Identification Of Antifungal Agents Research Articles

Antifungal Activities of Streptomyces blastmyceticus Strain 12-6 Against Plant Pathogenic Fungi

Streptomyces blastmyceticus strain 12-6 was isolated from a forest soil sample of Cheonan area on the basis of strong antifungal activities against plant pathogenic fungi. Butanol extracts of the cultural filtrates were active against C. acutatum, C. coccodes, C. gloeosporioides, F. oxysporum, and T. roseum. Active fractions were prepared by thin layer chromatography using silica gel plate; 12-6-2 (Rf 0.36), 12-6-3 (Rf 0.44). Scanning electron microscopy showed that the active fractions caused a change in surface texture of fungal spores from smooth surface to wrinkled surface. The lethal effect on the spores of the active fractions varied from 56% to 100%. It was shown that the spores of C. acutatum were more sensitive to the antifungal fractions than the spores of F. oxysporum. Fluorescence staining using TOTO-1 indicated that the antifungal fractions could make the spores more sensitive to the fluorescence dye. Thus, it was suggested that antifungal agents prepared in this study exhibited the antifungal activity by damaging the plasma membrane of both fungal spores and hyphae. Identification of antifungal agents in the active fraction using GC-MS analysis revealed the presence of cyclo-(Leu-Pro) and 9-octadecenamide as major components that have already been known as antifungal substances.

QuBiLs-MAS method in early drug discovery and rational drug identification of antifungal agents

The QuBiLs-MAS approach is used for the in silico modelling of the antifungal activity of organic molecules. To this effect, non-stochastic (NS) and simple-stochastic (SS) atom-based quadratic indices are used to codify chemical information for a comprehensive dataset of 2478 compounds having a great structural variability, with 1087 of them being antifungal agents, covering the broadest antifungal mechanisms of action known so far. The NS and SS index-based antifungal activity classification models obtained using linear discriminant analysis (LDA) yield correct classification percentages of 90.73% and 92.47%, respectively, for the training set. Additionally, these models are able to correctly classify 92.16% and 87.56% of 706 compounds in an external test set. A comparison of the statistical parameters of the QuBiLs-MAS LDA-based models with those for models reported in the literature reveals comparable to superior performance, although the latter were built over much smaller and less diverse datasets, representing fewer mechanisms of action. It may therefore be inferred that the QuBiLs-MAS method constitutes a valuable tool useful in the design and/or selection of new and broad spectrum agents against life-threatening fungal infections.

Synthesis and Study of Some Newer Analogues ofQuinolin-8-ol as Potent Antimicrobial Agents

New series of 4-(substituted phenyl)-5-[(quinolin-8-yloxy) methyl]-4H-1,2,4-triazole-3-thiol(4a-c),N³-(4-substituted phenyl)-5-[(quinolin-8-yloxy) methyl]-4H-1,2,4-triazole-3,4-diamine(5a-c)andN-(4-substituted phenyl)-5-[(quinolin-8-yloxy) methyl]-1,3,4-thiadiazol-2-amine(6a-g)have been synthesized and the structures of the new compounds were established on the basis of IR,1H NMR spectral data.In vitroantimicrobial activity (MIC activity) was evaluated and compared with standard drugs of loxacin and ketoconazole. Compounds5aand6ein the series have shown interesting antibacterial activity against bothS. aureus(gram-positive) andE. coli(gram-negative) organisms. In this paper, we also describe studies leading to identification of antifungal agents. In the gratifying result, most of the compounds were found to have moderate antimicrobial activity.