Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis.

The phenols are structurally heterogeneous pollutants and they present a variety of modes of toxic action (MOA), including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles, and soft electrophiles. Because it is often difficult to determine correctly the mechanism of action of a compound, quantitative structure-activity relationship (QSAR) methods, which have proved their interest in toxicity prediction, can be used. In this work, several QSAR models for the prediction of MOA of 221 phenols to the ciliated protozoan Tetrahymena pyriformis, using Chemistry Development Kit descriptors, are reported. Four machine learning techniques (ML), k-nearest neighbours, support vector machine, classification trees, and artificial neural networks, have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. They showed global accuracy values between 95.9% and 97.7% and area under Receiver Operator Curve values between 0.978 and 0.998; additionally, false alarm rate values were below 8.2% for training set. In order to validate our models, cross-validation (10-folds-out) and external test-set were performed with good behaviour in all cases. These models, obtained with ML techniques, were compared with others previously reported by other researchers, and the improvement was significant.

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.

Polymorphisms at the Werner locus: II. 1074Leu/Phe, 1367Cys/Arg, longevity, and atherosclerosis.

Werner syndrome (WS) is a progeroid syndrome caused by autosomal recessive null mutations at the WRN locus. The WRN gene encodes a nuclear protein of 180 kD that contains both exonuclease and helicase domains. WS patients develop various forms of arteriosclerosis, particularly atherosclerosis, and medial calcinosis. The most common cause of death in Caucasian subjects with WS is myocardial infarction. Previous studies have identified specific polymorphisms within WRN that may modulate the risk of atherosclerosis. Population studies of the 1074Leu/Phe and 1367Cys/Arg polymorphisms were undertaken to evaluate the role of WRN in atherogenesis. Frequencies of the 1074Leu/Phe polymorphisms in Finnish and Mexican populations revealed an age-dependent decline of 1074Phe/Phe genotype. In Mexican newborns, but not in Finnish newborns, the 1074Leu/Phe and 1367Cys/ Arg polymorphisms were in linkage disequilibrium. Among coronary artery disease subjects, there was a tendency for the 1074Phe allele to be associated with coronary stenosis in a gene dose-dependent manner. Furthermore, the 1367Arg/Arg genotype predicted a lower degree of coronary artery occlusion, as measured by NV50, when compared to the 1367Cys/Cys or 1367Cys/Arg genotypes. However, these tendencies did not achieve statistical significance. Samples from Mexican patients with ischemic stroke showed a trend of haplotype frequencies different from that in a control group of Mexican adults. These data support the hypothesis that WRN may mediate not only WS, but may also modulate more common age-related disorders and, perhaps, a basic aging process.