PERCH Solutions Ltd

Kuopio, Finland

PERCH Solutions Ltd

Kuopio, Finland
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PubMed | University of Amsterdam, Butte College, PERCH Solutions Ltd, Dominican University at River Forest and 2 more.
Type: Journal Article | Journal: The Journal of organic chemistry | Year: 2016

The revision of the structure of the sesquiterpene aquatolide from a bicyclo[2.2.0]hexane to a bicyclo[2.1.1]hexane structure using compelling NMR data, X-ray crystallography, and the recent confirmation via full synthesis exemplify that the achievement of structural correctness depends on the completeness of the experimental evidence. Archived FIDs and newly acquired aquatolide spectra demonstrate that archiving and rigorous interpretation of 1D (1)H NMR data may enhance the reproducibility of (bio)chemical research and curb the growing trend of structural misassignments. Despite being the most accessible NMR experiment, 1D (1)H spectra encode a wealth of information about bonds and molecular geometry that may be fully mined by (1)H iterative full spin analysis (HiFSA). Fully characterized 1D (1)H spectra are unideterminant for a given structure. The corresponding FIDs may be readily submitted with publications and collected in databases. Proton NMR spectra are indispensable for structural characterization even in conjunction with 2D data. Quantum interaction and linkage tables (QuILTs) are introduced for a more intuitive visualization of 1D J-coupling relationships, NOESY correlations, and heteronuclear experiments. Overall, this study represents a significant contribution to best practices in NMR-based structural analysis and dereplication.

Laatikainen R.,University of Eastern Finland | Hassinen T.,University of Eastern Finland | Lehtivarjo J.,University of Eastern Finland | Tiainen M.,University of Eastern Finland | And 12 more authors.
Journal of Chemical Information and Modeling | Year: 2014

A fast 3D/4D structure-sensitive procedure was developed and assessed for the chemical shift prediction of protons bonded to sp3carbons, which poses the maybe greatest challenge in the NMR spectral parameter prediction. The LPNC (Linear Prediction with Nonlinear Corrections) approach combines three well-established multivariate methods viz. the principal component regression (PCR), the random forest (RF) algorithm, and the k nearest neighbors (kNN) method. The role of RF is to find nonlinear corrections for the PCR predicted shifts, while kNN is used to take full advantage of similar chemical environments. Two basic molecular models were also compared and discussed: in the MC model the descriptors are computed from an ensemble of the conformers found by conformational search based on Metropolis Monte Carlo (MMC) simulation; in the 4D model the conformational space was further expanded to the fourth dimension (time) by adding molecular dynamics to the MC conformers. An illustrative case study about the application and interpretation of the 4D prediction for a conformationally flexible structure, scopolamine, is described in detail. © 2014 American Chemical Society.

Mihaleva V.V.,Wageningen University | Mihaleva V.V.,Unilever | Mihaleva V.V.,Netherlands Metabolomics Center | Korhonen S.-P.,PERCH Solutions Ltd. | And 7 more authors.
Analytical and Bioanalytical Chemistry | Year: 2014

An automated quantum mechanical total line shape (QMTLS) fitting model was implemented for quantitative nuclear magnetic resonance (NMR)-based profiling of 42 metabolites in ultrafiltrated human serum samples. Each metabolite was described by a set of chemical shifts, J-couplings, and line widths. These parameters were optimized for each metabolite in each sample by iteratively minimizing the difference between the calculated and the experimental spectrum. In total, 92.0 to 98.1 % of the signal intensities in the experimental spectrum could be explained by the calculated spectrum. The model was validated by comparison to signal integration of metabolites with isolated signals and by means of standard additions. Metabolites present at average concentration higher than 50 μM were quantified with average absolute relative error less than 10 % when using different initial parameters for the fitting procedure. Furthermore, the biological applicability of the QMTLS model was demonstrated on 287 samples from an intervention study in 37 human volunteers undergoing an exercise challenge. Our automated QMTLS model was able to cope with the large dynamic range of metabolite concentrations in serum and proved to be suitable for high-throughput analysis. © Springer-Verlag Berlin Heidelberg 2014.

Mihaleva V.V.,Wageningen University | Mihaleva V.V.,Netherlands Metabolomics Center | Te Beek T.A.H.,Netherlands Bioinformatics Center | Te Beek T.A.H.,Radboud University Nijmegen | And 10 more authors.
Analytical Chemistry | Year: 2013

Identification of natural compounds, especially secondary metabolites, has been hampered by the lack of easy to use and accessible reference databases. Nuclear magnetic resonance (NMR) spectroscopy is the most selective technique for identification of unknown metabolites. High quality 1H NMR (proton nuclear magnetic resonance) spectra combined with elemental composition obtained from mass spectrometry (MS) are essential for the identification process. Here, we present MetIDB, a reference database of experimental and predicted 1H NMR spectra of 6000 flavonoids. By incorporating the stereochemistry, intramolecular interactions, and solvent effects into the prediction model, chemical shifts and couplings were predicted with great accuracy. A user-friendly web-based interface for MetIDB has been established providing various interfaces to the data and data-mining possibilities. For each compound, additional information is available comprising compound annotation, a 1H NMR spectrum, 2D and 3D structure with correct stereochemistry, and monoisotopic mass as well as links to other web resources. The combination of chemical formula and 1H NMR chemical shifts proved to be very efficient in metabolite identification, especially for isobaric compounds. Using this database, the process of flavonoid identification can then be significantly shortened by avoiding repetitive elucidation of already described compounds. © 2013 American Chemical Society.

Thiele H.,Bruker | McLeod G.,Bruker | Niemitz M.,Perch Solutions Ltd. | Kuhn T.,Bruker
Monatshefte fur Chemie | Year: 2011

Abstract: The new complete molecular confidence (CMC) concept explores the synergies of the analytical techniques LC-MS and NMR to obtain an estimation of the purity, concentration, and identity of chemical compounds. The high mass accuracy of the MS and MS/MS data provided by the new generation of ESI-TOF and ESI-Q-TOF mass spectrometers provides an accurate determination of molecular weight, which is used specifically for the structural verification and purity determination of substances. The high separation of the isotope profile for both MS and MS/MS spectra affords further dimensions of information to achieve precise molecular formula determination. By performing a complete NMR spectral analysis, the automated consistency analysis routine provides a safe assessment of the consistency between molecular structure and 1H NMR spectrum. The routine returns the fully assigned spectrum and the accurate NMR parameters extracted from the experimental data. Absolute quantification of a series of samples can be automatically performed including the whole workflow from sample setup, automatic NMR measurements, analysis, and spread-sheet reporting. This allows determining mass contents, relative amounts of substances, and purity. The strategy is explored on a set of 96 different pyrrole derivates. Graphical Abstract: [Figure not available: see fulltext.] © 2011 Springer-Verlag.

Pauli G.F.,University of Illinois at Chicago | Chen S.-N.,University of Illinois at Chicago | Lankin D.C.,University of Illinois at Chicago | Bisson J.,University of Illinois at Chicago | And 13 more authors.
Journal of Natural Products | Year: 2014

The present study demonstrates the importance of adequate precision when reporting the λ and J parameters of frequency domain 1H NMR (HNMR) data. Using a variety of structural classes (terpenoids, phenolics, alkaloids) from different taxa (plants, cyanobacteria), this study develops rationales that explain the importance of enhanced precision in NMR spectroscopic analysis and rationalizes the need for reporting Δλ and ΔJ values at the 0.1-1 ppb and 10 mHz level, respectively. Spectral simulations paired with iteration are shown to be essential tools for complete spectral interpretation, adequate precision, and unambiguous HNMR-driven dereplication and metabolomic analysis. The broader applicability of the recommendation relates to the physicochemical properties of hydrogen ( 1H) and its ubiquity in organic molecules, making HNMR spectra an integral component of structure elucidation and verification. Regardless of origin or molecular weight, the HNMR spectrum of a compound can be very complex and encode a wealth of structural information that is often obscured by limited spectral dispersion and the occurrence of higher order effects. This altogether limits spectral interpretation, confines decoding of the underlying spin parameters, and explains the major challenge associated with the translation of HNMR spectra into tabulated information. On the other hand, the reproducibility of the spectral data set of any (new) chemical entity is essential for its structure elucidation and subsequent dereplication. Handling and documenting HNMR data with adequate precision is critical for establishing unequivocal links between chemical structure, analytical data, metabolomes, and biological activity. Using the full potential of HNMR spectra will facilitate the general reproducibility for future studies of bioactive chemicals, especially of compounds obtained from the diversity of terrestrial and marine organisms. © 2014 The American Chemical Society and American Society of Pharmacognosy.

Aranibar N.,Bristol Myers Squibb | Borys M.,Bristol Myers Squibb | Mackin N.A.,Bristol Myers Squibb | Ly V.,Bristol Myers Squibb | And 9 more authors.
Journal of Biomolecular NMR | Year: 2011

NMR spectroscopy was used to evaluate growth media and the cellular metabolome in two systems of interest to biomedical research. The first of these was a Chinese hamster ovary cell line engineered to express a recombinant protein. Here, NMR spectroscopy and a quantum mechanical total line shape analysis were utilized to quantify 30 metabolites such as amino acids, Krebs cycle intermediates, activated sugars, cofactors, and others in both media and cell extracts. The impact of bioreactor scale and addition of anti-apoptotic agents to the media on the extracellular and intracellular metabolome indicated changes in metabolic pathways of energy utilization. These results shed light into culture parameters that can be manipulated to optimize growth and protein production. Second, metabolomic analysis was performed on the superfusion media in a common model used for drug metabolism and toxicology studies, in vitro liver slices. In this study, it is demonstrated that two of the 48 standard media components, choline and histidine are depleted at a faster rate than many other nutrients. Augmenting the starting media with extra choline and histidine improves the long-term liver slice viability as measured by higher tissues levels of lactate dehydrogenase (LDH), glutathione and ATP, as well as lower LDH levels in the media at time points out to 94 h after initiation of incubation. In both models, media components and cellular metabolites are measured over time and correlated with currently accepted endpoint measures. © 2011 Springer Science+Business Media B.V.

Napolitano J.G.,University of Illinois at Chicago | Lankin D.C.,University of Illinois at Chicago | McAlpine J.B.,University of Illinois at Chicago | Niemitz M.,PERCH Solutions Ltd. | And 3 more authors.
Journal of Organic Chemistry | Year: 2013

The characteristic signals observed in NMR spectra encode essential information on the structure of small molecules. However, extracting all of this information from complex signal patterns is not trivial. This report demonstrates how computer-aided spectral analysis enables the complete interpretation of 1D 1H NMR data. The effectiveness of this approach is illustrated with a set of organic molecules, for which replicas of their 1H NMR spectra were generated. The potential impact of this methodology on organic chemistry research is discussed. © 2013 American Chemical Society.

PubMed | PERCH Solutions Ltd.
Type: Journal Article | Journal: The Journal of organic chemistry | Year: 2015

The ability of certain oligomeric proanthocyanidins (OPACs) to enhance the biomechanical properties of dentin involves collagen cross-linking of the 1.3-4.5 nm wide space via protein-polyphenol interactions. A systematic interdisciplinary search for the bioactive principles of pine bark has yielded the trimeric PAC, ent-epicatechin-(48)-epicatechin-(2O7,48)-catechin (3), representing the hitherto most potent single chemical entity capable of enhancing dentin stiffness. Building the case from two congeneric PAC dimers, a detailed structural analysis decoded the stereochemistry, spatial arrangement, and chemical properties of three dentin biomodifiers. Quantum-mechanics-driven (1)H iterative full spin analysis (QM-HiFSA) of NMR spectra distinguished previously unrecognized details such as higher order J coupling and provided valuable information about 3D structure. Detection and quantification of H/D-exchange effects by QM-HiFSA identified C-8 and C-6 as (re)active sites, explain preferences in biosynthetic linkage, and suggest their involvement in dentin cross-linking activity. Mapping of these molecular properties underscored the significance of high precision in both (1)H and (13)C NMR spectroscopy. Occurring at low- to subppb levels, these newly characterized chemical shift differences in ppb are small but diagnostic measures of dynamic processes inherent to the OPAC pharmacophores and can help augment our understanding of nanometer-scale intermolecular interactions in biomodified dentin macromolecules.

Chemical standardization, along with morphological and DNA analysis ensures the authenticity and advances the integrity evaluation of botanical preparations. Achievement of a more comprehensive, metabolomic standardization requires simultaneous quantitation of multiple marker compounds. Employing quantitative

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