Cell fishing: A similarity based approach and machine learning strategy for multiple cell lines-compound sensitivity prediction.

The prediction of cell-lines sensitivity to a given set of compounds is a very important factor in the optimization of in-vitro assays. To date, the most common prediction strategies are based upon machine learning or other quantitative structure-activity relationships (QSAR) based approaches. In the present research, we propose and discuss a straightforward strategy not based on any learning modelling but exclusively relying upon the chemical similarity of a query compound to reference compounds with annotated activity against cell lines. We also compare the performance of the proposed method to machine learning predictions on the same problem. A curated database of compounds-cell lines associations derived from ChemBL version 22 was created for algorithm construction and cross-validation. Validation was done using 10-fold cross-validation and testing the models on new data obtained from ChemBL version 25. In terms of accuracy, both methods perform similarly with values around 0.65 across 750 cell lines in 10-fold cross-validation experiments. By combining both methods it is possible to achieve 66% of correct classification rate in more than 26000 newly reported interactions comprising 11000 new compounds. A Web Service implementing the described approaches (both similarity and machine learning based models) is freely available at: http://bioquimio.udla.edu.ec/cellfishing

Horizontal transfer of carbohydrate metabolism genes into ectomycorrhizal Amanita

- The genus Amanita encompasses both symbiotic, ectomycorrhizal fungi and asymbiotic litter decomposers; all species are derived from asymbiotic ancestors. Symbiotic species are no longer able to degrade plant cell walls. The carbohydrate esterases family 1 (CE1s) is a diverse group of enzymes involved in carbon metabolism, including decomposition and carbon storage. CE1 genes of the ectomycorrhizal A. muscaria appear diverged from all other fungal homologues, and more similar to CE1s of bacteria, suggesting a horizontal gene transfer (HGT) event. - In order to test whether AmanitaCE1s were acquired horizontally, we built a phylogeny of CE1s collected from across the tree of life, and describe the evolution of CE1 genes among Amanita and relevant lineages of bacteria. - CE1s of symbiotic Amanita were very different from CE1s of asymbiotic Amanita, and are more similar to bacterial CE1s. The protein structure of one CE1 gene of A. muscaria matched a depolymerase that degrades the carbon storage molecule poly((R)-3-hydroxybutyrate) (PHB). Asymbiotic Amanita do not carry sequence or structural homologues of these genes. - The CE1s acquired through HGT may enable novel metabolisms, or play roles in signaling or defense. This is the first evidence for the horizontal transfer of carbohydrate metabolism genes into ectomycorrhizal fungi