Interactions between protein and RNA play a key role in many biological processes in the gene expression pathway. Those interactions are mediated through a variety of RNA-binding protein domains, among them the highly abundant RNA recognition motif (RRM). Here we studied protein-RNA complexes from different RNA binding domain families solved by NMR and x-ray crystallography. Characterizing the structural properties of the RNA at the binding interfaces revealed an unexpected number of nucleotides with unusual RNA conformations, specifically found in RNA-RRM complexes. Moreover, we observed that the RNA nucleotides that are directly involved in interactions with the RRM domains, via hydrogen bonds and hydrophobic contacts, are significantly enriched with unique RNA conformations. Further examination of the sequences binding the RRM domain showed a preference for G nucleotides in syn conformation to precede or to follow U nucleotides in the anti-conformation, and U nucleotides in C2' endo conformation to precede U and G nucleotides possessing the more common C3' endo conformation. These findings imply a possible mode of RNA recognition by the RRM domains which enables the recognition of a wide variety of different RNA sequences and shapes. Overall, this study suggests an additional way by which the RRM domain recognizes its RNA target, involving a conformational readout.
Gene expression is a multi-step process involving many layers of regulation. The main regulators of the pathway are DNA and RNA binding proteins. While over the years, a large number of DNA and RNA binding proteins have been identified and extensively studied, it is still expected that many other proteins, some with yet another known function, are awaiting to be discovered. Here we present a new web server, BindUP, freely accessible through the website http://bindup.technion.ac.il/, for predicting DNA and RNA binding proteins using a non-homology-based approach. Our method is based on the electrostatic features of the protein surface and other general properties of the protein. BindUP predicts nucleic acid binding function given the proteins three-dimensional structure or a structural model. Additionally, BindUP provides information on the largest electrostatic surface patches, visualized on the server. The server was tested on several datasets of DNA and RNA binding proteins, including proteins which do not possess DNA or RNA binding domains and have no similarity to known nucleic acid binding proteins, achieving very high accuracy. BindUP is applicable in either single or batch modes and can be applied for testing hundreds of proteins simultaneously in a highly efficient manner.
RNA molecules have highly versatile structures that can fold into myriad conformations, providing many potential pockets for binding small molecules. The increasing number of available RNA structures, in complex with proteins, small ligands and in free form, enables the design of new therapeutically useful RNA-binding ligands. Here we studied RNA ligand complexes from 10 RNA groups extracted from the protein data bank (PDB), including adaptive and non-adaptive complexes. We analyzed the chemical, physical, structural and conformational properties of binding pockets around the ligand. Comparing the properties of ligand-binding pockets to the properties of computed pockets extracted from all available RNA structures and RNA-protein interfaces, revealed that ligand-binding pockets, mainly the adaptive pockets, are characterized by unique properties, specifically enriched in rare conformations of the nucleobase and the sugar pucker. Further, we demonstrate that nucleotides possessing the rare conformations are preferentially involved in direct interactions with the ligand. Overall, based on our comprehensive analysis of RNA-ligand complexes, we suggest that the unique conformations adopted by RNA nucleotides play an important role in RNA recognition by small ligands. We term the recognition of a binding site by a ligand via the unique RNA conformations “RNA conformational readout.” We propose that “conformational readout” is a general way by which RNA binding pockets are recognized and selected from an ensemble of different RNA states.
A single fungal metabolite induces far-reaching transcriptomic reprogramming in the plant, priming immune responses and defense, in contrast to its immunosuppressive effect on animal cells. While the negative effects of gliotoxin-producing Trichoderma strains on growth may be observed only under a particular set of laboratory conditions, gliotoxin-linked molecular patterns, including the potential for limited cell death, could strongly prime plant defense, even in mature soil-grown plants in which the same Trichoderma strain promotes growth.
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