Impact of imperfect data on protein secondary structure estimates from Far-UV circular dichroism spectra.

Circular dichroism [CD] is widely used to rapidly assess protein structure. Deconvolution of the far-UV CD spectrum is widely used to quantify the secondary structural elements [SSEs]. Multiple algorithms are available for this. Imperfections in the experimental CD spectra arising from spectral noise, instrument miscalibration, spectral offsets and non-linearity will impact on the accuracy and precision of derived secondary structure estimates. Analytical validation for use in regulated environments, such as biopharmaceuticals, requires that the impact of imperfect data on these estimates be understood. Limited information on the impact of poor data were available. A series of noise-free simulated spectral datasets with modified intensity, wavelength, noise and intensity linearity and offsets were created from entries in the Protein Circular Dichroism Data Bank. These datasets were analysed using the BeStSel, on-line resource to estimate secondary structure. Data imperfections caused significant change in SSEs, but the spectral range is also important. This study emphasises the importance of analytical method validation and justifiable estimates of uncertainty when reporting results. The datasets created are made available as a resource to validate other secondary structure estimation programs.

Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis.

Predicting the mechanical properties of polymer materials using machine learning is essential for the design of next-generation of polymers. However, the strong relationship between the higher-order structure of polymers and their mechanical properties hinders the mechanical property predictions based on their primary structures. To incorporate information on higher-order structures into the prediction model, X-ray diffraction (XRD) can be used. This study proposes a strategy to generate appropriate descriptors from the XRD analysis of the injection-molded polypropylene samples, which were prepared under almost the same injection molding conditions. To this end, first, Bayesian spectral deconvolution is used to automatically create high-dimensional descriptors. Second, informative descriptors are selected to achieve highly accurate predictions by implementing the black-box optimization method using Ising machine. This approach was applied to custom-built polymer datasets containing data on homo- polypropylene and derived composite polymers with the addition of elastomers. Results show that reasonable accuracy of predictions for seven mechanical properties can be achieved using only XRD.

This study proposes a strategy to generate appropriate descriptors, which realize highly accurate predictions of mechanical properties via machine learning from the XRD analysis of the molded polypropylene samples.

A Methodology for Reconstructing Source Properties of a Conical Piezoelectric Actuator Using Array-Based Methods.

We investigated the force produced by a conical piezoelectric (PZT, lead zirconate titanate) transducer actuated by high voltage pulses (HVP) in contact with a steel transfer plate. Using elastic wave propagation theory in a semi-infinite plate, we aimed to quantify the magnitude and estimate the shape of the force-time function via the body waves produced in the transfer plate using the displacement field recorded on an array of 20 absolutely calibrated PZT receivers. We first calibrated the receiver array using glass capillary fracture. We proceeded to use a conical PZT transducer to actively produce a source at the origin, allowing us to study the displacement field produced on the now calibrated PZT receiver array. We studied two types of HVP: An impulsive and step source. The calibrated receiver array was used to estimate the general shape of the force-time functions for each type of HVP. From our hypothesized force-time functions we were able to estimate the peak force produced by the PZT actuator: The impulsive source generated a force of f peak = 2.90 ± 0.42 N and the step source generated f peak = 1.79 ± 0.30 N, respectively, for a peak applied voltage of 273 V. This translates to an applied force of ∼ 0.011 N/V and 0.007 N/V for the impulse and step force-time functions, respectively, which is similar to estimates found in the literature for other conical transducers in contact with metallic transfer media. This measurement was verified directly by independent measurements of the peak force f peak using a dynamic force transducer. We found that our methodology correctly estimated the magnitude of the force but is limited to transducers with incident angles θ < 53 ∘ . Beyond this angle, overestimates of the force were observed due to the lack of body wave energy produced by the source. These results allow us to quantitatively determine the forces produced by active PZT techniques using only the measurement of the displacement field captured on a calibrated conical PZT array. Quantitative understanding of active PZT sources additionally constrains the transfer functions approach, which is commonly used in the non-destructive testing of materials and in other fields, such as rock physics and laboratory seismology.

FIGS: Featured Ion-Guided Stoichiometry for Data-Independent Proteomics through Dynamic Deconvolution.

Data-independent acquisition (DIA) has significant advantages for mass spectrometry (MS)-based peptide quantification, while mixed spectra remain challenging for precise stoichiometry. We here choose to analyze the library spectra in specific sets preferentially and locally. Accordingly, the featured ions are defined as the fragment ions uniquely assigned to corresponding precursors in a given spectrum set, which are generated by dynamic deconvolution of the mixed mass spectra. Then, we present featured ion-guided stoichiometry (FIGS), a universal method for accurate and robust peptide quantification for the DIA-MS data. We validate the high performance on the quantification sensitivity, accuracy, and efficiency of FIGS. Notably, our FIGS dramatically improves the quantification accuracy for the full dynamic range, especially for low-abundance peptides.

Spectral deconvolution of redox species in the crotonyl-CoA-dependent NADH:ferredoxin oxidoreductase from Megasphaera elsdenii. A flavin-dependent bifurcating enzyme.

We have undertaken a spectral deconvolution of the three FADs of EtfAB/bcd to the spectral changes seen in the course of reduction, including the spectrally distinct anionic and neutral semiquinone states of electron-transferring and bcd flavins. We also demonstrate that, unlike similar systems, no charge-transfer complex is observed on titration of the reduced M. elsdenii EtfAB with NAD+. Finally, and significantly, we find that removal of the et FAD from EtfAB results in an uncrossing of the half-potentials of the bifurcating FAD that remains in the protein, as reflected in the accumulation of substantial FAD•- in the course of reductive titrations of the depleted EtfAB with sodium dithionite.

Amino-acid selective isotope labeling enables simultaneous overlapping signal decomposition and information extraction from NMR spectra.

Signal overlapping is a major bottleneck for protein NMR analysis. We propose a new method, stable-isotope-assisted parameter extraction (SiPex), to resolve overlapping signals by a combination of amino-acid selective isotope labeling (AASIL) and tensor decomposition. The basic idea of Sipex is that overlapping signals can be decomposed with the help of intensity patterns derived from quantitative fractional AASIL, which also provides amino-acid information. In SiPex, spectra for protein characterization, such as 15N relaxation measurements, are assembled with those for amino-acid information to form a four-order tensor, where the intensity patterns from AASIL contribute to high decomposition performance even if the signals share similar chemical shift values or characterization profiles, such as relaxation curves. The loading vectors of each decomposed component, corresponding to an amide group, represent both the amino-acid and relaxation information. This information link provides an alternative protein analysis method that does not require "assignments" in a general sense; i.e., chemical shift determinations, since the amino-acid information for some of the residues allows unambiguous assignment according to the dual selective labeling. SiPex can also decompose signals in time-domain raw data without Fourier transform, even in non-uniformly sampled data without spectral reconstruction. These features of SiPex should expand biological NMR applications by overcoming their overlapping and assignment problems.

A new strategy implementing mass spectrometry in the diagnosis of congenital disorders of N-glycosylation (CDG).

Objectives: Congenital disorders of N-glycosylation (CDG) are a large group of rare metabolic disorders caused by defects in the most common post-translational modification of proteins. CDGs are often difficult to diagnose as they are manifested with non-specific symptoms and signs. Analysis of serum transferrin (TRF) isoforms, as the classical procedure used to identify a CDG patient, enables to predict pathological steps in the N-linked glycosylation process. Methods: We devised a new strategy based on liquid chromatography-mass spectrometry (LC-MS) for the analysis of TRF isoforms by combining a simple and fast sample preparation with a specific chromatographic cleanup/separation step followed by mass-spectrometric measurement. Single TRF isoform masses were obtained through reconstruction of multiply charged electrospray data collected by quadrupole-MS technology. Hereby, we report the first analyzed serum samples obtained from 20 CDG patients and 100 controls. Results: The ratio of desialylated isoforms to total TRF was calculated for patients and controls. CDG-Type I patients showed higher amounts of bi-sialo isoform (range: 6.7-29.6%) compared to controls (<5.5%, mean percentage 3.9%). CDG-Type II pattern showed an increased peak of tri-sialo isoforms. The mean percentage of tri-sialo-TRF was 9.3% (range: 2.9-12.9%) in controls, which was lower than that obtained from two patients with COG5-CDG and MAN1B1-CDG (18.5 and 24.5%). Intraday and between-day imprecisions were less than 9 and 16%, respectively, for bi-sialo- and less than 3 and 6% for tri-sialo-TRF. Conclusions: This LC-MS-based approach provides a simple, sensitive and fast analytical tool for characterizing CDG disorders in a routine clinical biochemistry while improving diagnostic accuracy and speeding clinical decision-making.

Near-infrared in vitro measurements of photosystem I cofactors and electron-transfer partners with a recently developed spectrophotometer.

A kinetic-LED-array-spectrophotometer (Klas) was recently developed for measuring in vivo redox changes of P700, plastocyanin (PCy), and ferredoxin (Fd) in the near-infrared (NIR). This spectrophotometer is used in the present work for in vitro light-induced measurements with various combinations of photosystem I (PSI) from tobacco and two different cyanobacteria, spinach plastocyanin, cyanobacterial cytochrome c6 (cyt. c6), and Fd. It is shown that cyt. c6 oxidation contributes to the NIR absorption changes. The reduction of (FAFB), the terminal electron acceptor of PSI, was also observed and the shape of the (FAFB) NIR difference spectrum is similar to that of Fd. The NIR difference spectra of the electron-transfer cofactors were compared between different organisms and to those previously measured in vivo, whereas the relative absorption coefficients of all cofactors were determined by using single PSI turnover conditions. Thus, the (840 nm minus 965 nm) extinction coefficients of the light-induced species (oxidized minus reduced for PC and cyt. c6, reduced minus oxidized for (FAFB), and Fd) were determined with values of 0.207 ± 0.004, - 0.033 ± 0.006, - 0.036 ± 0.008, and - 0.021 ± 0.005 for PCy, cyt. c6, (FAFB) (single reduction), and Fd, respectively, by taking a reference value of + 1 for P700+. The fact that the NIR P700 coefficient is larger than that of PCy and much larger than that of other contributing species, combined with the observed variability in the NIR P700 spectral shape, emphasizes that deconvolution of NIR signals into different components requires a very precise determination of the P700 spectrum.

Synchronous Luminescence Spectroscopy as a Tool in the Discrimination and Characterization of Oral Cancer Tissue.

High incidence of oral cancer is primarily due to ongoing tobacco epidemic. In this work, synchronous luminescence spectroscopy (SLS) has been used to characterize and discriminate oral cancer tissue. Spectral deconvolution method is employed to compute the fluorescence intensity, peak wavelength, and full width half maxima for different endogenous fluorophores. The fluorescence measurements were made on 21 normal and 88 oral squamous cell carcinoma biopsy tissues. Besides, variations in relative concentration of collagen, NADH, and FAD, peak shifts and broadening of peaks are observed for tryptophan, NADH, and FAD, in oral cancer tissues indicating both biochemical and micro environmental changes at cellular level. Linear discriminant analysis showed that oral cancer tissue is discriminated with a sensitivity and specificity of 100% and 95.2% respectively.

Monitoring Breast Cancer Response to Treatment Using Stokes Shift Spectroscopy of Blood Plasma.

With the emerging trend of personalized cancer treatment, there is a need to develop noninvasive/minimally invasive techniques for treatment monitoring. In this regard, in this work fluorescence analysis of blood plasma of breast cancer patients has been used for the evaluation of response to treatment. This approach delivers information not only about the change in biochemical constituents but also about the altered metabolic pathway. Spectral deconvolution method is employed to compute the fluorescence intensity, peak wavelength, and full-width half maxima for different endogenous fluorophores. The fluorescence measurements were made on blood plasma collected from 10 normal subjects, 10 pre-treated cancer patients, and 10 post-treated patients. Besides, variations in relative concentration of tryptophan, collagen, NADH, and FAD, peak shifts and broadening of peaks are observed for tryptophan, NADH, and FAD, in blood plasma of pre-treated cancer patients indicating both biochemical and microenvironmental changes at cellular level. Further, the spectral profile of blood plasma of post-treated patients found to be similar to blood plasma of normal subjects. Linear discriminant analysis showed that pre-treated and post-treated breast cancer is discriminated with a sensitivity and specificity of 100% and 100% respectively.

Improvement of bioactive metabolite production in microbial cultures-A systems approach by OSMAC and deconvolution-based 1 HNMR quantification.

Traditionally, the screening of metabolites in microbial matrices is performed by monocultures. Nonetheless, the absence of biotic and abiotic interactions generally observed in nature still limit the chemical diversity and leads to "poorer" chemical profiles. Nowadays, several methods have been developed to determine the conditions under which cryptic genes are activated, in an attempt to induce these silenced biosynthetic pathways. Among those, the one strain, many compounds (OSMAC) strategy has been applied to enhance metabolic production by a systematic variation of growth parameters. The complexity of the chemical profiles from OSMAC experiments has required increasingly robust and accurate techniques. In this sense, deconvolution-based 1 HNMR quantification have emerged as a promising methodology to decrease complexity and provide a comprehensive perspective for metabolomics studies. Our present work shows an integrated strategy for the increased production and rapid quantification of compounds from microbial sources. Specifically, an OSMAC design of experiments (DoE) was used to optimize the microbial production of bioactive fusaric acid, cytochalasin D and 3-nitropropionic acid, and Global Spectral Deconvolution (GSD)-based 1 HNMR quantification was carried out for their measurement. The results showed that OSMAC increased the production of the metabolites by up to 33% and that GSD was able to extract accurate NMR integrals even in heavily coalescence spectral regions. Moreover, GSD-1 HNMR quantification was reproducible for all species and exhibited validated results that were more selective and accurate than comparative methods. Overall, this strategy up-regulated important metabolites using a reduced number of experiments and provided fast analyte monitor directly in raw extracts.

Untargeted/Targeted 2D Gas Chromatography/Mass Spectrometry Detection of the Total Volatile Tea Metabolome.

Identifying all analytes in a natural product is a daunting challenge, even if fractionated by volatility. In this study, comprehensive two-dimensional gas chromatography/mass spectrometry (GC×GC-MS) was used to investigate relative distribution of volatiles in green, pu-erh tea from leaves collected at two different elevations (1162 m and 1651 m). A total of 317 high and 280 low elevation compounds were detected, many of them known to have sensory and health beneficial properties. The samples were evaluated by two different software. The first, GC Image, used feature-based detection algorithms to identify spectral patterns and peak-regions, leading to tentative identification of 107 compounds. The software produced a composite map illustrating differences in the samples. The second, Ion Analytics, employed spectral deconvolution algorithms to detect target compounds, then subtracted their spectra from the total ion current chromatogram to reveal untargeted compounds. Compound identities were more easily assigned, since chromatogram complexities were reduced. Of the 317 compounds, for example, 34% were positively identified and 42% were tentatively identified, leaving 24% as unknowns. This study demonstrated the targeted/untargeted approach taken simplifies the analysis time for large data sets, leading to a better understanding of the chemistry behind biological phenomena.

ADAP-GC 3.2: Graphical Software Tool for Efficient Spectral Deconvolution of Gas Chromatography-High-Resolution Mass Spectrometry Metabolomics Data.

ADAP-GC is an automated computational workflow for extracting metabolite information from raw, untargeted gas chromatography-mass spectrometry metabolomics data. Deconvolution of coeluting analytes is a critical step in the workflow, and the underlying algorithm is able to extract fragmentation mass spectra of coeluting analytes with high accuracy. However, its latest version ADAP-GC 3.0 was not user-friendly. To make ADAP-GC easier to use, we have developed ADAP-GC 3.2 and describe here the improvements on three aspects. First, all of the algorithms in ADAP-GC 3.0 written in R have been replaced by their analogues in Java and incorporated into MZmine 2 to make the workflow user-friendly. Second, the clustering algorithm DBSCAN has replaced the original hierarchical clustering to allow faster spectral deconvolution. Finally, algorithms originally developed for constructing extracted ion chromatograms (EICs) and detecting EIC peaks from LC-MS data are incorporated into the ADAP-GC workflow, allowing the latter to process high mass resolution data. Performance of ADAP-GC 3.2 has been evaluated using unit mass resolution data from standard-mixture and urine samples. The identification and quantitation results were compared with those produced by ADAP-GC 3.0, AMDIS, AnalyzerPro, and ChromaTOF. Identification results for high mass resolution data derived from standard-mixture samples are presented as well.

An optimized band-target entropy minimization for mass spectral reconstruction of severely co-eluting and trace-level components.

Gas chromatography-mass spectrometry (GC-MS) is a versatile analytical method but its data is usually complicated by the presence of severely co-eluting and trace-level components. In this work, we introduce an optimized band-target entropy minimization approach for the analysis of complex mass spectral data. This new approach enables an automated mass spectral analysis which does not require any user-dependent inputs. Moreover, the approach provides improved sensitivity and accuracy for mass spectral reconstruction of severely co-eluting and trace-level components. The accuracy of our approach is compared to the automatic mass spectral deconvolution and identification system (AMDIS) with two controlled mixtures and a sample of Eucalyptus essential oil. Our approach was able to putatively identify 130 compounds in Eucalyptus essential oil, which was 46% in excess of that identified by AMDIS. This new approach is expected to benefit GC-MS analysis of complex mixtures such as biological samples and essential oils, in which the data are often complicated by co-eluting and trace-level components. Graphical abstract ᅟ.

Development of quantitative screen for 1550 chemicals with GC-MS.

With hundreds of thousands of chemicals in the environment, effective monitoring requires high-throughput analytical techniques. This paper presents a quantitative screening method for 1550 chemicals based on statistical modeling of responses with identification and integration performed using deconvolution reporting software. The method was evaluated with representative environmental samples. We tested biological extracts, low-density polyethylene, and silicone passive sampling devices spiked with known concentrations of 196 representative chemicals. A multiple linear regression (R2 = 0.80) was developed with molecular weight, logP, polar surface area, and fractional ion abundance to predict chemical responses within a factor of 2.5. Linearity beyond the calibration had R2 > 0.97 for three orders of magnitude. Median limits of quantitation were estimated to be 201 pg/µL (1.9× standard deviation). The number of detected chemicals and the accuracy of quantitation were similar for environmental samples and standard solutions. To our knowledge, this is the most precise method for the largest number of semi-volatile organic chemicals lacking authentic standards. Accessible instrumentation and software make this method cost effective in quantifying a large, customizable list of chemicals. When paired with silicone wristband passive samplers, this quantitative screen will be very useful for epidemiology where binning of concentrations is common. Graphical abstract A multiple linear regression of chemical responses measured with GC-MS allowed quantitation of 1550 chemicals in samples such as silicone wristbands.

Quantitative Evaluation of Broadband Photoacoustic Spectroscopy in the Infrared with an Optical Parametric Oscillator.

We evaluate the spectral resolution and the detection thresholds achievable for a photoacoustic spectroscopy (PAS) system in the broadband infrared wavelength region 3270 n m ≲ λ ≲ 3530 n m driven by a continuous wave optical parametric oscillator (OPO) with P ¯ ≈ 1.26 W . The absorption spectra, I PAS ( λ i ) , for diluted propane, ethane and methane test gases at low concentrations ( c ∼ 100 ppm ) were measured for ∼1350 discrete wavelengths λ i . The I PAS ( λ i ) spectra were then compared to the high resolution cross section data, σ FTIR , obtained by Fourier Transform Infrared Spectroscopy published in the HITRAN database. Deviations of 7.1(6)% for propane, 8.7(11)% for ethane and 15.0(14)% for methane with regard to the average uncertainty between I PAS ( λ i ) and the expected reference values based on σ FTIR were recorded. The characteristic absorption wavelengths λ res can be resolved with an average resolution of δ λ res ∼ 0.08 nm . Detection limits range between 7.1 ppb (ethane) to 13.6 ppb (methane). In an additional step, EUREQA, an artificial intelligence (AI) program, was successfully applied to deconvolute simulated PAS spectra of mixed gas samples at low limits of detection. The results justify a further development of PAS technology to support e.g., biomedical research.

Maximal clique method for the automated analysis of NMR TOCSY spectra of complex mixtures.

Characterization of the chemical components of complex mixtures in solution is important in many areas of biochemistry and chemical biology, including metabolomics. The use of 2D NMR total correlation spectroscopy (TOCSY) experiments has proven very useful for the identification of known metabolites as well as for the characterization of metabolites that are unknown by taking advantage of the good resolution and high sensitivity of this homonuclear experiment. Due to the complexity of the resulting spectra, automation is critical to facilitate and speed-up their analysis and enable high-throughput applications. To better meet these emerging needs, an automated spin-system identification algorithm of TOCSY spectra is introduced that represents the cross-peaks and their connectivities as a mathematical graph, for which all subgraphs are determined that are maximal cliques. Each maximal clique can be assigned to an individual spin system thereby providing a robust deconvolution of the original spectrum for the easy extraction of critical spin system information. The approach is demonstrated for a complex metabolite mixture consisting of 20 compounds and for E. coli cell lysate.

Tautomerism provides a molecular explanation for the mutagenic properties of the anti-HIV nucleoside 5-aza-5,6-dihydro-2'-deoxycytidine.

Viral lethal mutagenesis is a strategy whereby the innate immune system or mutagenic pool nucleotides increase the error rate of viral replication above the error catastrophe limit. Lethal mutagenesis has been proposed as a mechanism for several antiviral compounds, including the drug candidate 5-aza-5,6-dihydro-2'-deoxycytidine (KP1212), which causes A-to-G and G-to-A mutations in the HIV genome, both in tissue culture and in HIV positive patients undergoing KP1212 monotherapy. This work explored the molecular mechanism(s) underlying the mutagenicity of KP1212, and specifically whether tautomerism, a previously proposed hypothesis, could explain the biological consequences of this nucleoside analog. Establishing tautomerism of nucleic acid bases under physiological conditions has been challenging because of the lack of sensitive methods. This study investigated tautomerism using an array of spectroscopic, theoretical, and chemical biology approaches. Variable temperature NMR and 2D infrared spectroscopic methods demonstrated that KP1212 existed as a broad ensemble of interconverting tautomers, among which enolic forms dominated. The mutagenic properties of KP1212 were determined empirically by in vitro and in vivo replication of a single-stranded vector containing a single KP1212. It was found that KP1212 paired with both A (10%) and G (90%), which is in accord with clinical observations. Moreover, this mutation frequency is sufficient for pushing a viral population over its error catastrophe limit, as observed before in cell culture studies. Finally, a model is proposed that correlates the mutagenicity of KP1212 with its tautomeric distribution in solution.

ATR-FTIR characterization of generic brand-named and counterfeit sildenafil- and tadalafil-based tablets found on the Brazilian market.

Viagra and Cialis are among the most counterfeited medicines in many parts of the world, including Brazil. Despite the many studies that have been made regarding discrimination between genuine and counterfeit samples, most published works do not contemplate generic and similar versions of these medicines and also do not explore excipients/adjuvants contributions when characterizing genuine and suspected samples. In this study, we present our findings in exploring ATR-FTIR spectral profiles for characterizing both genuine and questioned samples of several generic and brand-name sildenafil- and tadalafil-based tablets available on the Brazilian market, including Viagra and Cialis. Multi-component spectral matching (deconvolution), objective visual comparison and correlation tests were used during analysis. Besides from allowing simple and quick identification of counterfeits, results obtained evidenced the strong spectral similarities between generic and brand-named tablets employing the same active ingredient and the indistinguishability between samples produced by the same manufacturer, generic or not. For all sildenafil-based and some tadalafil-based tablets tested, differentiation between samples from different manufacturers, attributed to slight variations in excipients/adjuvants proportions, was achieved, thus allowing the possibility of tracing an unknown/unidentified tablet back to a specific manufacturer.

Variability of some diterpene esters in coffee beverages as influenced by brewing procedures.

Several coffee brews, including classical and commercial beverages, were analyzed for their diterpene esters content (cafestol and kahweol linoleate, oleate, palmitate and stearate) by high performance liquid chromatography with diode array detector (HPLC-DAD) combined with spectral deconvolution. Due to the coelution of cafestol and kahweol esters at 225 nm, HPLC-DAD did not give accurate quantification of cafestol esters. Accordingly, spectral deconvolution was used to deconvolve the co-migrating profiles. Total cafestol and kahweol esters content of classical coffee brews ranged from 5-232 to 2-1016 mg/L, respectively. Commercial blends contained 1-54 mg/L of total cafestol esters and 2-403 mg/L of total kahweol esters. Boiled coffee had the highest diterpene esters content, while filtered and instant brews showed the lowest concentrations. However, individual diterpene esters content was not affected by brewing procedure as in terms of kahweol esters, kahweol palmitate was the main compound in all samples, followed by kahweol linoleate, oleate and stearate. Higher amounts of cafestol palmitate and stearate were also observed compared to cafestol linoleate and cafestol oleate. The ratio of diterpene esters esterified with unsaturated fatty acids to total diterpene esters was considered as measure of their unsaturation in analyzed samples which varied from 47 to 52%. Providing new information regarding the diterpene esters content and their distribution in coffee brews will allow a better use of coffee as a functional beverage.