CoV ( B ), SARS-CoV ( C ) and SARS-CoV-2 ( D ) in the Amide I band, between 1580 and 1750 cm − 1 , measured at pH 7.4 and at a concentration of 0.25 mg/ml. Similar data have been obtained for other concentrations (see Fig. S1 in supporting information). A first qualitative comparison can be made looking at Fig. 2 A, where the absorption spectra of the three S1 proteins are shown. While MERS-CoV (blue line) and SARS-CoV (red line) show a quite similar broad absorption band centered at about 1660 cm − 1 , in SARS-CoV-2 (yellow line) the band has a maximum around 1650 cm − 1 . This red-shift can be further quantified by calculating the differences A(ω) (SARS−CoV−2) -A(ω) (MERS−CoV) , and A(ω) (SARS−CoV−2) -A(ω) (SARS−CoV) (blue and red line in the inset of Fig. 2 A, respectively) and comparing them with the reproducibility of the A(ω) (SARS−CoV−2) absorption measurements. The reproducibility has been estimated by the difference A(ω) (SARS−CoV−2) -A(ω) (SARS−CoV−2) for two different measurement runs (yellow line in inset of Fig. 2 A). The SARS-CoV-2 absorption reproducibility fluctuates less than 2% in the whole Amide I spectral range. Instead, a sizeable difference (actually far out of the reproducibility of absorption spectra), can be observed when comparing SARS-CoV-2 with MERS-CoV and SARS-CoV absorptions. In particular, for both MERS-CoV and SARS-CoV there is an absorption reduction between 1600–1650 cm − 1 (in agreement with the main panel of Fig. 2 A), and a smaller enhancement at higher frequency. In order to identify the secondary structure for MERS-CoV, SARS-CoV and SARS-CoV-2, a global fitting approach ( 40 – 42 , 47 ) have been used for deconvoluting in Gaussian spectral components the Amide I band. The total fit (empty circles), and the spectral decomposition (colored Gaussians), of MERS-CoV, SARS-CoV and SARS-CoV-2 Amide I band (black lines), are reported in Fig. 2 B, C and D , respectively. The area of each component can be used to estimate the secondary structure content of the S1 protein. Table 1 summarizes the vibrational frequencies of the different Gaussian-components and their relative intensities, together with their assignment to specific secondary conformation structures ( 40 , 44 , 47 – 49 ). In particular, we notice in all A(ω) an intense peak around 1658 cm − 1 , associated with the α-helix structure ( 40,47–49 ). The β-sheet components are instead observed between 1620–1640 cm − 1 and around 1690 cm − 1 ( 49 ). In particular, the bands near 1630 cm − 1 and 1690 cm − 1 are typically related to an antiparallel arrangement of the β-sheet. The bands in the 1665–1690 cm − 1 range can be assigned instead to the β-turn structure. The broad absorption band centered at 1643 cm − 1 corresponds to random coils. The absorption band at 1619 cm − 1 , present only in SARS-CoV-2 S1 unit, is finally assigned to side chains and intermolecular anti-parallel β-sheets ( 40,44,47–49 ). The actual secondary structure of S1 unit in MERS-CoV, SARS-CoV and SARS-CoV-2 viruses at pH 7.4 can be estimated through the ratios among the intensity of each component of the Amide I band over the total intensity (also reported in Table 1 ) as obtained by the previously mentioned fitting procedure. From these data, one can observe that SARS-CoV and SARS-CoV-2 show similar α-helix (27.7% and 29.4%) and random coil contents (13.5% and 12.3%). The larger difference in the secondary structures of the S1 proteins can be instead observed in the arrangement of β-sheet and β-turn. Notably, a significant increase is revealed in the β-sheets content passing from MERS-CoV (20.6%) to SARS-CoV (26.8%) and SARS-CoV-2 (30.6%). This is mainly due to the strong increase of the antiparallel β-sheet structure observed at 1619 cm − 1 for the SARS-CoV-2 S1 unit, which corresponds to nearly 5% of the total protein secondary structures. An opposite trend is shown by the β-turn (1665–1687 cm − 1 ): MERS-CoV and SARS-CoV S1 proteins exhibit approximatively the same β-turn content (30.6 and 32 ), compared to ~ 28 of the SARS-CoV-2 S1 unit. Observing the results concerning MERS-CoV and SARS-CoV S1 proteins, we notice a similarity in the secondary conformational structure (α-helix and β-turn), attributable to the aminoacid sequence identity of their S1 unit ( 3 , 50 ). Instead, although both SARS-CoV-2 and SARS-CoV S1 proteins interact with the human hACE2 receptor and show a sequence similarity (between 73–75 ) as determined by Cryo-EM ( 3 ), they exhibit, on the basis of our vibrational absorption measurements, a robust secondary conformation difference. Table 1 Secondary structure assignment for MERS-CoV, SARS-CoV and SARS-CoV-2 S1 units derived from the Gaussian decomposition of the absorption spectra . For each S1-protein, we show (first column) the characteristic absorption frequency and (second column) the peak relative intensity. In the third column the observed absorption peaks are assigned to specific secondary conformations ( 40 , 49 ). MERS-CoV peaks [cm − 1 ] MERS-CoV peak relative intensity [%] SARS-CoV peaks [cm − 1 ] SARS-CoV peak relative intensity [%] SARS-CoV-2 peaks [cm − 1 ] SARS-CoV-2 peak relative intensity [%] Assignment - - - - 1619 5.2 β-sheet (intermolecular) 1628 14.0 1625 7.9 1628 11.4 β-sheet 1632 2.4 1633 12.7 1633 9.8 β-sheet 1641 16.5 1642 13.5 1643 12.3 Random coils 1650 13.7 1650 12.9 1650 13.6 α-helix 1658 18.6 1658 14.9 1658 15.9 α-helix 1666 10.6 1666 12.2 1666 5.6 β-turn 1673 8.3 - - 1673 6.7 β-turn - - 1675 10.4 - - β-turn 1680 11.8 1681 9.3 1678 15.2 β-turn 1693 4.2 1690 6.1 1693 4.2 β-sheet Being the receptor-protein recognition conformation-dependent, the observed differences can be related to their differential receptor-binding affinities. Indeed, recent Cryo-EM and computational studies have shed light on this behavior ( 19 , 51 – 54 ), investigating the binding affinity of the RBD sites for the hACE2-peptidase domain. Experimentally, Wrapp et al. ( 54 ) and Tai et al. ( 19 ) have reported that the SARS-CoV-2 RBD has a higher binding affinity for hACE2-peptidase domain than the SARS-CoV RBD. Amide I: Changes In Secondary Structure Induced By Ph Variation The pH-dependent conformation changes in proteins play a key role in virus replication, pathogenesis, and transmissibility. In particular, the local-environment pH can strongly influence the protonation state in folded proteins by promoting changes in interchain interactions. Consequently, the stability of proteins is pH-dependent, favoring conformational flexibility, protein activation and/or inactivation. In this framework, we have studied the secondary conformation of SARS-CoV-2 S1 protein at different pH values (pH = 4.55, 5.5, 7.4, 8.8 and 11.2), by measuring the absorbance A(ω) of the Amide I band (Fig. 3 A). The absorption behavior vs. pH is not monotonic; while SARS-CoV-2 S1 at serological (yellow line) and 8.8 (purple line) pH values show a similar broad absorption band centered at about 1650 cm − 1 , the spectra relative to mild low pHs (blue line at 4.55 pH, and red line at 5.5 pH) and alkaline pH (green line at 11.2 pH) are red-shifted of about 10 cm − 1 and exhibit a maximum around 1640 cm − 1 . This red-shifting can be further observed in Fig. 3 B, where the calculated absorption differences A(ω) (pH 7.4) -A(ω) (pH x) , are compared with the reproducibility of A(ω) (pH 7.4) . This last quantity has been estimated by the difference A(ω) (pH=7.4) -A(ω) (pH=7.4) for two different measurement runs (yellow line in Fig. 3 B). Let us notice that a similar reproducibility can be observed at any pH. The absorption reproducibility fluctuates less than 2% in the whole Amide I spectral range. Significant differences, actually far out the reproducibility, emerge when the pH moves from mild low values to alkaline ones. Indeed, an absorption frequency redistribution is observed around an isosbestic point at about 1647 ± 1 cm − 1 . As the S1 protein concentration and all physical parameters, e.g., temperature, pressure and relative humidity, are kept constant during experiments, the occurrence of the isosbestic point can be associated to the conformational changes in the protein structure induced by the pH. The influence of pH on the S1 protein conformation can be quantified by studying the change in peak position and intensity of the spectral components of the Amide I band through a global Gaussian fitting. The global fit (empty circles), and the spectral decomposition (colored Gaussians), of the Amide I band for different pHs (4.55, 5.5, 8.8 and 11.2), are compared in Fig. 3 C, D, E and F , respectively. Absorption at pH = 7.4 has been already reported in Fig. 2 D. The area of each spectral component has been used to estimate the secondary structure content and then its variation with pH. In Table S1 , the peak frequencies for the Amide I S1 protein vs. pH and associated to specific secondary conformation structures are shown while their intensities vs. pH are represented in Fig. 4 which will be discussed in the following ( 40 , 44 , 47 , 49 , 55 ). The main effect of pH concerns, firstly, the α-structure (see Table S1 in supporting information), which give rise to a main absorption band at 1658 cm − 1 and to a shoulder at lower frequencies around 1650 cm − 1 at 7.4 pH. While the main α-structure component remains nearly constant in frequency (1658–1659 cm − 1 ) for pH moving from 7.4 to 5.5, this band shifts near to 1663 cm − 1 at pH = 4.55 and at alkaline levels. Usually, a blue-shift is associated to the formation of a short α-helix. Moreover, for acid pHs, the whole α-helix absorption reduces its intensity of about 50% (see Fig. 4 ). The band at 1643 cm − 1 for 7.4 pH associated to random coils, is also influenced by pH variation, blue-shifting to 1646 cm − 1 for acid and alkaline pHs. Its intensity is maximized at pH = 5.5 (see Fig. 4 ). The intermolecular β-sheet located around 1619 cm − 1 at serological and alkaline pHs, instead red-shifts for acid conditions. The other β-sheet components are located between 1620–1640 cm − 1 and around 1690 cm − 1 (see Table S1 in supporting information) ( 44 ) at pH = 7.4. The band at 1629 is red-shifted at 1628 cm − 1 at acid pH levels suggesting the aggregation of sheets with a large number of strands ( 40 , 49 ), and blue-shifted at 1633 cm − 1 for alkaline pHs. The absorption of β-sheet for pH = 4.55, 5.5 and 11.2 pH is related to a new band at 1637 cm − 1 . Finally, the absorption at 1693 cm − 1 disappears for extreme pH values. From Table S1, the total intensity of β-sheet presents a minimum at serological pH, being maximized at acid pHs. The bands in 1666–1678 cm − 1 range, assigned to β-turn structures ( 40, 44, 47,49, 55 ) are blue-shifted compared to their spectral positions at 7.4 pH, while a new band appears at 1686 cm − 1 for pH values of 4.55, 8.8 and 11.2. The total intensity of β-turn structures, which shows a maximum at pH = 7.4 reduces both at acid and alkaline pHs. For a quantitative evaluation of secondary conformation changes, we show in Fig. 4 the ratio between the secondary structure peak areas and the total area vs. pH. At the serological pH 7.4, the α-helix and β-turn structures show their maxima, reducing their intensity both in acid and alkaline conditions. Conversely, the random coil and the β-sheet present an opposite behavior with minima at pH 7.4 while increasing towards the acid and alkaline pH values. Moving from serological to alkaline environment, at pH 8.8 the contents of random coil and α-helix are almost unchanged, differently from β-sheet and β-turn structures which increase and decrease, respectively. Thus, a slight unfolding of β-structures appears at pH 8.8, that is the typical environmental pH observed in bat caves where high ammonia concentrations build up. Moreover, at pH 11.2 the decrease of the β-turn content by an average of ~ 10% and the increase of β-sheet structure of 12% are observed. This behavior suggests a transition from β-turn the to the β-sheet structure in the strong alkaline medium (pH = 11.2), while a slight rearrangement of the α-structure is observed under mild alkaline conditions. This is also consistent with a loss of secondary structure, perhaps due to a partial protein unfolding. The reduction of the β-turn content is also observed for acidic pHs. In addition, the β-sheet content increases from its value at 7.4 pH (~ 30.6%) moving from neutral to mild low pH at 47% of all Amide I band. The content of side chains and intermolecular β-sheets (~ 1619 cm − 1 ), associated to a low frequency band, exhibits a pH-dependent behavior, with a maximum value of ~ 19% at 5.5 pH, to be compared with the serological value (5%). The strong changes of the protein secondary conformation at pH 5.5 is associated with the rearrangement and modification of the RBD sites. Some investigations have shown that several regions of the SARS-CoV-2 S protein are susceptible to mutations, with the RBD site particularly vulnerable to a conformational change ( 56 , 57 ). The RBD undergoes indeed a hinge-like movement that brings up or down the specific amino-acid sequence responsible for the binding to the hACE2 receptor ( 54 ) inducing a change in the secondary conformation. In our work, we observe a large variation of intermolecular β-sheets content for the SARS-CoV-2 S1 vs. pH (see Fig. 4 ), with a maximum value at pH = 5.5 (nearly 20%). This behavior can be related to a structural transition from a closed over a locked form of S1 as pH is increased from mild acidic to neutral as observed by Cryo-EM microscopy studies ( 58 , 59 ), with an optimal condition for the pre-fusion configuration at pH 5.5. The overall strong conformational changes of SARS-CoV-2 S1 unit vs. pH by passing from the alkaline ones, characteristic of the ecological niche bats ambient, to the human serological environment, suggests a high capability of S1 SARS-CoV-2 glycoprotein to adapt to different environments, further indicating the existence of a correlation between the S1 protein secondary conformation and the virus transmissibility. Discussion In this manuscript we investigate the secondary conformation structure of the S1 sub-unit spike-protein, which is responsible for anchoring coronaviruses to the human cellular membrane through infrared vibrational spectroscopy. In particular, the secondary S1 structures of MERS-CoV, SARS-CoV and SARS-CoV-2 have been characterized through infrared spectroscopy by measuring their Amide I vibrational band. Experimental data point out that the three S1 glycoproteins have different secondary conformations. Notably, SARS-CoV-2 glycoprotein S1 unit, at variance with MERS-CoV and SARS-CoV, presents a larger amount of intermolecular β-sheet structures, which indicates a more stable protein structure. Similarly, we have also observed large changes in the conformation of the SARS-CoV-2 S1 unit by moving from human serological pH to alkaline pH conditions characterizing the typical ecological niche of bats. The whole results indicate, from one side that infrared vibrational spectroscopy provides virologists with rapid and insightful information on secondary conformation of all coronavirus family establishing similarity and differences. From the other side, our data indicates the huge capability of the SARS-CoV-2 S glycoprotein to adapt to a variable environment, pointing out the strong role of the S1 protein secondary conformation in the virus transmissibility. Materials And Methods Protein preparation Recombinant S1 proteins, fused with a polyhistidine tag at the C terminus of MERS-CoV (Cat. 40069-V08B1), SARS-CoV (Cat. 40150-V08B1) and SARS-CoV-2 (Cat. 40591- V08B1) were purchased from Sino Biological Europe GmbH. They are expressed in baculovirus insect cells with the same purity > 90% as determined by Sodium Dodecyl Sulphate - PolyAcrylamide Gel Electrophoresis (SDS-PAGE), and finally used without further purification. This work was carried out on a dataset of S proteins collected in late spring 2020, and as regards SARS-CoV-2, we refer to the alpha variant that affected Europe and Italy in the pandemic crisis of March 2020. The lyophilized proteins were reconstructed dissolving 100 µg in distilled water (400 µl) at pH 7.4 (0.25 mg/ml concentration). The samples for the pH-dependent study of SARS-CoV-2 S1 subunit were prepared as follows. Briefly, in order to adjust the pH of proteins NaOH or HCl aqueous solutions at molar concentrations of 10 − 2 and 10 − 4 M were used. The solution has been gently shaken waiting for the state of equilibrium of the reaction, monitoring its pH with a pH-meter from DOSTMANN pH 80 + DHS. We prepared two samples of acidic S1 protein solutions at pH 4.55 and 5.5, and two in alkaline environments, having pH 8.8 and 11.2. Attenuated-total-reflection Infrared Spectroscopy And Data Analysis Attenuated Total Reflection (ATR) infrared spectra of the Spike glycoproteins S1-unit of MERS-CoV, SARS-CoV and SARS-CoV-2 were collected using a Bruker Vertex 70v Michelson spectrometer equipped with an ATR–Diamond module Harrick MVP-Pro and a DLaTGS wide range detector. Spectroscopic measurements were carried out at room temperature and with the interferometer under vacuum in order to eliminate water-vapor and CO2 absorptions. The background spectrum (buffer solution) was collected immediately prior to each sample measurement. Five microliters of the sample solution were placed directly on the diamond crystal and 64 scans between 400–4000 cm − 1 with a resolution of 2 cm-1 were acquired. Each spectrum is the average of six independent measurements. The ATR crystal was cleaned with ethanol (add purity) and subsequently with a lens tissue, in order to eliminate any spurious signal. Raw data have been processed and analyzed using OPUS 8.2 (Bruker Optics) and in-house algorithms based on MATLAB (ver. 2018, MathWorks Inc., USA). To obtain the protein absorption spectra A(ω), shown in Fig. 2 , we subtracted the buffer spectrum (see supplementary information for details) to eliminate the contribution of the background ( 47 , 48 ) and applied the ATR correction algorithm and a piecewise baseline subtraction. The secondary conformation of glycoprotein S1 unit is obtained by the decomposition of the Amide I vibrational absorption band ( 41 , 44 ) into its spectral components through the 2nd-derivative procedure ( 48 ) combined with a multicomponent Gaussian fitting. In particular, the frequencies, achieved by 2nd-derivative spectra, were used as starting points for Gaussian curve fitting and the residual error (RMSE) was employed for assessing the convolution procedure performance. The intensity of each component peak normalized to the total intensity was used to calculate the percentage of each absorption band and then to estimate the secondary conformation of the S1 unit spike protein ( 55 , 60 ). Declarations Data availability All data are available in the main text or the supplementary materials. Acknowledgments We thank NATO SPS for providing the opportunity and for supporting the development of SARS 3M project. We are also deeply grateful to all healthcare workers and beyond fighting COVID-19 to ensure community safety and health. Funding: This work was funded by the NATO Science for Peace and Security Programme under grant No. 5889 “SARS-CoV-2 Multi-Messenger Monitoring for Occupational Health & Safety (SARS 3M)”, by MIUR – Fondo speciale per la Ricerca - FISR 2020 COVID project titled “Multi-Messenger and Machine Learning Monitoring of SARS-CoV-2 for occupational health & safety (4M SARS-CoV-2)” and LazioInnova “Gruppi di Ricerca 2020” of the POR FESR 2014/2020—A0375-2020-36651 project entitled “DEUPAS -DEterminazione Ultrasensibile di agenti PAtogeni mediante Spettroscopia”. Financial support by the Grant to Department of Science, Roma Tre University (MIUR-Italy Dipartimenti di Eccellenza, ARTICOLO 1, COMMI 314-337 LEGGE 232/2016) is gratefully acknowledged. Author contributions Each author’s contribution(s) to the paper should be listed. Conceptualization: AD, SL; Methodology: AD, MDF, SL; Investigation: AD, MDF, TM, RM, SM; Formal Analysis: AD, MDF, RM; Data interpretation: AD, LS, MDF, GT; Visualization: AD, MDF, TM, RM, SM; Supervision: SL, AM, MP, GT, GDV; Funding acquisition: SL, AM, GDV, MP, GT; Writing—original draft: AD, SL; Writing—review & editing: AD, MDF, TM, RM, SM, MP, AM, GDV, GT, SL. All authors have read and agreed to the published version of the manuscript. Competing interests Authors declare that they have no competing interests. Supplementary Materials The online version contains supplementary material available at … References Li, Q. et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. N. Engl. J. Med . 382 , 1199-207 (2020). Huang, C. et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 395 (10223) , 497-506 (2020). Huang, Y., Yang, C., Xu, X.-F., Xu, W., Liu, S.-W. 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Evolutionary and structural analyses of SARS-CoV-2 D614G spike protein mutation now documented worldwide. Sci. Rep . 10(1) , 14031 (2020). Zhou, T. et al. Cryo-EM Structures of SARS-CoV-2 Spike without and with ACE2 Reveal a pH-Dependent Switch to Mediate Endosomal Positioning of Receptor-Binding Domains. Cell Host Microbe 28(6) , 867–879.e5 (2020). Shivu, B., Seshadri, S., Oberg, J. Li, K. A., Uversky, V. N., Fink, A. L. Distinct β-Sheet Structure in Protein Aggregates Determined by ATR–FTIR Spectroscopy. Biochemistry 52(31) , 5176-5183 (2013). Veesler, D. et al. Production and biophysical characterization of the CorA transporter from Methanosarcina mazei. Anal. Biochem . 388 (1), 115–121 (2009). Tables Table 1. Secondary structure assignment for MERS-CoV, SARS-CoV and SARS-CoV-2 S1 units derived from the Gaussian decomposition of the absorption spectra . For each S1-protein, we show (first column) the characteristic absorption frequency and (second column) the peak relative intensity. In the third column the observed absorption peaks are assigned to specific secondary conformations ( 40,49 ). MERS-CoV peaks [cm -1 ] MERS-CoV peak relative intensity [%] SARS-CoV peaks [cm -1 ] SARS-CoV peak relative intensity [%] SARS-CoV-2 peaks [cm -1 ] SARS-CoV-2 peak relative intensity [%] Assignment - - - - 1619 5.2 β-sheet (intermolecular) 1628 14.0 1625 7.9 1628 11.4 β-sheet 1632 2.4 1633 12.7 1633 9.8 β-sheet 1641 16.5 1642 13.5 1643 12.3 Random coils 1650 13.7 1650 12.9 1650 13.6 α-helix 1658 18.6 1658 14.9 1658 15.9 α -helix 1666 10.6 1666 12.2 1666 5.6 β-turn 1673 8.3 - - 1673 6.7 β-turn - - 1675 10.4 - - β-turn 1680 11.8 1681 9.3 1678 15.2 β-turn 1693 4.2 1690 6.1 1693 4.2 β-sheet Additional Declarations There is NO Competing Interest. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-2245843\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":154570166,\"identity\":\"7f9fb415-71f2-408c-a99c-c4f713969657\",\"order_by\":0,\"name\":\"Annalisa D'Arco\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"INFN - Laboratori Nazionali di Frascati\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Annalisa\",\"middleName\":\"\",\"lastName\":\"D'Arco\",\"suffix\":\"\"},{\"id\":154570167,\"identity\":\"d87e75c0-de27-4244-9a12-2817cfdc9a4c\",\"order_by\":1,\"name\":\"Marta Di Fabrizio\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratory of Biological Electron Microscopy, IPHYS, SB, EPFL \\u0026 Department of Fundamental Microbiology, Faculty of Biology and Medicine, UNIL\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Marta\",\"middleName\":\"Di\",\"lastName\":\"Fabrizio\",\"suffix\":\"\"},{\"id\":154570168,\"identity\":\"4843e4c5-54ce-4cc2-96d0-da305883c865\",\"order_by\":2,\"name\":\"Tiziana Mancini\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Rome La Sapienza\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Tiziana\",\"middleName\":\"\",\"lastName\":\"Mancini\",\"suffix\":\"\"},{\"id\":154570169,\"identity\":\"703e6ab4-a5ba-4d92-9fa9-a954bcf4fd4a\",\"order_by\":3,\"name\":\"Rosanna Mosetti\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0001-6768-3967\",\"institution\":\"University of Rome La Sapienza\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Rosanna\",\"middleName\":\"\",\"lastName\":\"Mosetti\",\"suffix\":\"\"},{\"id\":154570170,\"identity\":\"4c3b3257-939d-4c34-ad81-b94bcca9cce1\",\"order_by\":4,\"name\":\"Salvatore Macis\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Department of Physics, Sapienza University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Salvatore\",\"middleName\":\"\",\"lastName\":\"Macis\",\"suffix\":\"\"},{\"id\":154570171,\"identity\":\"0f20a365-aaa0-47e1-91d4-6f67132b8940\",\"order_by\":5,\"name\":\"Giovanna Tranfo\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"INAIL\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Giovanna\",\"middleName\":\"\",\"lastName\":\"Tranfo\",\"suffix\":\"\"},{\"id\":154570172,\"identity\":\"3561002b-10b4-473c-86b4-24a930078993\",\"order_by\":6,\"name\":\"Giancarlo Della Ventura\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0001-6277-961X\",\"institution\":\"Università di Roma Tre\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Giancarlo\",\"middleName\":\"Della\",\"lastName\":\"Ventura\",\"suffix\":\"\"},{\"id\":154570173,\"identity\":\"f2923bef-7c30-4dfe-a39d-3e4084c592ca\",\"order_by\":7,\"name\":\"Augusto Marcelli\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0002-8138-7547\",\"institution\":\"INFN - Laboratori Nazionali di Frascati\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Augusto\",\"middleName\":\"\",\"lastName\":\"Marcelli\",\"suffix\":\"\"},{\"id\":154570174,\"identity\":\"1959ca29-e9db-4125-a20e-3345a92590dd\",\"order_by\":8,\"name\":\"Massimo Petrarca\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0001-9508-6801\",\"institution\":\"Universita Sapienza\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Massimo\",\"middleName\":\"\",\"lastName\":\"Petrarca\",\"suffix\":\"\"},{\"id\":154570175,\"identity\":\"6fe60c8a-0922-4997-b26e-962383bb88e9\",\"order_by\":9,\"name\":\"Stefano Lupi\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIie2OsU7DMBCGz6rkLm6zsrR5hTDRwTwJi1k8xYhHcGQpE+yZ2ldotw4Mjk7KhMQLdChLN1ARSxmQsBNAHWqVEan+ZJ9/WffpDiAS+adsfRm6a9vUcwE4AA31UyBV9wLUbep7RbqfkLOv9JhPiS8SgmPSman1x5IDPVM1Xj7wq8QAwVuxgmGqDypZQ6+L+0fplBuB+UaqCgGwEpvgYhllF+tBiU7JM8wtKu2VwQ6DSlomb8XnjzJxyswrTIQVaBgxv1PAKfNjStbIczMqJaPsVdR3VqoFEu0VRqk4vJjB5+Kl5OOkr3C7s1xNnxDfnTJOjQ1s1sHa00H0989R/tITiUQiJ8kXcIha4nhre9IAAAAASUVORK5CYII=\",\"orcid\":\"https://orcid.org/0000-0001-7002-337X\",\"institution\":\"CNR-IOM and Dipartimento di Fisica, Sapienza Universit\\\\`a di Roma, P.le Aldo Moro 2, I-00185 Roma, Italy\",\"correspondingAuthor\":true,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Stefano\",\"middleName\":\"\",\"lastName\":\"Lupi\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2022-11-07 08:11:18\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-2245843/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-2245843/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":29687321,\"identity\":\"24ba6f84-8694-4d6f-8d11-d83f8e4890b5\",\"added_by\":\"auto\",\"created_at\":\"2022-11-29 23:03:00\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":343365,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eThe SARS-CoV-2 virion structure.\\u003c/strong\\u003e (\\u003cstrong\\u003eA\\u003c/strong\\u003e) Model of the SARS-CoV-2 virion and schematic diagram of its structural proteins and genome. (\\u003cstrong\\u003eB\\u003c/strong\\u003e) Detail of the S glycoprotein and its subunits S1 and S2. (\\u003cstrong\\u003eC\\u003c/strong\\u003e) Further detail of the S1 subunit, object of this experimental study.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2245843/v1/60ff9d667a95ed050290e167.png\"},{\"id\":29687326,\"identity\":\"9c97219c-4aed-4d51-a304-b32826b346a6\",\"added_by\":\"auto\",\"created_at\":\"2022-11-29 23:03:00\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":580478,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eComparison of Amide I S1 absorption spectra.\\u003c/strong\\u003e (\\u003cstrong\\u003eA\\u003c/strong\\u003e) a direct comparison among MERS-CoV (blue line), SARS-CoV (red-line) and SARS-CoV-2 (yellow line) S1 absorption is shown. While MERS-CoV and SARS-CoV show similar spectra centered around 1660 cm\\u003csup\\u003e-1\\u003c/sup\\u003e, the absorption of SARS-CoV-2 is red-shifted of about 10 cm\\u003csup\\u003e-1\\u003c/sup\\u003e, being centered around 1650 cm\\u003csup\\u003e-1\\u003c/sup\\u003e.\\u0026nbsp; In the inset of the same panel, we report the differences A(ω)\\u003csub\\u003e(SARS-CoV-2)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(SARS-CoV)\\u003c/sub\\u003e (red line), and A(ω)\\u003csub\\u003e(SARS-CoV-2)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(MERS-CoV)\\u003c/sub\\u003e (blue line), in comparison to the reproducibility of the SARS-CoV-2 absorption spectra. This is estimated by the difference A(ω)\\u003csub\\u003e(SARS-CoV-2)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(SARS-CoV-2)\\u003c/sub\\u003e for two separated measurement runs (yellow line). The inset shows a sizeable increase of the low-frequency absorption of SARS-CoV-2 S1 unit with respect to both SARS-CoV and MERS-CoV. Panels (\\u003cstrong\\u003eB\\u003c/strong\\u003e), (\\u003cstrong\\u003eC\\u003c/strong\\u003e) and (\\u003cstrong\\u003eD\\u003c/strong\\u003e) compare the absorption spectra of MERS-CoV, SARS-CoV and SARS-CoV-2 (black lines), their decomposition based on Gaussian peaks (colored lines) and the global fitting (empty circles).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2245843/v1/1028e425dd845d19acea1fc8.png\"},{\"id\":29688128,\"identity\":\"4b0b0407-ad78-4c20-9a4e-f1e7a54daaab\",\"added_by\":\"auto\",\"created_at\":\"2022-11-29 23:11:01\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":885176,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAmide I SARS-CoV-2 S1 absorption spectra at different pH values.\\u003c/strong\\u003e In (\\u003cstrong\\u003eA\\u003c/strong\\u003e), a direct comparison among SARS-CoV-2 S1 absorption spectra varying the pH from acid to alkaline condition is shown. While the spectra obtained at pH=7.4 and 8.8 are centered around 1650 cm\\u003csup\\u003e-1\\u003c/sup\\u003e, the absorption bands for the other pH values (4.55, 5.5 and 11.3) are red-shifted of about 10 cm\\u003csup\\u003e-1\\u003c/sup\\u003e being centered around 1640 cm\\u003csup\\u003e-1\\u003c/sup\\u003e.\\u0026nbsp; In (\\u003cstrong\\u003eB\\u003c/strong\\u003e), the differences A(ω)\\u003csub\\u003e(pH=7.4)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(pH=4.55)\\u003c/sub\\u003e (green line), and A(ω)\\u003csub\\u003e(pH=7.4)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(pH=5.5)\\u003c/sub\\u003e (light blue line), A(ω)\\u003csub\\u003e(pH=7.4)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(pH=8.8)\\u003c/sub\\u003e (violet line) and A(ω)\\u003csub\\u003e(pH=7.4)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(pH=11.3)\\u003c/sub\\u003e (blue line) in comparison to the reproducibility at pH=7.4. This quantity is estimated by the difference A(ω)\\u003csub\\u003e(pH=7.4)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(pH=7.4)\\u003c/sub\\u003e for two separate measurement runs (yellow line). While SARS-CoV-2 absorption reproducibility at pH=7.4 fluctuates less than 2% in the whole Amide I spectral range, sizeable differences appear when the pH moves from the serological value. In fact, an absorption redistribution occurs around an isosbestic point at about 1645 cm\\u003csup\\u003e-1\\u003c/sup\\u003e, with an absorption reduction between 1600-1645 cm\\u003csup\\u003e-1\\u003c/sup\\u003e for both acid and alkaline pHs, and an enhancement at higher frequencies. Panel (\\u003cstrong\\u003eC\\u003c/strong\\u003e), (\\u003cstrong\\u003eD\\u003c/strong\\u003e), (\\u003cstrong\\u003eE\\u003c/strong\\u003e) and (\\u003cstrong\\u003eF\\u003c/strong\\u003e) show instead the deconvoluted absorption spectra of the SARS-CoV-2 S1 at different pH (black lines) superimposed to the global fitting (empty circles) and the Gaussian components decomposition (colored lines).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2245843/v1/04e434eb020694658eea3a85.png\"},{\"id\":29688127,\"identity\":\"019c1255-f455-40bf-891f-ebbbe849fe32\",\"added_by\":\"auto\",\"created_at\":\"2022-11-29 23:11:00\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":417706,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eIntensity secondary structures vs. pH.\\u003c/strong\\u003e The intensity of β-sheet, α-helix, random-coil and β-turn absorptions vs. pHs from acid to alkaline levels.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2245843/v1/b0af96505028c8e64b163adc.png\"},{\"id\":30451202,\"identity\":\"dfe3eab2-cf51-46d0-8807-49ad1b646e84\",\"added_by\":\"auto\",\"created_at\":\"2022-12-16 21:46:04\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2042589,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2245843/v1/f176ba11-bd45-4820-b55a-2ce1fa3d055f.pdf\"},{\"id\":29687324,\"identity\":\"f1925800-e04b-4f3b-b2b0-371c82388dd3\",\"added_by\":\"auto\",\"created_at\":\"2022-11-29 23:03:00\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":823394,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"LupiSINatComm.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2245843/v1/4435ff8038d045b1c5f98ad1.docx\"},{\"id\":29687322,\"identity\":\"6af2b11f-07bd-4a17-b9e9-22085b8ed360\",\"added_by\":\"auto\",\"created_at\":\"2022-11-29 23:03:00\",\"extension\":\"png\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":230777,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eGraphical abstract\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"GA.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2245843/v1/6df6a5f1198dd439a3235565.png\"}],\"financialInterests\":\"There is \\u003cb\\u003eNO\\u003c/b\\u003e Competing Interest.\",\"formattedTitle\":\"Secondary conformation of MERS-CoV, SARS-CoV and SARS-CoV-2 Spike Proteins revealed by Infrared Vibrational Spectroscopy\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eThe global emergency, due to COVID-19 pandemic, poses a grave threat to public health, security and economy, imposing a severe burden on our society (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e). The virus responsible for COVID-19 disease is a new member of the Coronaviridae family, SARS-CoV-2 (\\u003cspan additionalcitationids=\\\"CR3\\\" citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e). Like SARS-CoV-2, other two coronaviruses (CoVs) are known to cause deadly pneumonia. These are severe acute respiratory syndrome coronavirus (SARS-CoV) (\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e) and Middle East respiratory syndrome coronavirus (MERS-CoV) (\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e) that determined the previous pandemics occurred in 2002 and 2012, respectively (\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThese viruses have different transmissibility, hospitalization and case fatality rates. SARS-CoV-2 is less deadly than SARS-CoV and, in particular of MERS-CoV, and it is considered the third highly infective CoV (\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e). However, a nodal point of any pandemic is the viral transmissibility, quantified by the virus reproductive rate parameter R\\u003csub\\u003e0\\u003c/sub\\u003e; if R\\u003csub\\u003e0\\u003c/sub\\u003e is greater than 1, the pandemic is assumed to be in a growing phase. For SARS-CoV-2, R\\u003csub\\u003e0\\u003c/sub\\u003e in the early months of pandemic has been estimated between 2 and 5 (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e), when the containment measures were not introduced, yet (\\u003cspan additionalcitationids=\\\"CR12\\\" citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e). This value is higher than those of SARS-CoV (\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e) (\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e) and MERS-CoV (0.9) (\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eCoVs are spherical viruses, with diameters ranging between 60\\u0026ndash;150 nm, as shown by Cryo-electron tomography and microscopy studies (\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e). They contain a non-segmented positive-sense RNA (+\\u0026thinsp;ssRNA), which acts as an mRNA for translation of the replicase polyproteins, encoding the genetic content accessory and structural proteins, such as Spike (S) glycoproteins. Spike is a I-th class fusion protein (\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e) protruding from the surface of mature virions (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eA). and plays a crucial role both in infection process (\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e) and viral pathogenesis (\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e), including the virus released to various human host cells.\\u003c/p\\u003e \\u003cp\\u003eMature S glycoproteins weigh about 150 kDa and are synthetized in terms of 1300 amino acids polypeptide chains, which associate as heavily glycosylated trimers (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eB). Each S protein is composed by two subunits (S1 and S2). The surface S1 subunit contains an N-terminal domain (NTD) and the receptor binding domain (RBD). Here, the receptor binding motif (RBM) part is responsible for anchoring the host cellular membrane through its receptors (\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e). Therefore, S-protein/cellular-receptor interaction is the primary factor regulating the infectious process. Following receptor binding, viruses gain entry inside the host human cell cytosol. This process is mediated by the membrane fusion S2 unit, which matches host and viral membranes. Another structural feature of S proteins is their extensive glycosylation (\\u003cspan additionalcitationids=\\\"CR24 CR25\\\" citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e). The CoV S glycoproteins are densely decorated by heterogeneous N-linked glycans, that are used by viral fusion proteins as a shield to counteract the host immune response (\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR28 CR29 CR30 CR31 CR32\\\" citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e), participating in the S folding (\\u003cspan additionalcitationids=\\\"CR35\\\" citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e) and working as recognition sites (\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThe transmissibility and pathogenicity of viruses are determined by both viral and host factors, such as the combination of immune evasion, the conformational masking of binding domains and glycan shielding, and the extent of the human receptor binding affinity and specificity. As all CoVs present S glycoproteins, their different peculiarities, such as transmissibility, could be related to different secondary S protein conformation (\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e). In addition, the efficient viral propagation within a biological host and/or ecological niche is also mediated by the pH. The pH could affect the S protein secondary conformation, inducing a refolding of the viral proteins, modulating the virus entry and engaging the hACE2 receptor. High pH values could result in viral protein inactivation, as it happens in the multifunctional hemagglutinin protein of the influenza virus (\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e). In light of the relevant role of the S protein and in particular of its S1 unit, is absolutely mandatory to investigate its secondary conformation in serological condition in different families of CoVs and also to study the secondary conformation stability as a function of pH.\\u003c/p\\u003e \\u003cp\\u003eIn this manuscript, we perform for the first time, at the best of our knowledge, a comparative infrared spectroscopic study of S1 unit glycoproteins of MERS-CoV, SARS-CoV and SARS-CoV-2, with the purpose of investigating their complex secondary structure in serological ambient. In particular, the secondary structure of MERS-CoV, SARS-CoV and SARS-CoV-2 S1 units has been determined through a spectral component analysis of the protein Amide I vibrational band (\\u003cspan additionalcitationids=\\\"CR41 CR42 CR43\\\" citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e). Through these measurements, we experimentally demonstrate that the three S1 glycoproteins have different secondary conformations. Notably, SARS-CoV-2 glycoprotein S1 unit reveals a strong difference in conformational secondary structure in comparison to the MERS-CoV and SARS-CoV ones, having a higher amount of intermolecular β-sheet structure. This difference indicates that the binding of the virus to the human receptor is correlated to the spike protein secondary conformation (\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e). We have also observed strong changes in the conformation of SARS-CoV-2 S1 unit by moving from neutral pH, which characterize the human serological environment, to endosomal pHs (mildly acidic) and finally to alkaline environments characterizing the ecological niche of bats. These results indicate a huge capability of SARS-CoV-2 S1 glycoprotein to rapidly adapt its secondary structure to different environments facilitating virus transmissibility, demonstrating that infrared vibrational spectroscopy is a valuable tool for the investigation of spike secondary conformation structure, and for identifying different coronavirus families.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eAmide I: Protein secondary structure\\u003c/h2\\u003e \\u003cp\\u003eFigure\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e shows the absorbances A(ω) vs. frequency (ω) of the S1 glycoprotein of MERS-CoV (\\u003cb\\u003eB\\u003c/b\\u003e), SARS-CoV (\\u003cb\\u003eC\\u003c/b\\u003e) and SARS-CoV-2 (\\u003cb\\u003eD\\u003c/b\\u003e) in the Amide I band, between 1580 and 1750 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e, measured at pH 7.4 and at a concentration of 0.25 mg/ml. Similar data have been obtained for other concentrations (see \\u003cb\\u003eFig. S1\\u003c/b\\u003e in supporting information). A first qualitative comparison can be made looking at Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA, where the absorption spectra of the three S1 proteins are shown. While MERS-CoV (blue line) and SARS-CoV (red line) show a quite similar broad absorption band centered at about 1660 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e, in SARS-CoV-2 (yellow line) the band has a maximum around 1650 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e. This red-shift can be further quantified by calculating the differences A(ω)\\u003csub\\u003e(SARS\\u0026minus;CoV\\u0026minus;2)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(MERS\\u0026minus;CoV)\\u003c/sub\\u003e, and A(ω)\\u003csub\\u003e(SARS\\u0026minus;CoV\\u0026minus;2)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(SARS\\u0026minus;CoV)\\u003c/sub\\u003e (blue and red line in the inset of Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA, respectively) and comparing them with the reproducibility of the A(ω)\\u003csub\\u003e(SARS\\u0026minus;CoV\\u0026minus;2)\\u003c/sub\\u003e absorption measurements. The reproducibility has been estimated by the difference A(ω)\\u003csub\\u003e(SARS\\u0026minus;CoV\\u0026minus;2)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(SARS\\u0026minus;CoV\\u0026minus;2)\\u003c/sub\\u003e for two different measurement runs (yellow line in inset of Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA). The SARS-CoV-2 absorption reproducibility fluctuates less than 2% in the whole Amide I spectral range. Instead, a sizeable difference (actually far out of the reproducibility of absorption spectra), can be observed when comparing SARS-CoV-2 with MERS-CoV and SARS-CoV absorptions. In particular, for both MERS-CoV and SARS-CoV there is an absorption reduction between 1600\\u0026ndash;1650 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e (in agreement with the main panel of Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA), and a smaller enhancement at higher frequency.\\u003c/p\\u003e \\u003cp\\u003eIn order to identify the secondary structure for MERS-CoV, SARS-CoV and SARS-CoV-2, a global fitting approach (\\u003cspan additionalcitationids=\\\"CR41\\\" citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e) have been used for deconvoluting in Gaussian spectral components the Amide I band. The total fit (empty circles), and the spectral decomposition (colored Gaussians), of MERS-CoV, SARS-CoV and SARS-CoV-2 Amide I band (black lines), are reported in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB, C and \\u003cb\\u003eD\\u003c/b\\u003e, respectively. The area of each component can be used to estimate the secondary structure content of the S1 protein.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e summarizes the vibrational frequencies of the different Gaussian-components and their relative intensities, together with their assignment to specific secondary conformation structures (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR48\\\" citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e). In particular, we notice in all A(ω) an intense peak around 1658 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e, associated with the α-helix structure (\\u003cem\\u003e40,47\\u0026ndash;49\\u003c/em\\u003e). The β-sheet components are instead observed between 1620\\u0026ndash;1640 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e and around 1690 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e (\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e). In particular, the bands near 1630 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e and 1690 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e are typically related to an antiparallel arrangement of the β-sheet. The bands in the 1665\\u0026ndash;1690 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e range can be assigned instead to the β-turn structure. The broad absorption band centered at 1643 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e corresponds to random coils. The absorption band at 1619 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e, present only in SARS-CoV-2 S1 unit, is finally assigned to side chains and intermolecular anti-parallel β-sheets (\\u003cem\\u003e40,44,47\\u0026ndash;49\\u003c/em\\u003e). The actual secondary structure of S1 unit in MERS-CoV, SARS-CoV and SARS-CoV-2 viruses at pH 7.4 can be estimated through the ratios among the intensity of each component of the Amide I band over the total intensity (also reported in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e) as obtained by the previously mentioned fitting procedure. From these data, one can observe that SARS-CoV and SARS-CoV-2 show similar α-helix (27.7% and 29.4%) and random coil contents (13.5% and 12.3%). The larger difference in the secondary structures of the S1 proteins can be instead observed in the arrangement of β-sheet and β-turn. Notably, a significant increase is revealed in the β-sheets content passing from MERS-CoV (20.6%) to SARS-CoV (26.8%) and SARS-CoV-2 (30.6%). This is mainly due to the strong increase of the antiparallel β-sheet structure observed at 1619 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e for the SARS-CoV-2 S1 unit, which corresponds to nearly 5% of the total protein secondary structures. An opposite trend is shown by the β-turn (1665\\u0026ndash;1687 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e): MERS-CoV and SARS-CoV S1 proteins exhibit approximatively the same β-turn content (30.6 and 32 ), compared to \\u003cb\\u003e~\\u003c/b\\u003e\\u0026thinsp;28 of the SARS-CoV-2 S1 unit. Observing the results concerning MERS-CoV and SARS-CoV S1 proteins, we notice a similarity in the secondary conformational structure (α-helix and β-turn), attributable to the aminoacid sequence identity of their S1 unit (\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e). Instead, although both SARS-CoV-2 and SARS-CoV S1 proteins interact with the human hACE2 receptor and show a sequence similarity (between 73\\u0026ndash;75 ) as determined by Cryo-EM (\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e), they exhibit, on the basis of our vibrational absorption measurements, a robust secondary conformation difference.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSecondary structure assignment for MERS-CoV, SARS-CoV and SARS-CoV-2 S1 units derived from the Gaussian decomposition of the absorption spectra\\u003c/b\\u003e. For each S1-protein, we show (first column) the characteristic absorption frequency and (second column) the peak relative intensity. In the third column the observed absorption peaks are assigned to specific secondary conformations (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMERS-CoV peaks\\u003c/p\\u003e \\u003cp\\u003e[cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e]\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eMERS-CoV peak relative intensity [%]\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eSARS-CoV peaks\\u003c/p\\u003e \\u003cp\\u003e[cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e]\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003eSARS-CoV peak relative intensity [%]\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eSARS-CoV-2 peaks\\u003c/p\\u003e \\u003cp\\u003e[cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e]\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eSARS-CoV-2 peak relative intensity [%]\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eAssignment\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e1619\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e5.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eβ-sheet (intermolecular)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1628\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e14.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1625\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e7.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e1628\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e11.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eβ-sheet\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1632\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1633\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e1633\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e9.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eβ-sheet\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1641\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e16.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1642\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e13.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e1643\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e12.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eRandom coils\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1650\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e13.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1650\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e1650\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e13.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eα-helix\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1658\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e18.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1658\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e14.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e1658\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e15.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eα-helix\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1666\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e10.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1666\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e1666\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e5.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eβ-turn\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1673\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e1673\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e6.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eβ-turn\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1675\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e10.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eβ-turn\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1680\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e11.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1681\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e9.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e1678\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e15.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eβ-turn\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1693\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1690\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e1693\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e4.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eβ-sheet\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eBeing the receptor-protein recognition conformation-dependent, the observed differences can be related to their differential receptor-binding affinities. Indeed, recent Cryo-EM and computational studies have shed light on this behavior (\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR52 CR53\\\" citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e), investigating the binding affinity of the RBD sites for the hACE2-peptidase domain. Experimentally, Wrapp et al. (\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e) and Tai et al. (\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e) have reported that the SARS-CoV-2 RBD has a higher binding affinity for hACE2-peptidase domain than the SARS-CoV RBD.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eAmide I: Changes In Secondary Structure Induced By Ph Variation\\u003c/h3\\u003e\\n\\u003cp\\u003eThe pH-dependent conformation changes in proteins play a key role in virus replication, pathogenesis, and transmissibility. In particular, the local-environment pH can strongly influence the protonation state in folded proteins by promoting changes in interchain interactions. Consequently, the stability of proteins is pH-dependent, favoring conformational flexibility, protein activation and/or inactivation. In this framework, we have studied the secondary conformation of SARS-CoV-2 S1 protein at different pH values (pH\\u0026thinsp;=\\u0026thinsp;4.55, 5.5, 7.4, 8.8 and 11.2), by measuring the absorbance A(ω) of the Amide I band (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA). The absorption behavior vs. pH is not monotonic; while SARS-CoV-2 S1 at serological (yellow line) and 8.8 (purple line) pH values show a similar broad absorption band centered at about 1650 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e, the spectra relative to mild low pHs (blue line at 4.55 pH, and red line at 5.5 pH) and alkaline pH (green line at 11.2 pH) are red-shifted of about 10 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e and exhibit a maximum around 1640 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e. This red-shifting can be further observed in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB, where the calculated absorption differences A(ω)\\u003csub\\u003e(pH 7.4)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(pH x)\\u003c/sub\\u003e, are compared with the reproducibility of A(ω)\\u003csub\\u003e(pH 7.4)\\u003c/sub\\u003e. This last quantity has been estimated by the difference A(ω)\\u003csub\\u003e(pH=7.4)\\u003c/sub\\u003e-A(ω)\\u003csub\\u003e(pH=7.4)\\u003c/sub\\u003e for two different measurement runs (yellow line in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB). Let us notice that a similar reproducibility can be observed at any pH. The absorption reproducibility fluctuates less than 2% in the whole Amide I spectral range. Significant differences, actually far out the reproducibility, emerge when the pH moves from mild low values to alkaline ones. Indeed, an absorption frequency redistribution is observed around an isosbestic point at about 1647\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e. As the S1 protein concentration and all physical parameters, e.g., temperature, pressure and relative humidity, are kept constant during experiments, the occurrence of the isosbestic point can be associated to the conformational changes in the protein structure induced by the pH.\\u003c/p\\u003e \\u003cp\\u003eThe influence of pH on the S1 protein conformation can be quantified by studying the change in peak position and intensity of the spectral components of the Amide I band through a global Gaussian fitting. The global fit (empty circles), and the spectral decomposition (colored Gaussians), of the Amide I band for different pHs (4.55, 5.5, 8.8 and 11.2), are compared in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eC, D, E and \\u003cb\\u003eF\\u003c/b\\u003e, respectively. Absorption at pH\\u0026thinsp;=\\u0026thinsp;7.4 has been already reported in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eD. The area of each spectral component has been used to estimate the secondary structure content and then its variation with pH. In \\u003cb\\u003eTable S1\\u003c/b\\u003e, the peak frequencies for the Amide I S1 protein vs. pH and associated to specific secondary conformation structures are shown while their intensities vs. pH are represented in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e which will be discussed in the following (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe main effect of pH concerns, firstly, the α-structure (see \\u003cb\\u003eTable S1\\u003c/b\\u003e in supporting information), which give rise to a main absorption band at 1658 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e and to a shoulder at lower frequencies around 1650 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e at 7.4 pH. While the main α-structure component remains nearly constant in frequency (1658\\u0026ndash;1659 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e) for pH moving from 7.4 to 5.5, this band shifts near to 1663 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e at pH\\u0026thinsp;=\\u0026thinsp;4.55 and at alkaline levels. Usually, a blue-shift is associated to the formation of a short α-helix. Moreover, for acid pHs, the whole α-helix absorption reduces its intensity of about 50% (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). The band at 1643 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e for 7.4 pH associated to random coils, is also influenced by pH variation, blue-shifting to 1646 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e for acid and alkaline pHs. Its intensity is maximized at pH\\u0026thinsp;=\\u0026thinsp;5.5 (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). The intermolecular β-sheet located around 1619 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e at serological and alkaline pHs, instead red-shifts for acid conditions. The other β-sheet components are located between 1620\\u0026ndash;1640 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e and around 1690 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e (see \\u003cb\\u003eTable S1\\u003c/b\\u003e in supporting information) (\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e) at pH\\u0026thinsp;=\\u0026thinsp;7.4. The band at 1629 is red-shifted at 1628 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e at acid pH levels suggesting the aggregation of sheets with a large number of strands (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e), and blue-shifted at 1633 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e for alkaline pHs. The absorption of β-sheet for pH\\u0026thinsp;=\\u0026thinsp;4.55, 5.5 and 11.2 pH is related to a new band at 1637 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e. Finally, the absorption at 1693 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e disappears for extreme pH values. From Table S1, the total intensity of β-sheet presents a minimum at serological pH, being maximized at acid pHs. The bands in 1666\\u0026ndash;1678 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e range, assigned to β-turn structures (\\u003cem\\u003e40, 44, 47,49, 55\\u003c/em\\u003e) are blue-shifted compared to their spectral positions at 7.4 pH, while a new band appears at 1686 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e for pH values of 4.55, 8.8 and 11.2. The total intensity of β-turn structures, which shows a maximum at pH\\u0026thinsp;=\\u0026thinsp;7.4 reduces both at acid and alkaline pHs.\\u003c/p\\u003e \\u003cp\\u003eFor a quantitative evaluation of secondary conformation changes, we show in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e the ratio between the secondary structure peak areas and the total area vs. pH. At the serological pH 7.4, the α-helix and β-turn structures show their maxima, reducing their intensity both in acid and alkaline conditions. Conversely, the random coil and the β-sheet present an opposite behavior with minima at pH 7.4 while increasing towards the acid and alkaline pH values. Moving from serological to alkaline environment, at pH 8.8 the contents of random coil and α-helix are almost unchanged, differently from β-sheet and β-turn structures which increase and decrease, respectively. Thus, a slight unfolding of β-structures appears at pH 8.8, that is the typical environmental pH observed in bat caves where high ammonia concentrations build up. Moreover, at pH 11.2 the decrease of the β-turn content by an average of ~\\u0026thinsp;10% and the increase of β-sheet structure of 12% are observed. This behavior suggests a transition from β-turn the to the β-sheet structure in the strong alkaline medium (pH\\u0026thinsp;=\\u0026thinsp;11.2), while a slight rearrangement of the α-structure is observed under mild alkaline conditions. This is also consistent with a loss of secondary structure, perhaps due to a partial protein unfolding. The reduction of the β-turn content is also observed for acidic pHs. In addition, the β-sheet content increases from its value at 7.4 pH (~\\u0026thinsp;30.6%) moving from neutral to mild low pH at 47% of all Amide I band. The content of side chains and intermolecular β-sheets (~\\u0026thinsp;1619 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e), associated to a low frequency band, exhibits a pH-dependent behavior, with a maximum value of ~\\u0026thinsp;19% at 5.5 pH, to be compared with the serological value (5%).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe strong changes of the protein secondary conformation at pH 5.5 is associated with the rearrangement and modification of the RBD sites. Some investigations have shown that several regions of the SARS-CoV-2 S protein are susceptible to mutations, with the RBD site particularly vulnerable to a conformational change (\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e). The RBD undergoes indeed a hinge-like movement that brings up or down the specific amino-acid sequence responsible for the binding to the hACE2 receptor (\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e) inducing a change in the secondary conformation. In our work, we observe a large variation of intermolecular β-sheets content for the SARS-CoV-2 S1 vs. pH (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e), with a maximum value at pH\\u0026thinsp;=\\u0026thinsp;5.5 (nearly 20%). This behavior can be related to a structural transition from a closed over a locked form of S1 as pH is increased from mild acidic to neutral as observed by Cryo-EM microscopy studies (\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e), with an optimal condition for the pre-fusion configuration at pH 5.5.\\u003c/p\\u003e \\u003cp\\u003eThe overall strong conformational changes of SARS-CoV-2 S1 unit vs. pH by passing from the alkaline ones, characteristic of the ecological niche bats ambient, to the human serological environment, suggests a high capability of S1 SARS-CoV-2 glycoprotein to adapt to different environments, further indicating the existence of a correlation between the S1 protein secondary conformation and the virus transmissibility.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eIn this manuscript we investigate the secondary conformation structure of the S1 sub-unit spike-protein, which is responsible for anchoring coronaviruses to the human cellular membrane through infrared vibrational spectroscopy. In particular, the secondary S1 structures of MERS-CoV, SARS-CoV and SARS-CoV-2 have been characterized through infrared spectroscopy by measuring their Amide I vibrational band. Experimental data point out that the three S1 glycoproteins have different secondary conformations. Notably, SARS-CoV-2 glycoprotein S1 unit, at variance with MERS-CoV and SARS-CoV, presents a larger amount of intermolecular β-sheet structures, which indicates a more stable protein structure. Similarly, we have also observed large changes in the conformation of the SARS-CoV-2 S1 unit by moving from human serological pH to alkaline pH conditions characterizing the typical ecological niche of bats.\\u003c/p\\u003e \\u003cp\\u003eThe whole results indicate, from one side that infrared vibrational spectroscopy provides virologists with rapid and insightful information on secondary conformation of all coronavirus family establishing similarity and differences. From the other side, our data indicates the huge capability of the SARS-CoV-2 S glycoprotein to adapt to a variable environment, pointing out the strong role of the S1 protein secondary conformation in the virus transmissibility.\\u003c/p\\u003e\"},{\"header\":\"Materials And Methods\",\"content\":\"\\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eProtein preparation\\u003c/h2\\u003e \\u003cp\\u003eRecombinant S1 proteins, fused with a polyhistidine tag at the C terminus of MERS-CoV (Cat. 40069-V08B1), SARS-CoV (Cat. 40150-V08B1) and SARS-CoV-2 (Cat. 40591- V08B1) were purchased from Sino Biological Europe GmbH. They are expressed in baculovirus insect cells with the same purity\\u0026thinsp;\\u0026gt;\\u0026thinsp;90% as determined by Sodium Dodecyl Sulphate - PolyAcrylamide Gel Electrophoresis (SDS-PAGE), and finally used without further purification. This work was carried out on a dataset of S proteins collected in late spring 2020, and as regards SARS-CoV-2, we refer to the alpha variant that affected Europe and Italy in the pandemic crisis of March 2020.\\u003c/p\\u003e \\u003cp\\u003eThe lyophilized proteins were reconstructed dissolving 100 \\u0026micro;g in distilled water (400 \\u0026micro;l) at pH 7.4 (0.25 mg/ml concentration). The samples for the pH-dependent study of SARS-CoV-2 S1 subunit were prepared as follows. Briefly, in order to adjust the pH of proteins NaOH or HCl aqueous solutions at molar concentrations of 10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e and 10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;4\\u003c/sup\\u003e M were used. The solution has been gently shaken waiting for the state of equilibrium of the reaction, monitoring its pH with a pH-meter from DOSTMANN pH 80\\u0026thinsp;+\\u0026thinsp;DHS. We prepared two samples of acidic S1 protein solutions at pH 4.55 and 5.5, and two in alkaline environments, having pH 8.8 and 11.2.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eAttenuated-total-reflection Infrared Spectroscopy And Data Analysis\\u003c/h3\\u003e\\n\\u003cp\\u003eAttenuated Total Reflection (ATR) infrared spectra of the Spike glycoproteins S1-unit of MERS-CoV, SARS-CoV and SARS-CoV-2 were collected using a Bruker Vertex 70v Michelson spectrometer equipped with an ATR\\u0026ndash;Diamond module Harrick MVP-Pro and a DLaTGS wide range detector. Spectroscopic measurements were carried out at room temperature and with the interferometer under vacuum in order to eliminate water-vapor and CO2 absorptions. The background spectrum (buffer solution) was collected immediately prior to each sample measurement. Five microliters of the sample solution were placed directly on the diamond crystal and 64 scans between 400\\u0026ndash;4000 cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e with a resolution of 2 cm-1 were acquired. Each spectrum is the average of six independent measurements. The ATR crystal was cleaned with ethanol (add purity) and subsequently with a lens tissue, in order to eliminate any spurious signal.\\u003c/p\\u003e \\u003cp\\u003eRaw data have been processed and analyzed using OPUS 8.2 (Bruker Optics) and in-house algorithms based on MATLAB (ver. 2018, MathWorks Inc., USA). To obtain the protein absorption spectra A(ω), shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, we subtracted the buffer spectrum (see supplementary information for details) to eliminate the contribution of the background (\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e) and applied the ATR correction algorithm and a piecewise baseline subtraction.\\u003c/p\\u003e \\u003cp\\u003eThe secondary conformation of glycoprotein S1 unit is obtained by the decomposition of the Amide I vibrational absorption band (\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e) into its spectral components through the 2nd-derivative procedure (\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e) combined with a multicomponent Gaussian fitting. In particular, the frequencies, achieved by 2nd-derivative spectra, were used as starting points for Gaussian curve fitting and the residual error (RMSE) was employed for assessing the convolution procedure performance. The intensity of each component peak normalized to the total intensity was used to calculate the percentage of each absorption band and then to estimate the secondary conformation of the S1 unit spike protein (\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e).\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eData availability\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll data are available in the main text or the supplementary materials.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgments\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe\\u0026nbsp;thank NATO SPS for providing the opportunity and for supporting the development of SARS 3M project. We are also deeply grateful to all healthcare workers and beyond fighting COVID-19 to ensure community safety and health.\\u003c/p\\u003e\\n\\u003cp\\u003eFunding: This work was funded by the NATO Science for Peace and Security Programme under grant No. 5889 \\u0026nbsp;\\u0026ldquo;SARS-CoV-2 Multi-Messenger Monitoring for Occupational Health \\u0026amp; Safety (SARS 3M)\\u0026rdquo;, by MIUR \\u0026ndash; Fondo speciale per la Ricerca - FISR 2020 COVID project titled \\u0026ldquo;Multi-Messenger and Machine Learning Monitoring of SARS-CoV-2 for occupational health \\u0026amp; safety (4M SARS-CoV-2)\\u0026rdquo; and LazioInnova \\u0026ldquo;Gruppi di Ricerca 2020\\u0026rdquo; of the POR FESR 2014/2020\\u0026mdash;A0375-2020-36651 project entitled \\u0026ldquo;DEUPAS -DEterminazione Ultrasensibile di agenti PAtogeni mediante Spettroscopia\\u0026rdquo;. Financial support by the Grant to Department of Science, Roma Tre University (MIUR-Italy Dipartimenti di Eccellenza, ARTICOLO 1, COMMI 314-337 LEGGE 232/2016) is gratefully acknowledged.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eEach author\\u0026rsquo;s contribution(s) to the paper should be listed. Conceptualization: AD, SL; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Methodology: AD, MDF, SL; Investigation: AD, MDF, TM, RM, SM; Formal Analysis: AD, MDF, RM; Data interpretation: AD, LS, MDF, GT; Visualization: AD, MDF, TM, RM, SM; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Supervision: SL, AM, MP, GT, GDV; Funding acquisition: SL, AM, GDV, MP, GT; Writing\\u0026mdash;original draft: AD, SL; Writing\\u0026mdash;review \\u0026amp; editing: AD, MDF, TM, RM, SM, MP, AM, GDV, GT, SL. All authors have read and agreed to the published version of the manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAuthors declare that they have no competing interests.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSupplementary Materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe online version contains supplementary material available at \\u0026hellip;\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eLi, Q. et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. \\u003cem\\u003eN. Engl. J. Med\\u003c/em\\u003e. \\u003cstrong\\u003e382\\u003c/strong\\u003e, 1199-207 (2020). \\u003c/li\\u003e\\n\\u003cli\\u003eHuang, C. et al. 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Distinct \\u0026beta;-Sheet Structure in Protein Aggregates Determined by ATR\\u0026ndash;FTIR Spectroscopy. \\u003cem\\u003eBiochemistry \\u003c/em\\u003e\\u003cstrong\\u003e52(31)\\u003c/strong\\u003e, 5176-5183 (2013). \\u003c/li\\u003e\\n\\u003cli\\u003eVeesler, D. et al. Production and biophysical characterization of the CorA transporter from Methanosarcina mazei. \\u003cem\\u003eAnal. Biochem\\u003c/em\\u003e. \\u003cstrong\\u003e388\\u003c/strong\\u003e (1), 115\\u0026ndash;121 (2009). \\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"Tables\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 1. Secondary structure assignment for MERS-CoV, SARS-CoV and SARS-CoV-2 S1 units derived from the Gaussian decomposition of the absorption spectra\\u003c/strong\\u003e. For each S1-protein, we show (first column) the characteristic absorption frequency and (second column) the peak relative intensity. In the third column the observed absorption peaks are assigned to specific secondary conformations (\\u003cem\\u003e40,49\\u003c/em\\u003e).\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellpadding=\\\"0\\\" cellspacing=\\\"0\\\" width=\\\"614\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.72549019607843%\\\"\\u003e\\n \\u003cp\\u003eMERS-CoV peaks\\u003c/p\\u003e\\n \\u003cp\\u003e[cm\\u003csup\\u003e-1\\u003c/sup\\u003e]\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.72549019607843%\\\"\\u003e\\n \\u003cp\\u003eMERS-CoV peak relative intensity [%]\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.72549019607843%\\\"\\u003e\\n \\u003cp\\u003eSARS-CoV peaks\\u003c/p\\u003e\\n \\u003cp\\u003e[cm\\u003csup\\u003e-1\\u003c/sup\\u003e]\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.72549019607843%\\\"\\u003e\\n \\u003cp\\u003eSARS-CoV peak relative intensity [%]\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" width=\\\"13.72549019607843%\\\"\\u003e\\n \\u003cp\\u003eSARS-CoV-2 peaks\\u003c/p\\u003e\\n \\u003cp\\u003e[cm\\u003csup\\u003e-1\\u003c/sup\\u003e]\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.72549019607843%\\\"\\u003e\\n \\u003cp\\u003eSARS-CoV-2 peak relative intensity [%]\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"17.647058823529413%\\\"\\u003e\\n \\u003cp\\u003eAssignment\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e-\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e-\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e-\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"10.277324632952691%\\\"\\u003e\\n \\u003cp\\u003e-\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" width=\\\"17.29200652528548%\\\"\\u003e\\n \\u003cp\\u003e1619\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e5.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"17.61827079934747%\\\"\\u003e\\n \\u003cp\\u003e\\u0026beta;-sheet (intermolecular)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e1628\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e14.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e1625\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"10.277324632952691%\\\"\\u003e\\n \\u003cp\\u003e7.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" width=\\\"17.29200652528548%\\\"\\u003e\\n \\u003cp\\u003e1628\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e11.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"17.61827079934747%\\\"\\u003e\\n \\u003cp\\u003e\\u0026beta;-sheet\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e1632\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e2.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e1633\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"10.277324632952691%\\\"\\u003e\\n \\u003cp\\u003e12.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" width=\\\"17.29200652528548%\\\"\\u003e\\n \\u003cp\\u003e1633\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e9.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"17.61827079934747%\\\"\\u003e\\n \\u003cp\\u003e\\u0026beta;-sheet\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e1641\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" width=\\\"13.70309951060359%\\\"\\u003e\\n \\u003cp\\u003e16.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" 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Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-2245843/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-2245843/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eAll coronaviruses are characterized by spike glycoproteins whose S1 subunit contains the receptor binding domain anchoring the virus to the host cellular membrane and regulating virus transmissibility and infectious process. Although the protein/receptor interaction depends on the spike secondary-conformation, in particular to its S1 unit, few is known about the secondary-structure of different coronaviruses. \\u0026nbsp;In this paper the S1 conformation is investigated for MERS-CoV, SARS-CoV and SARS-CoV-2 in serological condition, by measuring their Amide I infrared vibrational absorption bands. The SARS-CoV-2 secondary structure reveals a strong difference in comparison to MERS-CoV and SARS-CoV ones, with a higher amount of intermolecular β-sheet content. Moreover, the conformation of SARS-CoV-2 S1 shows a significant change by moving from serological pH and mild acidic to alkaline pH conditions close to the bat ecological niche. Both results suggest a huge capability of SARS-CoV-2 S1 glycoprotein to adapt its secondary structure to different environments.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Secondary conformation of MERS-CoV, SARS-CoV and SARS-CoV-2 Spike Proteins revealed by Infrared Vibrational Spectroscopy\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2022-11-29 23:02:55\",\"doi\":\"10.21203/rs.3.rs-2245843/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"9a42f5f5-b422-4560-bbb7-bf8bbc25e4d3\",\"owner\":[],\"postedDate\":\"November 29th, 2022\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":17198004,\"name\":\"Biological sciences/Biophysics/Molecular biophysics\"},{\"id\":17198005,\"name\":\"Health sciences/Biomarkers/Diagnostic markers\"}],\"tags\":[],\"updatedAt\":\"2022-12-16T21:45:56+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2022-11-29 23:02:55\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-2245843\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-2245843\",\"identity\":\"rs-2245843\",\"version\":[\"v1\"]},\"buildId\":\"WrCJVZZCHTDjtuVLN7oU0\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}