RESUMO
Multidrug resistance activities pECr50 of diverse strains of pathogenic fungus Penicillium digitatum against seven toxicants were studied by Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA). Fungal growth data (radii, circumferences, surface areas of fungal colonies, radius differences and ratios) in absence and presence of toxicants were used to derive eight new descriptors for 35 fungal strains. This data set was studied by PCA and HCA, and was correlated with the genome descriptor PCR for expression of gene CYP51 by Partial Least Squares (PLS) regression. Both analyses of pECr50 data and of fungal growth data have identified baseline resistance character, origin and target fruits of the fungal strains. In addition, the analysis of fungal growth data shows that fungal growth morphology is multivariate by nature, meaning that experimental data can be explored more intensely than in usual practice. Fungal growth is directly related to the production of enzyme P45014DM as the main resistance mechanism of P. digitatum against demethylation inhibitors. This is visible from a parsimonious PLS model (two principal components, Q2 = 0.985, R2 = 0.991, SEV = 0.028), validated with eight strains in the external validation set (Q2ev = 0.982, R2ev = 0.990, SECev = 0.025). Chemometric methods in exploring bioassay data are promising approaches to obtain useful information on fungal resistance and to apply these findings in practice.
Assuntos
Antifúngicos/toxicidade , Farmacorresistência Fúngica Múltipla , Fungicidas Industriais/toxicidade , Penicillium/efeitos dos fármacos , Análise por Conglomerados , Sistema Enzimático do Citocromo P-450/genética , Proteínas Fúngicas/genética , Penicillium/crescimento & desenvolvimento , Análise de Componente PrincipalRESUMO
Three hundred and nine carbon-carbon, carbon-nitrogen, and carbon-oxygen pi-bond lengths in high precision crystal structures of 31 purine and pyrimidine nucleobases were related to the Pauling pi-bond order, its analogues corrected to crystal packing effects, the numbers of non-hydrogen atoms around the bond, and the sum of atomic numbers of the bond atoms. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) demonstrated that the bond lengths in the nucleobases are three-dimensional phenomenon, characterized by nine distinct classes of bonds. Bond lengths predicted by Linear Regression models, Pauling Harmonic Potential Curves, Multiple Linear Regression, Principal Component, and Partial Least Squares Regression were compared to those calculated by molecular mechanics, semiempirical, and ab initio methods using PCA-HCA procedure on the calculated bond lengths, statistical parameters, and structural aromaticity indices. Incorporation of crystal packing effects into bond orders makes multivariate models to be competitive to semiempirical results, while further improvement of quantum chemical calculations can be achieved by geometry optimization of molecular clusters.
Assuntos
Modelos Químicos , Nucleosídeos de Purina/química , Nucleosídeos de Pirimidina/química , Bases de Dados Factuais , Modelos MolecularesRESUMO
Two hundred and twenty-three aromatic carbon-carbon bond lengths in high precision crystal structures containing 22 planar condensed benzenoid polycyclic aromatic hydrocarbons (PB-PAHs) were related to the Pauling pi-bond order, its analogue corrected to crystal packing effects, the number of hexagonal rings around the bond, and the numbers of carbons atoms around the bond at topological distance one and two. Principal Component Analysis (PCA) showed that the bond lengths in PB-PAHs are at least two-dimensional phenomenon, with well pronounced classification into 12 types of bonds, as confirmed with Hierachical Cluster Analysis (HCA). Consequently, Multiple Linear Regression (MLR) and Partial Least Squares (PLS) models were superior to univariate models, reducing the degeneration of the data set and improving the estimation of Julg's structural aromaticity index. The approximate regression models based on topological descriptors only were built for fast and easy prediction of bond lengths and bond orders in PB-PAHs.