RESUMEN
Nuclear magnetic resonance (NMR) is a powerful analytical tool which can be used for authenticating honey, at chemical constituent levels by enabling identification and quantification of the spectral patterns. However, it is still challenging, as it may be a person-centric analysis or a time-consuming process to analyze many honey samples in a limited time. Hence, automating the NMR spectral analysis of honey with the supervised machine learning models accelerates the analysis process and especially food chemistry researcher or food industry with non-NMR experts would benefit immensely from such advancements. Here, we have successfully demonstrated this technology by considering three major sugar adulterants, i.e., brown rice syrup, corn syrup, and jaggery syrup, in honey at varying concentrations. The necessary supervised machine learning classification analysis is performed by using logistic regression, deep learning-based neural network, and light gradient boosting machines schemes.
RESUMEN
A new class of NOAH NMR experiments (NOAH-AST and NOAH-ASTPS), with the abbreviations, A: 1,1-ADEQUATE, S: sensitivity improved version of multiplicity-edited (ME)-HSQC, T: TOCSY, and TPS: pure shift TOCSY, are reported to obtain complete chemical shift assignments of small organic molecules from a single NMR experiment. While NOAH-AST provides 13C-13C, 1H-13C, and 1H-1H connectivities for molecules with well resolved chemical shifts, NOAH-ASTPS experiments discern 1H-1H connectivities even in complex organic molecules such as steroids at ultra-high resolution. These methods are very flexible and allow to record data through non-uniform-sampling, which reduces the experimental time to a great extent. In order to make these methods friendly to non-NMR experts (especially organic chemists and natural product scientists), python scripts have been developed and they help researchers in using these methods.
RESUMEN
A novel G-SERF-PSYCHE-TOCSY (gradient encoded selective refocusing in pure shift yielded by chirp excitation version of total correlation spectroscopy) NMR pulse scheme has been proposed, which produces TOCSY chemical shift correlations, on one hand, and scalar coupling values for the spins scalarly coupled to irradiated resonances, by showing them as doublets along the indirect dimension, on the other. Therefore, recording such an experiment, for a group of spins with overlapping chemical shifts, in organic molecules can adequately provide scalar coupling information in a G-SERF manner along the indirect dimensions, and they can be assigned to particular spin pairs. Such COSY chemical shift correlations (which appear as doublets for the scalarly coupled spins) can be readily discriminated from the TOCSY peaks (which do not show such splitting) in the G-SERF-PSYCHE-TOCSY spectrum.
RESUMEN
The process of assembly and accumulation of the intrinsically disordered protein (IDP), alpha-synuclein (αSyn) into amyloid fibrils is a pathogenic process leading to several neurodegenerative disorders such as Parkinson's disease, multiple system atrophy and others. Although several molecules are known to inhibit αSyn fibrillization, the mechanism of inhibition is just beginning to emerge. Here, we report the inhibition of fibrillization of αSyn by Triphala, a herbal preparation in the traditional Indian medical system of Ayurveda. Triphala was found to be a rich source of polyphenols which are known to act as amyloid inhibitors. ThT fluorescence and TEM studies showed that Triphala inhibited the fibrillization of αSyn. However, it was observed that Triphala does not disaggregate preformed αSyn fibrils. Further, native-PAGE showed that Triphala reduces the propensity of αSyn to oligomerize during the lag phase of fibrillization. Our NMR results showed that certain stretches of residues in the N-terminal and NAC regions of αSyn play an anchor role in the self-association process of the protein, thereby providing mechanistic insights into the early events during αSyn fibrillization.
RESUMEN
Application of Non Uniform Sampling (NUS) along with Band-selective Excitation Short-Transient (BEST) NMR experiments has been demonstrated for obtaining the important residue-specific atomic level backbone chemical shift values in short durations of time. This application has been demonstrated with both well-folded (ubiquitin) and unfolded (α-synuclein) proteins alike. With this strategy, the experiments required for determining backbone chemical shifts can be performed very rapidly, i.e., in â¼2 hours of spectrometer time, and this data can be used to calculate the backbone folds of proteins using well established algorithms. This will be of great value for structural proteomic investigations on one hand, where the speed of structure determination is a limiting factor and for application in the study of slow kinetic processes involving proteins, such as fibrillization, on the other hand.
RESUMEN
Hybrid peptidic oligomers comprising natural and unnatural amino acid residues that can exhibit biomolecular folding and hydrogen-bonding mimicry have attracted considerable interest in recent years. While a variety of hybrid peptidic helices have been reported in the literature, other secondary structural patterns such as γ-turns and ribbons have not been well explored so far. The present work reports the design of novel periodic γ-turns in the oligomers of 1:1 natural-α/unnatural trans-ß-norborenene (TNAA) amino acid residues. Through DFT, NMR, and MD studies, it is convincingly shown that, in the mixed conformational pool, the heterogeneous backbone of the hybrid peptides preferentially adopt periodic 8-membered (pseudo γ-turn)/7-membered (inverse γ-turn) hydrogen bonds in both polar and non-polar solvent media. It is observed that the stereochemistry and local conformational preference of the ß-amino acid building blocks have a profound influence on accessing the specific secondary fold. These findings may be of significant relevance for the development of molecular scaffolds that facilitate desired positioning of functional side-chains.