scholarly journals Isolation, Structure Elucidation and in Silico Prediction of Potential Drug-Like Flavonoids from Onosma chitralicum Targeted towards Functionally Important Proteins of Drug-Resistant Bad Bugs

Molecules ◽  
2021 ◽  
Vol 26 (7) ◽  
pp. 2048
Author(s):  
Shakeel Ahmad Khan ◽  
Shafi Ullah Khan ◽  
Fozia ◽  
Najeeb Ullah ◽  
Mohibullah Shah ◽  
...  

Admittedly, the disastrous emergence of drug resistance in prokaryotic and eukaryotic human pathogens has created an urgent need to develop novel chemotherapeutic agents. Onosma chitralicum is a source of traditional medicine with cooling, laxative, and anthelmintic effects. The objective of the current research was to analyze the biological potential of Onosma chitralicum, and to isolate and characterize the chemical constituents of the plant. The crude extracts of the plant prepared with different solvents, such as aqueous, hexane, chloroform, ethyl acetate, and butanol, were subjected to antimicrobial activities. Results corroborate that crude (methanol), EtoAc, and n-C6H14 fractions were more active against bacterial strains. Among these fractions, the EtoAc fraction was found more potent. The EtoAc fraction was the most active against the selected microbes, which was subjected to successive column chromatography, and the resultant compounds 1 to 7 were isolated. Different techniques, such as UV, IR, and NMR, were used to characterize the structures of the isolated compounds 1–7. All the isolated pure compounds (1–7) were tested for their antimicrobial potential. Compounds 1 (4′,8-dimethoxy-7-hydroxyisoflavone), 6 (5,3′,3-trihydroxy-7,4′-dimethoxyflavanone), and 7 (5′,7,8-trihydroxy-6,3′,4′-trimethoxyflavanone) were found to be more active against Staphylococcus aureus and Salmonella Typhi. Compound 1 inhibited S. typhi and S. aureus to 10 ± 0.21 mm and 10 ± 0.45 mm, whereas compound 6 showed inhibition to 10 ± 0.77 mm and 9 ± 0.20 mm, respectively. Compound 7 inhibited S. aureus to 6 ± 0.36 mm. Compounds 6 and 7 showed significant antibacterial potential, and the structure–activity relationship also justifies their binding to the bacterial enzymes, i.e., beta-hydroxyacyl dehydratase (HadAB complex) and tyrosyl-tRNA synthetase. Both bacterial enzymes are potential drug targets. Further, the isolated compounds were found to be active against the tested fungal strains. Whereas docking identified compound 7, the best binder to the lanosterol 14α-demethylase (an essential fungal cell membrane synthesizing enzyme), reported as an antifungal fluconazole binding enzyme. Based on our isolation-linked preliminary structure-activity relationship (SAR) data, we conclude that O. chitralicum can be a good source of natural compounds for drug development against some potential enzyme targets.

Author(s):  
Soghra Khabnadideh ◽  
Razieh Sabet ◽  
Hasti Pour Naghz ◽  
Masoumeh Divar

Breast cancer is the most common diagnosed cancer and the leading cause of related death in woman across the world. Nowadays, there are many effective chemotherapeutic agents used in the treatment of breast cancer, however due to the high side effects of these drugs, there is still an urgent need to develop new drugs for battle the disease. Computational chemistry is unique method in drug discovery which reduce cost. In this study 105 molecules were subjected to quantitative structure-activity relationship analysis to find the structure requirements for ligand binding. Then their structures were drowning in Hyperchem and also optimized, the structural invariants used in this study were those obtained from whole molecular structures: by both hyperchem and dragon. Four chemometrics method including MLR, FA-MLR, PCR and GA-PLS were employed to make connection between structural parameters and cytotoxic effects. GA-PLS showed Chemical, Topological, Randic molecular, Charge, 3D-Morse, Functional, Atom-centeredindices to be the most significant parameters on cytotoxic activity. The result of FA-MLR analysis revealed the effects of Chemical, Atom-centered, Galvez and Functional on the cytotoxic activity too. A comparison between the different statistical methods employed indicated that GA-PLS represented superior results and it could explain and predict 72% and 80% variances in the PIC50 data, respectively.


Planta Medica ◽  
2008 ◽  
Vol 74 (09) ◽  
Author(s):  
MA Brenzan ◽  
CV Nakamura ◽  
BPD Filho ◽  
T Ueda-Nakamura ◽  
MCM Young ◽  
...  

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