Dataset Information

Synthesis, spectroscopic (FT-IR, FT-Raman, NMR & UV-Vis), reactive (ELF, LOL, Fukui), drug likeness and molecular docking insights on novel 4-[3-(3-methoxy-phenyl)-3-oxo-propenyl]-benzonitrile by experimental and computational methods.

ABSTRACT: The spectroscopic analysis such as FT-IR, FT-Raman, UV-Vis and NMR are conducted for the synthesized molecule by both experimental and theoretical approach. The theoretical computations were achieved by DFT method with B3LYP functional and 6-311 ++ G (d, P) basis set. Firstly the geometrical parameters obtained by DFT are compared with the related experimental parameters. Experimental FT-IR and FT-Raman spectra of the title molecule have been acquired. The vibrational analysis is conducted and the assignments concerned to the observed bands are mentioned through the potential energy distribution (PED). The GIAO method was employed for theoretical NMR analysis and the results are compared with experimental chemical shifts. In accumulation to these analyses NLO, NBO, FMO and MEP analysis have been conducted to understand the nature of the molecule. ELF and LOL were performed. The drug likeness and molecular docking studies also conducted. The potency of inhibition of molecule against M^PRO and PL^PRO receptors has been performed using molecular docking studies.

SUBMITTER: Radder SB

PROVIDER: S-EPMC8632848 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Rat ear cartilage was studied using Fourier transform-infrared (FT-IR) microspectroscopy to expand the current knowledge which has been established for relatively more complex cartilage types. Comparison of the FT-IR spectra of the ear cartilage extracellular matrix (ECM) with published data on articular cartilage, collagen II and 4-chondroitin-sulfate standards, as well as of collagen type I-containing dermal collagen bundles (CBs) with collagen type II, was performed. Ear cartilage ECM glycosaminoglycans (GAGs) were revealed histochemically and as a reduction in ECM FT-IR spectral band heights (1140-820 cm-1) after testicular hyaluronidase digestion. Although ear cartilage is less complex than articular cartilage, it contains ECM components with a macromolecular orientation as revealed using polarization microscopy. Collagen type II and GAGs, which play a structural role in the stereo-arrangement of the ear cartilage, contribute to its FT-IR spectrum. Similar to articular cartilage, ear cartilage showed that proteoglycans add a contribution to the collagen amide I spectral region, a finding that does not recommend this region for collagen type II quantification purposes. In contrast to articular cartilage, the symmetric stretching vibration of -SO3- groups at 1064 cm-1 appeared under-represented in the FT-IR spectral profile of ear cartilage. Because the band corresponding to the asymmetric stretching vibration of -SO3- groups (1236-1225 cm-1) overlapped with that of amide III bands, it is not recommended for evaluation of the -SO3- contribution to the FT-IR spectrum of the ear cartilage ECM. Instead, a peak (or shoulder) at 1027-1016 cm-1 could be better considered for this intent. Amide I/amide II ratios as calculated here and data from the literature suggest that protein complexes of the ear cartilage ECM are arranged with a lower helical conformation compared to pure collagen II. The present results could motivate further studies on this tissue under pathological or experimental states involving ear cartilage.

Project description:One of the most important issues in the wine sector and prevention of adulterations of wines are discrimination of grape varieties, geographical origin of wine, and year of vintage. In this experimental research study, UV-Vis and FT-IR spectroscopic screening analytical approaches together with chemometric pattern recognition techniques were applied and compared in addressing two wine authentication problems: discrimination of (i) varietal and (ii) year of vintage of red wines produced in the same oenological region. UV-Vis and FT-IR spectra of red wines were registered for all the samples and the principal features related to chemical composition of the samples were identified. Furthermore, for the discrimination and classification of red wines a multivariate data analysis was developed. Spectral UV-Vis and FT-IR data were reduced to a small number of principal components (PCs) using principal component analysis (PCA) and then partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were performed in order to develop qualitative classification and regression models. The first three PCs used to build the models explained 89% of the total variance in the case of UV-Vis data and 98% of the total variance for FR-IR data. PLS-DA results show that acceptable linear regression fits were observed for the varietal classification of wines based on FT-IR data. According to the obtained LDA classification rates, it can be affirmed that UV-Vis spectroscopy works better than FT-IR spectroscopy for the discrimination of red wines according to the grape variety, while classification of wines according to year of vintage was better for the LDA based FT-IR data model. A clear discrimination of aged wines (over six years) was observed. The proposed methodologies can be used as accessible tools for the wine identity assurance without the need for costly and laborious chemical analysis, which makes them more accessible to many laboratories.

Dataset Information

Synthesis, spectroscopic (FT-IR, FT-Raman, NMR & UV-Vis), reactive (ELF, LOL, Fukui), drug likeness and molecular docking insights on novel 4-[3-(3-methoxy-phenyl)-3-oxo-propenyl]-benzonitrile by experimental and computational methods.

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