Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model

A Model for Manganese interaction with Deinococcus radiodurans proteome network involved in ROS response and defense

A complex network of regulatory proteins takes part in the mechanism underlying the radioresistance of Deinoccocus radiodurans bacterium (DR). The interaction of Mn(II) ions with DR-proteins and peptides seems to be responsible for proteins protection from oxidative damage induced by Reactive Oxygen Species during irradiation. In the present work we describe a combined approach of bioinformatic strategies based on structural data and annotation to predict the Mn(II)-binding proteins encoded by the genome of DR and, in parallel, the same predictions for other bacteria were performed; the comparison revealed that, in most of the cases, the content of Mn(II)-binding proteins is significantly higher in radioresistant than in radiosensitive bacteria. Moreover, we report the in silico protein-protein interaction network of the putative Mn(II)-proteins, remodeled in order to enhance the knowledge about the impact of Mn-binding proteins in DR ability to protect also DNA from various damaging agents such as ionizing radiation, UV radiation and oxidative stress.