Rationally selected basis proteins: a new approach to selecting proteins for spectroscopic secondary structure analysis

Oncogenic CALR mutant C-terminus mediates dual binding to the thrombopoietin receptor triggering complex dimerization and activation

Calreticulin (CALR) frameshift mutations represent the second cause of myeloproliferative neoplasms (MPN). In healthy cells, CALR transiently and non-specifically interacts with immature N-glycosylated proteins through its N-terminal domain. Conversely, CALR frameshift mutants turn into rogue cytokines by stably and specifically interacting with the Thrombopoietin Receptor (TpoR), inducing its constitutive activation. Here, we identify the basis of the acquired specificity of CALR mutants for TpoR and define the mechanisms by which complex formation triggers TpoR dimerization and activation. Our work reveals that CALR mutant C-terminus unmasks CALR N-terminal domain, rendering it more accessible to bind immature N-glycans on TpoR. We further find that the basic mutant C-terminus is partially α-helical and define how its α-helical segment concomitantly binds acidic patches of TpoR extracellular domain and induces dimerization of both CALR mutant and TpoR. Finally, we propose a model of the tetrameric TpoR-CALR mutant complex and identify potentially targetable sites.

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 β-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.

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 β-sheet, and 6.3 ± 2.2% for the "other" structures when using ASLR.

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 β-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 β-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 β-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 β-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.

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, β-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 β-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.

Bayesian inference assessment of protein secondary structure analysis using circular dichroism data - how much structural information is contained in protein circular dichroism spectra?

Circular dichroism spectroscopy is an important tool for determining the structural characteristics of biomolecules, particularly the secondary structure of proteins. In this paper we propose a Bayesian model that estimates the covariance structure within a measured spectrum and quantifies the uncertainty associated with the inferred secondary structures and characteristic spectra associated with each secondary structure type. Furthermore, we used tools from Bayesian model selection to determine the best secondary structure classification scheme and illustrate a technique for comparing whether or not two or more measured protein spectra share the same secondary structure. Our findings suggest that it is not possible to identify more than 3 distinct secondary structure classes from CD spectra above 175 nm. The inclusion of data from wavelengths between 175 and 200 nm did not substantially affect the ability to determine secondary structure fractions.

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.

Novel Bovine Serum Albumin Protein Backbone Reassembly Study: Strongly Twisted β-Sheet Structure Promotion upon Interaction with GO-PAMAM

This study investigates the formation of a graphene oxide-polyamidoamine dendrimer complex (GO-PAMAM) and its association and interaction with bovine serum albumin (BSA). Fourier-transform infrared spectrometry and X-ray photoelectron spectrometry indicated the formation of covalent linkage between the GO surface and PAMAM with 7.22% nitrogen content in the GO-PAMAM sample, and various interactions between BSA and GO-PAMAM, including π-π* interactions at 291.5 eV for the binding energy value. Thermogravimetric analysis highlighted the increasing thermal stability throughout the modification process, from 151 to 192 °C for the 10% weight loss temperature. Raman spectrometry and X-ray diffraction analysis were used in order to examine the complexes’ assembly, showing a prominent (0 0 2) lattice in GO-PAMAM. Dynamic light scattering tests proved the formation of stable graphenic and graphenic-protein aggregates. The secondary structure rearrangement of BSA after interaction with GO-PAMAM was investigated using circular dichroism spectroscopy. We have observed a shift from 10.9% β-sheet composition in native BSA to 64.9% β-sheet composition after the interaction with GO-PAMAM. This interaction promoted the rearrangement of the protein backbone, leading to strongly twisted β-sheet secondary structure architecture.

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 β- sheets, length of β-strands and amino acid content, all features that may be important for the interpretation of FTIR spectra.

Infrared imaging of high density protein arrays

We propose in this paper that protein microarrays could be analysed by infrared imaging in place of enzymatic or fluorescence labelling.

FTIR spectral signature of anticancer drugs. Can drug mode of action be identified?

Infrared spectroscopy has brought invaluable information about proteins and about the mechanism of action of enzymes. These achievements are difficult to transpose to living organisms as all biological molecules absorb in the mid infrared, with usually a high degree of overlap. Deciphering the contribution of each enzyme is therefore almost impossible. On the other hand, small changes in the infrared spectra of cells induced by environmental conditions or drugs may provide an accurate signature of the metabolic shift experienced by the cell as a response to a change in the growth medium. The present paper aims at reviewing the contribution of infrared spectroscopy to the description of small chemical changes that occur in cells when they are exposed to a drug. In particular, this review will focus on cancer cells and anti-cancer drugs. Results accumulated so far tend to demonstrate that infrared spectroscopy could be a very accurate descriptor of the mode of action of anticancer drugs. If confirmed, such a segmentation of potential drugs according to their "mode of action" will be invaluable for the discovery of new therapeutic molecules. This article is part of a Special Issue entitled: Physiological Enzymology and Protein Functions.

MARTINI bead form factors for the analysis of time-resolved X-ray scattering of proteins

Time-resolved small- and wide-angle X-ray scattering (SAXS and WAXS) methods probe the structural dynamics of proteins in solution. Although technologically advanced, these methods are in many cases limited by data interpretation. The calculation of X-ray scattering profiles is computationally demanding and poses a bottleneck for all SAXS/WAXS-assisted structural refinement and, in particular, for the analysis of time-resolved data. A way of speeding up these calculations is to represent biomolecules as collections of coarse-grained scatterers. Here, such coarse-graining schemes are presented and discussed and their accuracies examined. It is demonstrated that scattering factors coincident with the popular MARTINI coarse-graining scheme produce reliable difference scattering in the range 0 < q < 0.75 Å-1. The findings are promising for future attempts at X-ray scattering data analysis, and may help to bridge the gap between time-resolved experiments and their interpretation.

Electrostatic frequency shifts in amide I vibrational spectra: direct parameterization against experiment

The interpretation of protein amide I infrared spectra has been greatly assisted by the observation that the vibrational frequency of a peptide unit reports on its local electrostatic environment. However, the interpretation of spectra remains largely qualitative due to a lack of direct quantitative connections between computational models and experimental data. Here, we present an empirical parameterization of an electrostatic amide I frequency map derived from the infrared absorption spectra of 28 dipeptides. The observed frequency shifts are analyzed in terms of the local electrostatic potential, field, and field gradient, evaluated at sites near the amide bond in molecular dynamics simulations. We find that the frequency shifts observed in experiment correlate very well with the electric field in the direction of the C=O bond evaluated at the position of the amide oxygen atom. A linear best-fit mapping between observed frequencies and electric field yield sample standard deviations of 2.8 and 3.7 cm(-1) for the CHARMM27 and OPLS-AA force fields, respectively, and maximum deviations (within our data set) of 9 cm(-1). These results are discussed in the broader context of amide I vibrational models and the effort to produce quantitative agreement between simulated and experimental absorption spectra.

Structural aspects of amyloid formation

Amyloid fibrils are highly organized and generally insoluble protein aggregates rich in β secondary structure that can be formed by a wide range of sequences. They have been the object of intense scrutiny because their formation has been associated with a number of neurodegenerative disorders such as Alzheimer's, Parkinson's, Huntington's, and Creutzfeldt-Jakob's diseases. As a consequence of these efforts, much is now known about the properties of proteins that render them prone to form amyloid fibrils, about the mechanism of fibrillation, about the molecular structures of the fibrils, and about the forces that stabilize them. The relationship between the structural properties of the monomeric protein and those of the corresponding aggregate has been, in particular, intensively studied. In this chapter, we will provide an account of current knowledge on this intriguing relationship and provide the reader with key references about this topic.

Protein profile in vascular wall of atherosclerotic mice analyzed ex vivo using FT-IR spectroscopy

The structure of proteins in a tissue can undergo changes on account of disease state such as diabetes or atherosclerosis. In this work the protein profile in atherosclerotic tissue is monitored by FT-IR imaging coupled with Hierarchical Cluster Analysis (HCA). Additionally, a model for prediction of secondary structure of proteins content based on amide I and II range is used to show the distribution of analyzed proteins. A new protein class emerged in atherosclerotic tissue in the region of the plaque and additionally the plaque was found to be strongly mixed with smooth muscle cell. The calculated secondary structure contents of proteins in atherosclerotic tissue in comparison to healthy tissue showed an increase of structures related to beta-sheet (E and T) and a decrease of helical (H) and unassigned arrangements.

Identification of peptides derived from the human antimicrobial peptide LL-37 active against biofilms formed by Pseudomonas aeruginosa using a library of truncated fragments

Persistent Pseudomonas aeruginosa infections are a major cause of morbidity and mortality in cystic fibrosis (CF) patients and are linked to the formation of a biofilm. The development of new biofilm inhibition strategies is thus a major challenge. LL-37 is the only human antimicrobial peptide derived from cathelicidin. The effects on the P. aeruginosa PAO1 strain of synthetic truncated fragments of this peptide were compared with the effects of the original peptide. Fragments of LL-37 composed of 19 residues (LL-19, LL13-31, and LL7-25) inhibited biofilm formation. The strongest antibiofilm activity was observed with the peptides LL7-37 and LL-31, which decreased the percentage of biomass formation at a very low concentration. Some peptides were also active on the bacteria within an established biofilm. LL7-31, LL-31, and LL7-37 increased the uptake of propidium iodide (PI) by sessile bacteria. The peptide LL7-37 decreased the height of the biofilm and partly disrupted it. The peptides active within the biofilm had an infrared spectrum compatible with an α-helix. LL-37, but not the peptides LL7-31 and LL7-37, showed cellular toxicity by permeabilizing the eukaryotic plasma membrane (uptake of ethidium bromide and release of lactate dehydrogenase [LDH]). None of the tested peptides affected mitochondrial activity in eukaryotic cells. In conclusion, a 25-amino-acid peptide (LL7-31) displayed both strong antimicrobial and antibiofilm activities. The peptide was even active on cells within a preformed biofilm and had reduced toxicity toward eukaryotic cells. Our results also suggest the contribution of secondary structures (α-helix) to the activity of the peptides on biofilms.

Toxic prefibrillar α-synuclein amyloid oligomers adopt a distinctive antiparallel β-sheet structure

Parkinson's disease is an age-related movement disorder characterized by the presence in the mid-brain of amyloid deposits of the 140-amino-acid protein AS (α-synuclein). AS fibrillation follows a nucleation polymerization pathway involving diverse transient prefibrillar species varying in size and morphology. Similar to other neurodegenerative diseases, cytotoxicity is currently attributed to these prefibrillar species rather than to the insoluble aggregates. Nevertheless, the underlying molecular mechanisms responsible for cytotoxicity remain elusive and structural studies may contribute to the understanding of both the amyloid aggregation mechanism and oligomer-induced toxicity. It is already recognized that soluble oligomeric AS species adopt β-sheet structures that differ from those characterizing the fibrillar structure. In the present study we used ATR (attenuated total reflection)-FTIR (Fourier-transform infrared) spectroscopy, a technique especially sensitive to β-sheet structure, to get a deeper insight into the β-sheet organization within oligomers and fibrils. Careful spectral analysis revealed that AS oligomers adopt an antiparallel β-sheet structure, whereas fibrils adopt a parallel arrangement. The results are discussed in terms of regions of the protein involved in the early β-sheet interactions and the implications of such conformational arrangement for the pathogenicity associated with AS oligomers.

Protein refolding is required for assembly of the type three secretion needle

Pathogenic Gram-negative bacteria use a type three secretion system (TTSS) to deliver virulence factors into host cells. Although the order in which proteins incorporate into the growing TTSS is well described, the underlying assembly mechanisms are still unclear. Here we show that the TTSS needle protomer refolds spontaneously to extend the needle from the distal end. We developed a functional mutant of the needle protomer from Shigella flexneri and Salmonella typhimurium to study its assembly in vitro. We show that the protomer partially refolds from alpha-helix into beta-strand conformation to form the TTSS needle. Reconstitution experiments show that needle growth does not require ATP. Thus, like the structurally related flagellar systems, the needle elongates by subunit polymerization at the distal end but requires protomer refolding. Our studies provide a starting point to understand the molecular assembly mechanisms and the structure of the TTSS at atomic level.

Antiparallel beta-sheet: a signature structure of the oligomeric amyloid beta-peptide

AD (Alzheimer's disease) is linked to Abeta (amyloid beta-peptide) misfolding. Studies demonstrate that the level of soluble Abeta oligomeric forms correlates better with the progression of the disease than the level of fibrillar forms. Conformation-dependent antibodies have been developed to detect either Abeta oligomers or fibrils, suggesting that structural differences between these forms of Abeta exist. Using conditions which yield well-defined Abeta-(1-42) oligomers or fibrils, we studied the secondary structure of these species by ATR (attenuated total reflection)-FTIR (Fourier-transform infrared) spectroscopy. Whereas fibrillar Abeta was organized in a parallel beta-sheet conformation, oligomeric Abeta displayed distinct spectral features, which were attributed to an antiparallel beta-sheet structure. We also noted striking similarities between Abeta oligomers spectra and those of bacterial outer membrane porins. We discuss our results in terms of a possible organization of the antiparallel beta-sheets in Abeta oligomers, which may be related to reported effects of these highly toxic species in the amyloid pathogenesis associated with AD.

Protein secondary structure content in solution, films and tissues: redundancy and complementarity of the information content in circular dichroism, transmission and ATR FTIR spectra

The paper presents a simple and robust method to determine protein secondary structure from circular dichroism, transmission and attenuated total reflection (ATR) Fourier transform infrared spectra. It is found that the different spectroscopic methods bring valuable but roughly identical information on the secondary structure of proteins. ATR and transmission FTIR spectra display distinct differences, yet the secondary structure can be predicted from their spectra with roughly the same success. It is also found that one wavenumber or wavelength includes the large majority of the information correlated with secondary structure content and no more than 3 significant independent wavenumbers/wavelengths could be found for any of the spectroscopic data. This finding indicates that more complex linear combinations of the absorbance or ellipticities will not further improve secondary structure predictions. Furthermore, the information content in CD, transmission and ATR FTIR spectra is largely redundant. If combining CD and FTIR results in some improvement of structure prediction quality, the improvement is too modest to prompt spectroscopists to collect different spectroscopic data for structure prediction purposes. On the other hand, the data collected show that the quality of the FTIR spectrometers is such that biosensors or imaging methods sampling from 10(-9) to 10(-15) g yield spectra of sufficient quality to analyze protein secondary structure. These new techniques open the way to a new area of research, both in protein conformational response to ligand and imaging at sub-cellular scales.

Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations

BACKGROUND

A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available.

RESULTS

In this study we show that the sequence prediction methods have accuracies nearly comparable to those of spectroscopic methods. However, we also demonstrate that combining the spectroscopic and sequences techniques produces significant overall improvements in secondary structure determinations. In addition, combining the extra information content available from synchrotron radiation circular dichroism data with sequence methods also shows improvements.

CONCLUSION

Combining sequence prediction with experimentally determined spectroscopic methods for protein secondary structure content significantly enhances the accuracy of the overall results obtained.

A reference database for circular dichroism spectroscopy covering fold and secondary structure space

MOTIVATION

Circular Dichroism (CD) spectroscopy is a long-established technique for studying protein secondary structures in solution. Empirical analyses of CD data rely on the availability of reference datasets comprised of far-UV CD spectra of proteins whose crystal structures have been determined. This article reports on the creation of a new reference dataset which effectively covers both secondary structure and fold space, and uses the higher information content available in synchrotron radiation circular dichroism (SRCD) spectra to more accurately predict secondary structure than has been possible with existing reference datasets. It also examines the effects of wavelength range, structural redundancy and different means of categorizing secondary structures on the accuracy of the analyses. In addition, it describes a novel use of hierarchical cluster analyses to identify protein relatedness based on spectral properties alone. The databases are shown to be applicable in both conventional CD and SRCD spectroscopic analyses of proteins. Hence, by combining new bioinformatics and biophysical methods, a database has been produced that should have wide applicability as a tool for structural molecular biology.

The papaya Kunitz-type trypsin inhibitor is a highly stable beta-sheet glycoprotein

The papaya Kunitz-type trypsin inhibitor, a 24-kDa glycoprotein, was purified to homogeneity. The purified inhibitor stoichiometrically inhibits bovine trypsin in a 1:1 molar ratio. Circular dichroism and infrared spectroscopy analyses demonstrated that the inhibitor contains extensive beta-sheet structures. The inhibitor was found to retain its full inhibitory activity over a broad pH range (1.5-11.0) and temperature (up to 80 degrees C), besides being stable at very high concentrations of strong chemical denaturants (e.g., 5.5 M guanidine hydrochloride). The inhibitor retained its compact structure over the pH range analyzed as shown by 8-anilino-1-naphtalenesulfonic acid binding characteristics, excluding the formation of some relaxed or molten state. Exposure to 2.5 mM dithiothreitol for 120 min caused a 33% loss of the inhibitory activity, while a loss of 75% was obtained in the presence of 20 mM of dithiothreitol during the same time period. A complete loss of the inhibitory activity was observed after incubation with 50 mM dithiothreitol for 5 min. Incubation of the inhibitor with general proteases belonging to different families revealed its extraordinary resistance to proteolysis in comparison with the soybean trypsin inhibitor, the archetypal member of the Kunitz-type inhibitors family. The inhibitor also exhibited a remarkable resistance to proteolytic degradation against pepsin for at least a 24-h incubation period. Instead, the soybean inhibitor was completely degraded after 2 h incubation with this aspartic protease. All these data demonstrated the high stability of the papaya trypsin inhibitor.

Evaluation of the information content in infrared spectra for protein secondary structure determination

Fourier-transform infrared spectroscopy is a method of choice for the experimental determination of protein secondary structure. Numerous approaches have been developed during the past 15 years. A critical parameter that has not been taken into account systematically is the selection of the wavenumbers used for building the mathematical models used for structure prediction. The high quality of the current Fourier-transform infrared spectrometers makes the absorbance at every single wavenumber a valid and almost noiseless type of information. We address here the question of the amount of independent information present in the infrared spectra of proteins for the prediction of the different secondary structure contents. It appears that, at most, the absorbance at three distinct frequencies of the spectra contain all the nonredundant information that can be related to one secondary structure content. The ascending stepwise method proposed here identifies the relevance of each wavenumber of the infrared spectrum for the prediction of a given secondary structure and yields a particularly simple method for computing the secondary structure content. Using the 50-protein database built beforehand to contain as little fold redundancy as possible, the standard error of prediction in cross-validation is 5.5% for the alpha-helix, 6.6% for the beta-sheet, and 3.4% for the beta-turn.

Chemometric tools for classification and elucidation of protein secondary structure from infrared and circular dichroism spectroscopic measurements

Protein classification and characterization often rely on the information contained in the protein secondary structure. Protein class assignment is usually based on X-ray diffraction measurements, which need the protein in a crystallized form, or on NMR spectra, to obtain the structure of a protein in solution. Simple spectroscopic techniques, such as circular dichroism (CD) and infrared (IR) spectroscopies, are also known to be related to protein secondary structure, but they have seldom been used for protein classification. To see the potential of CD, IR, and combined CD/IR measurements for protein classification, unsupervised pattern recognition methods, Principal Component Analysis (PCA) and cluster analysis, are proposed first to check for natural grouping tendencies of proteins according to their measured spectra. Partial Least Squares Discriminant Analysis (PLS-DA), a supervised pattern recognition method, is used afterwards to test the possibility to model explicitly each protein class and to test these models in class assignment of unknown proteins. Determination of the protein secondary structure, understood as the prediction of the abundance of the different secondary structure motifs in the biomolecule, was carried out with the local regression method interval Partial Least Squares (iPLS). CD, IR, and CD/IR measurements were correlated to the fraction of the motif to be predicted, determined from X-ray measurements. iPLS builds models extracting the spectral information most correlated to a specific secondary motif and avoids the use of irrelevant spectral regions. Spectral intervals chosen by iPLS models provide structural information which can be used to confirm previous biochemical assignments or identify new motif-related spectral features. The predictive ability of the models built with the selected spectral regions has a quality similar to previous classical approaches.

Proteins in Action Monitored by Time-Resolved FTIR Spectroscopy

In the post genome era proteins coming into the focus of life sciences. X-ray structure analysis and NMR spectroscopy are established methods to determine the geometry of proteins. In order to determine the molecular reaction mechanism of proteins, time-resolved FTIR (trFTIR) difference spectroscopy emerges as a valuable tool. In this Minireview we describe the trFTIR difference spectroscopy and show its application on the light-driven proton pump bacteriorhodopsin (bR), the photosynthetic reaction center and the GTPase Ras, which is crucial in signal transduction. The main principles of the technique are presented, including a summary of triggering techniques, scan modes and analysis.

Columba: an integrated database of proteins, structures, and annotations

BACKGROUND

Structural and functional research often requires the computation of sets of protein structures based on certain properties of the proteins, such as sequence features, fold classification, or functional annotation. Compiling such sets using current web resources is tedious because the necessary data are spread over many different databases. To facilitate this task, we have created COLUMBA, an integrated database of annotations of protein structures.

DESCRIPTION

COLUMBA currently integrates twelve different databases, including PDB, KEGG, Swiss-Prot, CATH, SCOP, the Gene Ontology, and ENZYME. The database can be searched using either keyword search or data source-specific web forms. Users can thus quickly select and download PDB entries that, for instance, participate in a particular pathway, are classified as containing a certain CATH architecture, are annotated as having a certain molecular function in the Gene Ontology, and whose structures have a resolution under a defined threshold. The results of queries are provided in both machine-readable extensible markup language and human-readable format. The structures themselves can be viewed interactively on the web.

CONCLUSION

The COLUMBA database facilitates the creation of protein structure data sets for many structure-based studies. It allows to combine queries on a number of structure-related databases not covered by other projects at present. Thus, information on both many and few protein structures can be used efficiently. The web interface for COLUMBA is available at http://www.columba-db.de.

Monitoring protein-ligand interactions by time-resolved FTIR difference spectroscopy

Time-resolved FTIR difference spectroscopy is a valuable tool to monitor the dynamics of protein-ligand interactions, which selects out of the background absorbance of the whole sample the absorbance bands of the protein groups and of the ligands, which are involved in the protein reaction. The absorbance changes can be monitored with time-resolutions down to nanoseconds and followed then over nine orders of time up to seconds even in membrane proteins with the size of 100,000 Dalton. Here, we will discuss the various experimental setups. We will show new developments for sample cells and how to trigger a reaction within these cells. The kinetic analysis of the data will be discussed. A crucial step in the data analysis is the clear-cut band assignment to chemical groups of the protein and the ligand. This is done either by site directed mutagenesis or by isotopically labeling. Examples for band assignments will be presented in this chapter.

The optimization of protein secondary structure determination with infrared and circular dichroism spectra

We have used the circular dichroism and infrared spectra of a specially designed 50 protein database [Oberg, K.A., Ruysschaert, J.M. & Goormaghtigh, E. (2003) Protein Sci. 12, 2015-2031] in order to optimize the accuracy of spectroscopic protein secondary structure determination using multivariate statistical analysis methods. The results demonstrate that when the proteins are carefully selected for the diversity in their structure, no smaller subset of the database contains the necessary information to describe the entire set. One conclusion of the paper is therefore that large protein databases, observing stringent selection criteria, are necessary for the prediction of unknown proteins. A second important conclusion is that only the comparison of analyses run on circular dichroism and infrared spectra independently is able to identify failed solutions in the absence of known structure. Interestingly, it was also found in the course of this study that the amide II band has high information content and could be used alone for secondary structure prediction in place of amide I.