Determination of Secondary Structure of Proteins by Nanoinfrared Spectroscopy.

Nanoscale infrared spectroscopy (AFMIR) is becoming an important tool for the analysis of biological sample, in particular protein assemblies, at the nanoscale level. While the amide I band is usually used to determine the secondary structure of proteins in Fourier transform infrared spectroscopy, no tool has been developed so far for AFMIR. The paper introduces a method for the study of secondary structure of protein based on a protein library of 38 well-characterized proteins. Ascending stepwise linear regression (ASLR) and partial least square (PLS) regression were used to correlate spectrum characteristic bands with the major secondary structures (α-helixes and ß-sheets). ASLR appears to provide better results than PLS. The secondary structure predictions are characterized by a root mean square standard error in a cross validation of 6.39% for α-helixes and 6.23% for ß-sheets.

Electro-plasmonic-assisted biosensing of proteins and cells at the surface of optical fiber.

An electro-plasmonic biosensor is used to attract proteins and cells on the surface of a fiber optic probe by controlled biomolecular migration. Concentrating targets on a high performance plasmon-assisted fiber grating sensor leads to a drastic enhancement of the limit of detection. This architecture relies on a biofunctionalized gold coated tilted fiber Bragg grating (TFBG) that operates as a working electrode to enable electrophoresis in the probed medium. The applied electric field triggers the attraction of proteins over a distance of almost 250 µm from the sensor surface, which is more than two orders of magnitude larger than the intrinsic penetration depth of the plasmon wave. Quantitative determination of target analytes was performed by cyclic voltammetry measurements using the gold coated fiber as an electrode, simultaneously with optical transmission measurements of the underlying fiber grating. In our work, these electro-plasmonic optrodes were used against a clinically-relevant biomarker in breast cancer diagnosis, namely HER2 (Human Epidermal Growth Factor Receptor-2). In vitro assays confirm that their limit of detection lies in the subpicomolar range for proteins, which is beyond reach of similar sensors without voltammetry. The improved detection limit is further facilitated by an improvement of the signal-to-noise ratio of the read-out process. Whole cell capture is finally demonstrated by the same micro-system.

ATR-FTIR Biosensors for Antibody Detection and Analysis.

Quality control of drug products is of paramount importance in the pharmaceutical world. It ensures product safety, efficiency, and consistency. In the case of complex biomolecules such as therapeutic proteins, small variations in bioprocess parameters can induce substantial variations in terms of structure, impacting the drug product quality. Conditions for obtaining highly reproducible grafting of 11-mercaptoundecanoic acid were determined. On that basis, we developed an easy-to-use, cost effective, and timesaving biosensor based on ATR-FTIR spectroscopy able to detect immunoglobulins during their production. A germanium crystal, used as an internal reflection element (IRE) for FTIR spectroscopy, was covalently coated with immunoglobulin-binding proteins. This thereby functionalized surface could bind only immunoglobulins present in complex media such as culture media or biopharmaceutical products. The potential subsequent analysis of their structure by ATR-FTIR spectroscopy makes this biosensor a powerful tool to monitor the production of biotherapeutics and assess important critical quality attributes (CQAs) such as high-order structure and aggregation level.

A New Alternative Tool to Analyse Glycosylation in Monoclonal Antibodies Based on Drop-Coating Deposition Raman imaging: A Proof of Concept.

Glycosylation is considered a critical quality attribute of therapeutic proteins as it affects their stability, bioactivity, and safety. Hence, the development of analytical methods able to characterize the composition and structure of glycoproteins is crucial. Existing methods are time consuming, expensive, and require significant sample preparation, which can alter the robustness of the analyses. In this context, we developed a fast, direct, and simple drop-coating deposition Raman imaging (DCDR) method combined with multivariate curve resolution alternating least square (MCR-ALS) to analyze glycosylation in monoclonal antibodies (mAbs). A database of hyperspectral Raman imaging data of glycoproteins was built, and the glycoproteins were characterized by LC-FLR-MS as a reference method to determine the composition in glycans and monosaccharides. The DCDR method was used and allowed the separation of excipient and protein by forming a "coffee ring". MCR-ALS analysis was performed to visualize the distribution of the compounds in the drop and to extract the pure spectral components. Further, the strategy of SVD-truncation was used to select the number of components to resolve by MCR-ALS. Raman spectra were processed by support vector regression (SVR). SVR models showed good predictive performance in terms of RMSECV, R2CV.

Simple and Scalable Chemical Surface Patterning via Direct Deposition from Immobilized Plasma Filaments in a Dielectric Barrier Discharge.

In this work, immobilization of the often unwanted filaments in dielectric barrier discharges (DBD) is achieved and used for one-step deposition of patterned coatings. By texturing one of the dielectric surfaces, a discharge containing stationary plasma filaments is ignited in a mix of argon and propargyl methacrylate (PMA) in a reactor operating at atmospheric pressure. From PMA, hydrophobic and hydrophilic chemical and topographical contrasts at sub-millimeter scale are obtained on silicon and glass substrates. Chemical and physical characterizations of the samples are performed by micrometer-scale X-ray photoelectron spectroscopy and infrared imaging and by water contact angle and profilometry, respectively. From the latter and additional information from high-speed imaging of the plasma phase and electrical measurements, it is suggested that filaments, denser in energetic species, lead to higher deposition rate with higher fragmentation of the precursor, while surface discharges igniting outwards the filaments are leading to smoother and slower deposition. This work opens a new route for a one-step large-area chemical and morphological patterning of surfaces at sub-millimeter scales. Moreover, the possibility to separately deposit coatings from filaments and the surrounding plasma phase can be helpful to better understand the processes occurring during plasma polymerization in filamentary DBD.

A new alternative tool to analyse glycosylation in pharmaceutical proteins based on infrared spectroscopy combined with nonlinear support vector regression.

Almost 60% of commercialized pharmaceutical proteins are glycosylated. Glycosylation is considered a critical quality attribute, as it affects the stability, bioactivity and safety of proteins. Hence, the development of analytical methods to characterise the composition and structure of glycoproteins is crucial. Currently, existing methods are time-consuming, expensive, and require significant sample preparation steps, which can alter the robustness of the analyses. In this work, we suggest the use of a fast, direct, and simple Fourier transform infrared spectroscopy (FT-IR) combined with a chemometric strategy to address this challenge. In this context, a database of FT-IR spectra of glycoproteins was built, and the glycoproteins were characterised by reference methods (MALDI-TOF, LC-ESI-QTOF and LC-FLR-MS) to estimate the mass ratio between carbohydrates and proteins and determine the composition in monosaccharides. The FT-IR spectra were processed first by Partial Least Squares Regression (PLSR), one of the most used regression algorithms in spectroscopy and secondly by Support Vector Regression (SVR). SVR has emerged in recent years and is now considered a powerful alternative to PLSR, thanks to its ability to flexibly model nonlinear relationships. The results provide clear evidence of the efficiency of the combination of FT-IR spectroscopy, and SVR modelling to characterise glycosylation in therapeutic proteins. The SVR models showed better predictive performances than the PLSR models in terms of RMSECV, RMSEP, R2CV, R2Pred and RPD. This tool offers several potential applications, such as comparing the glycosylation of a biosimilar and the original molecule, monitoring batch-to-batch homogeneity, and in-process control.

Protein Structural Denaturation Evaluated by MCR-ALS of Protein Microarray FTIR Spectra.

The loss of native structure is common in proteins. Among others, aggregation is one structural modification of particular importance as it is a major concern for the efficiency and safety of biotherapeutic proteins. Yet, recognizing the structural features associated with intermolecular bridging in a high-throughput manner remains a challenge. We combined here the use of protein microarrays spotted at a density of ca 2500 samples per cm2 and Fourier transform infrared (FTIR) imaging to analyze structural modifications in a set of 85 proteins characterized by widely different secondary structure contents, submitted or not to mild denaturing conditions. Multivariate curve resolution alternating least squares (MCR-ALS) was used to model a new spectral component appearing in the protein set subject to denaturing conditions. In the native protein set, 6 components were found to be sufficient to obtain good modeling of the spectra. Furthermore, their shape allowed them to be assigned to α-helix, ß-sheet, and other structures. Their content in each protein was correlated with the known secondary structure, confirming these assignments. In the denatured proteins, a new component was necessary and modeled by MCR-ALS. This new component could be assigned to the intermolecular ß-sheet, bridging protein molecules. MCR-ALS, therefore, unveiled a potential spectroscopic marker of protein aggregation and allowed a semiquantitative evaluation of its content. Insight into other structural rearrangements was also obtained.

Macromolecular assembly and membrane activity of antimicrobial D,L-α-Cyclic peptides.

Antimicrobial peptides are viewed as a promising alternative to conventional antibiotics, as their activity through membrane targeting makes them less prone to resistance development. Among them, antimicrobial D,L-α-cyclic peptides (CPs) have been proposed as an alternative, specially due to their cyclic nature and to the presence of D-α-amino acids that increases their resistance to proteases. In present work, second generation D,L-α-cyclic peptides with proven antimicrobial activity are shown to form complex macromolecular assemblies in the presence of membranes. We addressed the CPs:membrane interactions through a combination of experimental techniques (DSC and ATR-FTIR) with coarse-grained molecular dynamics (CG-MD) simulations, aiming at understanding their interactions, macromolecular assemblies and eventually unveil their mechanism of action. DSC shows that the interaction depends heavily on the negatively charge content of the membrane and on lipid/peptide ratio, suggesting different mechanisms for the different peptides and lipid systems. CG-MD proved that CPs can self-assemble at the lipid surface as nanotubes or micellar aggregates, depending on the peptide, in agreement with ATR-FTIR results. Finally, our results shed light into possible mechanisms of action of the peptides with pending hydrocarbon tail, namely membrane extensive segregation and/or membrane disintegration through the formation of disk-like lipid/peptide aggregates.

Analysis of Glycoproteins by ATR-FTIR Spectroscopy: Comparative Assessment.

FTIR spectroscopy has been widely used to characterize biopharmaceuticals for many years, in particular to analyze protein structure. More recently, it was demonstrated to be a useful tool to study and compare protein samples in terms of glycosylation. Based on a spectral region specific to carbohydrate absorption, we present here a detailed protocol to compare the FTIR spectra of glycoproteins in terms of global glycosylation level and in terms of glycan composition. This FTIR information is compared to MS information. Both approaches yield consistent results but it appears FTIR analysis is easier and more rapid to perform comparisons.

Attenuated total reflection-Fourier transform infrared spectroscopy: a tool to characterize antimicrobial cyclic peptide-membrane interactions.

Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) has been used for the structural characterization of peptides and their interactions with membranes. Antimicrobial peptides (AMPs) are part of our immune system and widely studied in recent years. Many linear AMPs have been studied, but their cyclization was shown to enhance the peptide's activity. We have used cyclic peptides (CPs) of an even number of alternating D- and L-α-amino acids, an emerging class of potential AMPs. These CPs can adopt a flat-ring shape that can stack into an antiparallel structure, forming intermolecular hydrogen bonds between different units, creating a tubular ß-sheet structure - self-assembled cyclic peptide nanotubes (SCPNs). To get the structural information on peptides in solution and/or in contact with membranes, Amide I and II absorptions are used as they can adopt frequency and shape band characteristics that are influenced by the strength of existing hydrogen bonds between the amide CO and NH involved in secondary structures such as helix, ß-sheet or aperiodic structures. The combination of polarized lens with ATR-FTIR provides an important tool to study the orientation of peptides when interacting with lipid membranes as the information can be derived on the position relative to the membrane normal. This work shows how ATR-FTIR used together with polarized light was successfully used to characterize structurally two CPs (RSKSWPgKQ and RSKSWXC10KQ) in solution and upon interaction with negatively charged membranes of DMPG, assessing the formation and orientation of tubular structures (SCPNs) that were shown to be enhanced by the presence of the lipid membrane.

Evaluation of protein secondary structure from FTIR spectra improved after partial deuteration.

FTIR spectroscopy has become a major tool to determine protein secondary structure. One of the identified obstacle for reaching better predictions is the strong overlap of bands assigned to different secondary structures. Yet, while for instance disordered structures and α-helical structures absorb almost at the same wavenumber, the absorbance bands are differentially shifted upon deuteration, in part because exchange is much faster for disordered structures. We recorded the FTIR spectra of 85 proteins at different stages of hydrogen/deuterium exchange process using protein microarrays and infrared imaging for high throughput measurements. Several methods were used to relate spectral shape to secondary structure content. While in absolute terms, ß-sheet is always better predicted than α-helix content, results consistently indicate an improvement of secondary structure predictions essentially for the α-helix and the category called "Others" (grouping random, turns, bends, etc.) after 15 min of exchange. On the contrary, the ß-sheet fraction is better predicted in non-deuterated conditions. Using partial least square regression, the error of prediction for the α-helix content is reduced after 15-min deuteration. Further deuteration degrades the prediction. Error on the prediction for the "Others" structures also decreases after 15-min deuteration. Cross-validation or a single 25-protein test set result in the same overall conclusions.

Amino acid side chain contribution to protein FTIR spectra: impact on secondary structure evaluation.

Prediction of protein secondary structure from FTIR spectra usually relies on the absorbance in the amide I-amide II region of the spectrum. It assumes that the absorbance in this spectral region, i.e., roughly 1700-1500 cm-1 is solely arising from amide contributions. Yet, it is accepted that, on the average, about 20% of the absorbance is due to amino acid side chains. The present paper evaluates the contribution of amino acid side chains in this spectral region and the potential to improve secondary structure prediction after correcting for their contribution. We show that the ß-sheet content prediction is improved upon subtraction of amino acid side chain contributions in the amide I-amide II spectral range. Improvement is relatively important, for instance, the error of prediction of ß-sheet content decreases from 5.42 to 4.97% when evaluated by ascending stepwise regression. Other methods tested such as partial least square regression and support vector machine have also improved accuracy for ß-sheet content evaluation. The other structures such as α-helix do not significantly benefit from side chain contribution subtraction, in some cases prediction is even degraded. We show that co-linearity between secondary structure content and amino acid composition is not a main limitation for improving secondary structure prediction. We also show that, even though based on different criteria, secondary structures defined by DSSP and XTLSSTR both arrive at the same conclusion: only the ß-sheet structure clearly benefits from side chain subtraction. It must be concluded that side chain contribution subtraction benefit for the evaluation of other secondary structure contents is limited by the very rough description of side chain absorbance which does not take into account the variations related to their environment. The study was performed on a large protein set. To deal with the large number of proteins present, we worked on protein microarrays deposited on BaF2 slides and FTIR spectra were acquired with an imaging system.

FTIR Imaging of Protein Microarrays for High Throughput Secondary Structure Determination.

The paper introduces a new method designed for high-throughput protein structure determination. It is based on spotting proteins as microarrays at a density of ca. 2000-4000 samples per cm2 and recording Fourier transform infrared (FTIR) spectra by FTIR imaging. It also introduces a new protein library, called cSP92, which contains 92 well-characterized proteins. It has been designed to cover as well as possible the structural space, both in terms of secondary structures and higher level structures. Ascending stepwise linear regression (ASLR), partial least square (PLS) regression, and support vector machine (SVM) have been used to correlate spectral characteristics to secondary structure features. ASLR generally provides better results than PLS and SVM. The observation that secondary structure prediction is as good for protein microarray spectra as for the reference attenuated total reflection spectra recorded on the same samples validates the high throughput microarray approach. Repeated double cross-validation shows that the approach is suitable for the high accuracy determination of the protein secondary structure with root mean square standard error in the cross-validation of 4.9 ± 1.1% for α-helix, 4.6 ± 0.8% for ß-sheet, and 6.3 ± 2.2% for the "other" structures when using ASLR.

Searching for a Better Match between Protein Secondary Structure Definitions and Protein FTIR Spectra.

Obtaining protein secondary structure content from high-resolution structures requires definitions and thresholds for the various parameters involved, typically hydrogen bond energy or length/angle and backbone φ/ψ angles. Several definitions are currently used and can have a profound impact on secondary structure content. Fourier transform infrared (FTIR) spectroscopy has its own sensitivity to molecular geometry. It is, therefore, important to select a set of definitions that matches this sensitivity. Here, we used a new protein set consisting of 92 proteins designed for the calibration of spectroscopic methods. Spectra have been obtained from protein microarrays in a high throughput process. The potential for improving secondary structure predictions from FTIR spectra has been tested using 71 structures determined according to different definitions. The paper demonstrates that different secondary structure definitions result in large variations in secondary structure content that are not equivalent in view of the protein FTIR spectra. The prediction quality factor ζ can be improved by ca. 20-50% by selecting an adequate definition set. The results also indicate that the dictionary of secondary structure of proteins (DSSP) algorithm, which is currently widely used to evaluate protein secondary structure content, is a good choice when dealing with FTIR spectra.

SOMSpec as a General Purpose Validated Self-Organising Map Tool for Rapid Protein Secondary Structure Prediction From Infrared Absorbance Data.

A protein's structure is the key to its function. As protein structure can vary with environment, it is important to be able to determine it over a wide range of concentrations, temperatures, formulation vehicles, and states. Robust reproducible validated methods are required for applications including batch-batch comparisons of biopharmaceutical products. Circular dichroism is widely used for this purpose, but an alternative is required for concentrations above 10 mg/mL or for solutions with chiral buffer components that absorb far UV light. Infrared (IR) protein absorbance spectra of the Amide I region (1,600-1700 cm-1) contain information about secondary structure and require higher concentrations than circular dichroism often with complementary spectral windows. In this paper, we consider a number of approaches to extract structural information from a protein infrared spectrum and determine their reliability for regulatory and research purpose. In particular, we compare direct and second derivative band-fitting with a self-organising map (SOM) approach applied to a number of different reference sets. The self-organising map (SOM) approach proved significantly more accurate than the band-fitting approaches for solution spectra. As there is no validated benchmark method available for infrared structure fitting, SOMSpec was implemented in a leave-one-out validation (LOOV) approach for solid-state transmission and thin-film attenuated total reflectance (ATR) reference sets. We then tested SOMSpec and the thin-film ATR reference set against 68 solution spectra and found the average prediction error for helix (α + 310) and ß-sheet was less than 6% for proteins with less than 40% helix. This is quantitatively better than other available approaches. The visual output format of SOMSpec aids identification of poor predictions. We also demonstrated how to convert aqueous ATR spectra to and from transmission spectra for structure fitting. Fourier self-deconvolution did not improve the average structure predictions.

HER2 biosensing through SPR-envelope tracking in plasmonic optical fiber gratings.

In the biomedical detection context, plasmonic tilted fiber Bragg gratings (TFBGs) have been demonstrated to be a very accurate and sensitive sensing tool, especially well-adapted for biochemical detection. In this work, we have developed an aptasensor following a triple strategy to improve the overall sensing performances and robustness. Single polarization fiber (SPF) is used as biosensor substrate while the demodulation is based on tracking a peculiar feature of the lower envelope of the cladding mode resonances spectrum. This method is highly sensitive and yields wavelength shifts several tens of times higher than the ones reported so far based on the tracking of individual modes of the spectrum. An amplification of the response is further performed through a sandwich assay by the use of specific antibodies. These improvements have been achieved on a biosensor developed for the detection of the HER2 (Human Epidermal Growth Factor Receptor-2) protein, a relevant breast cancer biomarker. These advanced developments can be very interesting for point-of-care biomedical measurements in a convenient practical way.

Membrane targeting antimicrobial cyclic peptide nanotubes - an experimental and computational study.

The search of new antibiotics, particularly with new mechanisms of action, is nowadays a very important public health issue, due to the worldwide increase of resistant pathogens. Within this effort, much research has been done on antimicrobial peptides, because having the membrane as a target, they represent a new antibiotic paradigm. Among these, cyclic peptides (CPs) made of sequences of D- and L-amino acids have emerged as a new class of potential antimicrobial peptides, due to their expected higher resistance to protease degradation. These CPs are planar structures that can form Self-assembled Cyclic Peptide Nanotubes (SCPNs), in particular in the presence of lipid membranes. Aiming at understanding their mechanism of action, we used biophysical experimental techniques (DSC and ATR-FTIR) together with Coarse-grained molecular dynamics (CG-MD) simulations, to characterize the interaction of these CPs with model membranes of different electrostatic charges' contents. DSC results revealed that the CPs show a strong interaction with negatively charged membranes, with differences in the strength of interactions depending on peptide and on membrane charge content, at odds with no or mild interactions with zwitterionic membranes. ATR-FTIR suggested that the peptides self-assemble at the membrane surface, adopting mainly a ß-structure. The experiments with polarized light showed that in most cases they lie parallel to the membrane surface, but other forms and orientations are also apparent, depending on peptide structure and lipid:peptide ratio. The nanotube formation and orientation, as well as the dependence on membrane charge were also confirmed by the CG-MD simulations. These provide detail on the position and interactions, in agreement with the experimental results. Based on the findings reported here, we could proceed to the design and synthesis of a second-generation CPs, based on CP2 (soluble peptide), with increased activity and reduced toxicity.

A convenient protein library for spectroscopic calibrations.

While several Raman, CD or FTIR spectral libraries are available for well-characterized proteins of known structure, proteins themselves are usually very difficult to acquire, preventing a convenient calibration of new instruments and new recording methods. The problem is particularly critical in the field of FTIR spectroscopy where numerous new methods are becoming available on the market. The present papers reports the construction of a protein library (cSP92) including commercially available products, that are well characterized experimentally for their purity and solubility in conditions compatible with the recording of FTIR spectra and whose high-resolution structure is available. Overall, 92 proteins were selected. These proteins cover well the CATH space at the level of classes and architectures. In terms of secondary structure content, an analysis of their high-resolution structure by DSSP shows that the mean content in the different secondary structures present in cSP92 is very similar to the mean content found in the PDB. The 92-protein set is analyzed in details for the distribution of helix length, number of strands in ß- sheets, length of ß-strands and amino acid content, all features that may be important for the interpretation of FTIR spectra.

FTIR spectroscopy as an analytical tool to compare glycosylation in therapeutic monoclonal antibodies.

Glycosylation is the most common protein post-translational modification (PTM), especially in biopharmaceuticals. It is a critical quality attribute as it impacts product solubility, stability, half-life, pharmacokinetics and pharmacodynamics (PK/PD), bioactivity and safety (e.g. immunogenicity). Yet, current glycan analysis methods involve multiple and lengthy sample preparation steps which can affect the robustness of the analyses. The development of orthogonal, direct and simple method is therefore desirable. In this study, we suggest use of FTIR spectroscopy to address this challenge. Use of this technique, combined with statistical tools, to compare samples or batches in terms of glycosylation or monosaccharide profile, has three potential applications: to compare glycosylation of a biosimilar and the original (innovator) molecule, for monitoring of batch-to-batch consistency, and for in-process control. Fourteen therapeutic monoclonal antibodies (mAbs), one Fc-fusion protein and several other common glycoproteins have been used to demonstrate that FTIR spectra of glycoproteins display spectral variations according to their glycan and monosaccharide compositions. We show that FTIR spectra of glycoproteins provide a global but accurate fingerprint of the glycosylation profile. This fingerprint is not only sensitive to large differences such as the presence or absence of several monosaccharides but also to smaller modifications of the glycan and monosaccharide content.

Multimodal plasmonic optical fiber grating aptasensor.

Tilted fiber Bragg gratings (TFBGs) are now a well-established technology in the scientific literature, bringing numerous advantages, especially for biodetection. Significant sensitivity improvements are achieved by exciting plasmon waves on their metal-coated surface. Nowadays, a large part of advances in this topic relies on new strategies aimed at providing sensitivity enhancements. In this work, TFBGs are produced in both single-mode and multimode telecommunication-grade optical fibers, and their relative performances are evaluated for refractometry and biosensing purposes. TFBGs are biofunctionalized with aptamers oriented against HER2 (Human Epidermal Growth Factor Receptor-2), a relevant protein biomarker for breast cancer diagnosis. In vitro assays confirm that the sensing performances of TFBGs in multimode fiber are higher or identical to those of their counterparts in single-mode fiber, respectively, when bulk refractometry or surface biosensing is considered. These observations are confirmed by numerical simulations. TFBGs in multimode fiber bring valuable practical assets, featuring a reduced spectral bandwidth for improved multiplexing possibilities enabling the detection of several biomarkers.