Design and synthesis of paromomycin-related heterocycle-substituted aminoglycoside mimetics based on a mass spectrometry RNA-binding assay.
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Biomedical subjects
Publications and source records attributed to Richard H Griffey.
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RNA molecules fold into characteristic secondary and tertiary structures that account for their diverse functional activities. Many of these RNA structures, or certain structural motifs within them, are thought to recur in multiple genes within a single organism or across the same gene in several organisms and provide a common regulatory mechanism. Search algorithms, such as RNAMotif, can be used to mine nucleotide sequence databases for these repeating motifs. RNAMotif allows users to capture essential features of known structures in detailed descriptors and can be used to identify, with high specificity, other similar motifs within the nucleotide database. However, when the descriptor constraints are relaxed to provide more flexibility, or when there is very little a priori information about hypothesized RNA structures, the number of motif 'hits' may become very large. Exhaustive methods to search for similar RNA structures over these large search spaces are likely to be computationally intractable. Here we describe a powerful new algorithm based on evolutionary computation to solve this problem. A series of experiments using ferritin IRE and SRP RNA stem-loop motifs were used to verify the method. We demonstrate that even when searching extremely large search spaces, of the order of 10(23) potential solutions, we could find the correct solution in a fraction of the time it would have taken for exhaustive comparisons.
A technique for lead discovery vs RNA targets utilizing mass spectrometry (MS) screening methods is described. The structure-activity relationships (SAR) derived from assaying weak binding motifs allows the pharmacophores discovered to be elaborated via "SAR by MS" to higher affinity ligands. Application of this strategy to a subdomain of the 23S rRNA afforded a new class of compounds with functional activity.
Solution dissociation constants and changes in free energies associated with ligand binding to proteins have been measured in the gas phase using mass spectrometry.
The recent explosion in available bacterial genome sequences has initiated the need to improve an ability to annotate important sequence and structural elements in a fast, efficient and accurate manner. In particular, small non-coding RNAs (sRNAs) have been difficult to predict. The sRNAs play an important number of structural, catalytic and regulatory roles in the cell. Although a few groups have recently published prediction methods for annotating sRNAs in bacterial genome, much remains to be done in this field. Toward the goal of developing an efficient method for predicting unknown sRNA genes in the completed Escherichia coli genome, we adopted a bioinformatics approach to search for DNA regions that contain a sigma70 promoter within a short distance of a rho-independent terminator. Among a total of 227 candidate sRNA genes initially identified, 32 were previously described sRNAs, orphan tRNAs, and partial tRNA and rRNA operons. Fifty-one are mRNAs genes encoding annotated extremely small open reading frames (ORFs) following an acceptable ribosome binding site. One hundred forty-four are potentially novel non-translatable sRNA genes. Using total RNA isolated from E. coli MG1655 cells grown under four different conditions, we verified transcripts of some of the genes by Northern hybridization. Here we summarize our data and discuss the rules and advantages/disadvantages of using this approach in annotating sRNA genes on bacterial genomes.