Combining Experimental with Computational Infrared and Mass Spectra for High-Throughput Nontargeted Chemical Structure Identification

Combined Experimental and Theoretical Insights: Spectroscopic and Molecular Investigation of Polyphenols from Fagonia indica via DFT, UV-vis, and FT-IR Approaches

This review deals with computational study of polyphenolic compounds of medicinal importance and interest for drug development. Herein, four polyphenolic compounds comprising catechol (1), caffeic acid (II), gallic acid (III), and pyrogallol (IV) have been isolated from a medicinal specie, Fagonia indica, by applying silica gel column chromatography. These compounds were identified by using gas chromatography-mass spectrometry (GC-MS) analysis and confirmed by geometric computational analysis. According to computational results, caffeic acid has shown the highest biological activation due to higher chemical softness, electronegativity (χ (eV) = -648.644), and electrostatic potential value (-8.424 × 10-2 to +8.424 × 10-2), while smaller values of chemical potential (-0.269), ELUMO (-0.080), and energy gap (ΔE = 0.149). The Mulliken atomic charges were calculated by using DFT/B3LYP with basis set 6-311G for the determination of active sites. The oxygen atom of catechol showed highest nucleophilic characteristic with a more negative charge (08 = -0.695), and pyrogallol indicated a strong electrophilic center at C14 = 0.415 with a higher positive charge. Moreover, UV-visible absorption spectra and a detailed study of vibrational frequencies for all phenolic compounds by employing the DFT approach with 3-21G, 6-31G, and 6-311G basis sets at the ground-state level showed the great agreement with experimental results. ANOVA has been applied to validate the theoretical data. Results suggest that compounds I-IV are suitable in diverse fields.