General molecular principles of ribosome biogenesis have been well explored in bacteria and eukaryotes. Collectively, these studies have revealed important functional differences and few similarities between these processes. Phylogenetic studies suggest that the information processing machineries from archaea and eukaryotes are evolutionary more closely related than their bacterial counterparts. These observations raise the question of how ribosome synthesis in archaea may proceed in vivo. In this study, we describe a versatile plasmid-based cis-acting reporter system allowing to analyze in vivo the consequences of ribosomal RNA mutations in the model archaeon Haloferax volcanii. Applying this system, we provide evidence that the bulge-helix-bulge motif enclosed within the ribosomal RNA processing stems is required for the formation of archaeal-specific circular-pre-rRNA intermediates and mature rRNAs. In addition, we have collected evidences suggesting functional coordination of the early steps of ribosome synthesis in H. volcanii. Together our investigation describes a versatile platform allowing to generate and functionally analyze the fate of diverse rRNA variants, thereby paving the way to better understand the cis-acting molecular determinants necessary for archaeal ribosome synthesis, maturation, stability and function.

Current FDA-approved kinase inhibitors cause diverse adverse effects, some of which are due to the mechanism-independent effects of these drugs. Identifying these mechanism-independent interactions could improve drug safety and support drug repurposing. Here, we develop iDTPnd (integrated Drug Target Predictor with negative dataset), a computational approach for large-scale discovery of novel targets for known drugs. For a given drug, we construct a positive structural signature as well as a negative structural signature that captures the weakly conserved structural features of drug-binding sites. To facilitate assessment of unintended targets, iDTPnd also provides a docking-based interaction score and its statistical significance. We confirm the interactions of sorafenib, imatinib, dasatinib, sunitinib, and pazopanib with their known targets at a sensitivity of 52% and a specificity of 55%. We also validate 10 predicted novel targets by using in vitro experiments. Our results suggest that proteins other than kinases, such as nuclear receptors, cytochrome P450, and MHC class I molecules, can also be physiologically relevant targets of kinase inhibitors. Our method is general and broadly applicable for the identification of protein–small molecule interactions, when sufficient drug–target 3D data are available. The code for constructing the structural signatures is available at https://sfb.kaust.edu.sa/Documents/iDTP.zip.

7Current FDA-approved kinase inhibitors cause diverse adverse effects, some of which are due to 2 8 the mechanism-independent effects of these drugs. Identifying these mechanism-independent 2 9 interactions could improve drug safety and support drug repurposing. We have developed 3 0 "iDTPnd", a computational approach for large-scale discovery of novel targets for known drugs. 1For a given drug, we construct a positive and a negative structural signature that captures the 3 2 weakly conserved structural features of drug binding sites. To facilitate assessment of unintended 3 3 targets iDTPnd also provides a docking-based interaction score and its statistical significance. 4We were able to confirm the interaction of sorafenib, imatinib, dasatinib, sunitinib, and 3 5 pazopanib with their known targets at a sensitivity and specificity of 52% and 55% respectively. 6We have validated 10 predicted novel targets, using in vitro experiments. Our results suggest that 3 7 proteins other than kinases, such as nuclear receptors, cytochrome P450 or MHC Class I 3 8 molecules can also be physiologically relevant targets of kinase inhibitors. Our method is general 3 9 and broadly applicable for the identification of protein-small molecule interactions, when 4 0 sufficient drug-target 3D data are available. 4 1 Keywords 4 2 Protein-drug interactions; iDTPnd; Kinase inhibitors; Drug binding site signatures 4 3