Functional characterization of the YmcB and YqeV tRNA methylthiotransferases of Bacillus subtilis

Methylthiotransferases (MTTases) are a closely related family of proteins that perform both radical-S-adenosylmethionine (SAM) mediated sulfur insertion and SAM-dependent methylation to modify nucleic acid or protein targets with a methyl thioether group (–SCH3). Members of two of the four known subgroups of MTTases have been characterized, typified by MiaB, which modifies N6-isopentenyladenosine (i6A) to 2-methylthio-N6-isopentenyladenosine (ms2i6A) in tRNA, and RimO, which modifies a specific aspartate residue in ribosomal protein S12. In this work, we have characterized the two MTTases encoded by Bacillus subtilis 168 and find that, consistent with bioinformatic predictions, ymcB is required for ms2i6A formation (MiaB activity), and yqeV is required for modification of N6-threonylcarbamoyladenosine (t6A) to 2-methylthio-N6-threonylcarbamoyladenosine (ms2t6A) in tRNA. The enzyme responsible for the latter activity belongs to a third MTTase subgroup, no member of which has previously been characterized. We performed domain-swapping experiments between YmcB and YqeV to narrow down the protein domain(s) responsible for distinguishing i6A from t6A and found that the C-terminal TRAM domain, putatively involved with RNA binding, is likely not involved with this discrimination. Finally, we performed a computational analysis to identify candidate residues outside the TRAM domain that may be involved with substrate recognition. These residues represent interesting targets for further analysis

Functional characterization of the YmcB and YqeV tRNA methylthiotransferases of Bacillus subtilis

Methylthiotransferases (MTTases) are a closely related family of proteins that perform both radical-S-adenosylmethionine (SAM) mediated sulfur insertion and SAM-dependent methylation to modify nucleic acid or protein targets with a methyl thioether group (–SCH3). Members of two of the four known subgroups of MTTases have been characterized, typified by MiaB, which modifies N6-isopentenyladenosine (i6A) to 2-methylthio-N6-isopentenyladenosine (ms2i6A) in tRNA, and RimO, which modifies a specific aspartate residue in ribosomal protein S12. In this work, we have characterized the two MTTases encoded by Bacillus subtilis 168 and find that, consistent with bioinformatic predictions, ymcB is required for ms2i6A formation (MiaB activity), and yqeV is required for modification of N6-threonylcarbamoyladenosine (t6A) to 2-methylthio-N6-threonylcarbamoyladenosine (ms2t6A) in tRNA. The enzyme responsible for the latter activity belongs to a third MTTase subgroup, no member of which has previously been characterized. We performed domain-swapping experiments between YmcB and YqeV to narrow down the protein domain(s) responsible for distinguishing i6A from t6A and found that the C-terminal TRAM domain, putatively involved with RNA binding, is likely not involved with this discrimination. Finally, we performed a computational analysis to identify candidate residues outside the TRAM domain that may be involved with substrate recognition. These residues represent interesting targets for further analysis

A thermodynamic definition of protein folds

Modern techniques in structural biology, like homology modeling, protein threading, protein fold classification, and homology detection have proven extremely useful. For example, they have provided us with evolutionary information about protein homology which has in some many cases lead directly to therapeutics. Due to the importance of these methods, augmenting or improving them may lead to significant advances in understanding proteins. These methods treat the high-resolution structure as a static entity upon which they operate, however we know that proteins are not static entities---they are polymers that exist in an enormous array of conformational states. Therefore, we propose to model the proteins from a statistical thermodynamic viewpoint based upon their average energetic properties. We show that this model can be used to (1) better characterize the partial unfolding process of proteins, and (2) reclassify the protein fold space from a new perspective

An Energetic Representation of Protein Architecture that Is Independent of Primary and Secondary Structure

AbstractProtein fold classification often assumes that similarity in primary, secondary, or tertiary structure signifies a common evolutionary origin. However, when similarity is not obvious, it is sometimes difficult to conclude that particular proteins are completely unrelated. Clearly, a set of organizing principles that is independent of traditional classification could be valuable in linking different structural motifs and identifying common ancestry from seemingly disparate folds. Here, a four-dimensional ensemble-based energetic space spanned by a diverse set of proteins was defined and its characteristics were contrasted with those of Cartesian coordinate space. Eigenvector decomposition of this energetic space revealed the dominant physical processes contributing to the more or less stable regions of a protein. Unexpectedly, those processes were identical for proteins with different secondary structure content and were also identical among different amino-acid types. The implications of these results are twofold. First, it indicates that excited conformational states comprising the protein native state ensemble, largely invisible upon inspection of the high-resolution structure, are the major determinant of the energetic space. Second, it suggests that folds dissimilar in sequence or structure could nonetheless be energetically similar if their respective excited conformational states are considered, one example of which was observed in the N-terminal region of the Arc repressor switch mutant. Taken together, these results provide a surface area-based framework for understanding folds in energetic terms, a framework that may eventually yield a means of identifying common ancestry among structurally dissimilar proteins