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. 2012 Feb 24;17(3):2298-315.
doi: 10.3390/molecules17032298.

Experimental methodologies and evaluations of computer-aided drug design methodologies applied to a series of 2-aminothiophene derivatives with antifungal activities

Luciana Scotti  1 , Marcus Tullius Scotti, Edeltrudes de Oliveira Lima, Marcelo Sobral da Silva, Maria do Carmo Alves de Lima, Ivan da Rocha Pitta, Ricardo Olímpio de Moura, Jaismary Gonzaga Batista de Oliveira, Rayssa Marques Duarte da Cruz, Francisco Jaime Bezerra Mendonça Junior
Affiliations

Experimental methodologies and evaluations of computer-aided drug design methodologies applied to a series of 2-aminothiophene derivatives with antifungal activities

Luciana Scotti et al. Molecules. .

Abstract

Fifty 2-[(arylidene)amino]-4,5-cycloalkyl[b]thiophene-3-carbonitrile derivatives were screened for their in vitro antifungal activities against Candida krusei and Cryptococcus neoformans. Based on experimentally determined minimum inhibitory concentration (MIC) values, we conducted computer-aided drug design studies [molecular modelling, chemometric tools (CPCA, PCA, PLS) and QSAR-3D] that enable the prediction of three-dimensional structural characteristics that influence the antifungal activities of these derivatives. These predictions provide direction with regard to the syntheses of new derivatives with improved biological activities, which can be used as therapeutic alternatives for the treatment of fungal infections.

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Figures

Figure 1
Figure 1
General structure of the studied 2-aminothiophenes.
Figure 2
Figure 2
Ionisation potentials obtained for compounds 10, 22, 42, 2, 17 and 37.
Figure 3
Figure 3
Maps of interaction with the probes H2O, N1 and O obtained for inactive compounds 20 and 45 and for active compounds 15 and 17.
Figure 4
Figure 4
The relationship between the weights of the blocks of descriptors and the PC1 and PC2 components of the CPCA calculated using activities against C. krusei and C. neoformans.
Figure 5
Figure 5
Positions of objects in relation to PC1 and PC2 components. Blue represents more active compounds, lilac represents compounds that are moderately active, and pink represents less active compounds.
Figure 6
Figure 6
Graph of experimental versus calculated activity values, predicted by Equation (1).
Figure 7
Figure 7
Best fit model obtained in PLS.
See this image and copyright information in PMC

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