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'RNA walk' a novel approach to study RNA-RNA interactions between a small RNA and its target.

ABSTRACT: In this study we describe a novel method to investigate the RNA-RNA interactions between a small RNA and its target that we termed 'RNA walk'. The method is based on UV-induced AMT cross-linking in vivo followed by affinity selection of the hybrid molecules and mapping the intermolecular adducts by RT-PCR or real-time PCR. Domains carrying the cross-linked adducts fail to efficiently amplify by PCR compared with non-cross-linked domains. This method was calibrated and used to study the interaction between a special tRNA-like molecule (sRNA-85) that is part of the trypanosome signal recognition particle (SRP) complex and the ribosome. Four contact sites between sRNA-85 and rRNA were identified by 'RNA walk' and were further fine-mapped by primer extension. Two of the contact sites are expected; one contact site mimics the interaction of the mammalian Alu domain of SRP with the ribosome and the other contact sites include a canonical tRNA interaction. The two other cross-linked sites could not be predicted. We propose that 'RNA walk, is a generic method to map target RNA small RNAs interactions in vivo.

SUBMITTER: Lustig Y

PROVIDER: S-EPMC2800229 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

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'RNA walk' a novel approach to study RNA-RNA interactions between a small RNA and its target.

Lustig Yaniv Y Wachtel Chaim C Safro Mark M Liu Li L Michaeli Shulamit S

Nucleic acids research 20091023 1

In this study we describe a novel method to investigate the RNA-RNA interactions between a small RNA and its target that we termed 'RNA walk'. The method is based on UV-induced AMT cross-linking in vivo followed by affinity selection of the hybrid molecules and mapping the intermolecular adducts by RT-PCR or real-time PCR. Domains carrying the cross-linked adducts fail to efficiently amplify by PCR compared with non-cross-linked domains. This method was calibrated and used to study the interacti ...[more]

PMID: 19854950

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Project description:Most small molecule drugs interact with unintended, often unknown, biological targets and these off-target interactions may lead to both preclinical and clinical toxic events. Undesired off-target interactions are often not detected using current drug discovery assays, such as experimental polypharmacological screens. Thus, improvement in the early identification of off-target interactions represents an opportunity to reduce safety-related attrition rates during preclinical and clinical development. In order to better identify potential off-target interactions that could be linked to predictable safety issues, a novel computational approach to predict safety-relevant interactions currently not covered was designed and evaluated. These analyses, termed Off-Target Safety Assessment (OTSA), cover more than 7,000 targets (~35% of the proteome) and > 2,46,704 preclinical and clinical alerts (as of January 20, 2019). The approach described herein exploits a highly curated training set of >1 million compounds (tracking >20 million compound-structure activity relationship/SAR data points) with known in vitro activities derived from patents, journals, and publicly available databases. This computational process was used to predict both the primary and secondary pharmacological activities for a selection of 857 diverse small molecule drugs for which extensive secondary pharmacology data are readily available (456 discontinued and 401 FDA approved). The OTSA process predicted a total of 7,990 interactions for these 857 molecules. Of these, 3,923 and 4,067 possible high-scoring interactions were predicted for the discontinued and approved drugs, respectively, translating to an average of 9.3 interactions per drug. The OTSA process correctly identified the known pharmacological targets for >70% of these drugs, but also predicted a significant number of off-targets that may provide additional insight into observed in vivo effects. About 51.5% (2,025) and 22% (900) of these predicted high-scoring interactions have not previously been reported for the discontinued and approved drugs, respectively, and these may have a potential for repurposing efforts. Moreover, for both drug categories, higher promiscuity was observed for compounds with a MW range of 300 to 500, TPSA of ~200, and clogP ≥7. This computation also revealed significantly lower promiscuity (i.e., number of confirmed off-targets) for compounds with MW > 700 and MW<200 for both categories. In addition, 15 internal small molecules with known off-target interactions were evaluated. For these compounds, the OTSA framework not only captured about 56.8% of in vitro confirmed off-target interactions, but also identified the right pharmacological targets for 14 compounds as one of the top scoring targets. In conclusion, the OTSA process demonstrates good predictive performance characteristics and represents an additional tool with utility during the lead optimization stage of the drug discovery process. Additionally, the computed physiochemical properties such as clogP (i.e., lipophilicity), molecular weight, pKa and logS (i.e., solubility) were found to be statistically different between the approved and discontinued drugs, but the internal compounds were close to the approved drugs space in most part.

Dataset Information

'RNA walk' a novel approach to study RNA-RNA interactions between a small RNA and its target.

Publications

'RNA walk' a novel approach to study RNA-RNA interactions between a small RNA and its target.

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