scholarly journals DrugPred_RNA – Structure-Based Druggability Predictions for RNA Binding Sites

Author(s):  
Illimar Hugo Rekand ◽  
Ruth Brenk

RNA is an emerging target for drug discovery.<sup> </sup>However, like for proteins, not all RNA binding sites are equally suited to be addressed with conventional drug-like ligands. To this end, we have developed the structure-based druggability predicator DrugPred_RNA to identify druggable RNA binding sites. Due to the paucity of annotated RNA binding sites, the predictor was trained on protein pockets, albeit using only descriptors that can be calculated for both, RNA and protein binding sites. DrugPred_RNA performed well in discriminating druggable from less druggable binding sites for the protein set and delivered sensible predictions for selected RNA binding sites. Further, the majority of drug-like ligands contained in a data set of RNA-containing pockets were found in pockets predicted to be druggable, further adding confidence to the performance of DrugPred_RNA. The method is robust against conformational changes in the binding site and can contribute to direct drug discovery efforts for RNA targets

2021 ◽  
Author(s):  
Illimar Hugo Rekand ◽  
Ruth Brenk

RNA is an emerging target for drug discovery. However, like for proteins, not all RNA binding sites are equally suited to be addressed with conventional drug-like ligands. To this end, we have developed the structure-based druggability predicator DrugPred_RNA to identify druggable RNA binding sites. Due to the paucity of annotated RNA binding sites, the predictor was trained on protein pockets, albeit using only descriptors that can be calculated for both, RNA and protein binding sites. DrugPred_RNA performed well in discriminating druggable from less druggable binding sites for the protein set and delivered sensible predictions for selected RNA binding sites. In addition, the majority of drug-like ligands contained in a data set of RNA pockets were found in pockets predicted to be druggable, further adding confidence to the performance of DrugPred_RNA. The method is robust against conformational changes in the binding site and can contribute to direct drug discovery efforts for RNA targets.


Author(s):  
Illimar Hugo Rekand ◽  
Ruth Brenk

RNA is an emerging target for drug discovery.<sup> </sup>However, like for proteins, not all RNA binding sites are equally suited to be addressed with conventional drug-like ligands. To this end, we have developed the structure-based druggability predicator DrugPred_RNA to identify druggable RNA binding sites. Due to the paucity of annotated RNA binding sites, the predictor was trained on protein pockets, albeit using only descriptors that can be calculated for both, RNA and protein binding sites. DrugPred_RNA performed well in discriminating druggable from less druggable binding sites for the protein set and delivered sensible predictions for selected RNA binding sites. Further, the majority of drug-like ligands contained in a data set of RNA-containing pockets were found in pockets predicted to be druggable, further adding confidence to the performance of DrugPred_RNA. The method is robust against conformational changes in the binding site and can contribute to direct drug discovery efforts for RNA targets


2003 ◽  
Vol 185 (15) ◽  
pp. 4572-4577 ◽  
Author(s):  
Jian Qiao ◽  
Xueying Qiao ◽  
Yang Sun ◽  
Leonard Mindich

ABSTRACT The genomes of bacteriophage φ6 and its relatives are packaged through a mechanism that involves the recognition and translocation of the three different plus strand transcripts of the segmented double-stranded RNA genomes into preformed polyhedral structures called procapsids or inner cores. This packaging requires hydrolysis of nucleoside triphosphates and takes place in the order S-M-L. Packaging is dependent on unique sequences of about 200 nucleotides near the 5′ ends of plus strand transcripts of the three genomic segments. Changes in the pac sequences lead to loss of packaging ability but can be suppressed by second-site changes in RNA or amino acid changes in protein P1, the major structural protein of the procapsid. It appears that P1 is the determinant of the RNA binding sites, and it is suggested that the binding sites overlap or are conformational changes of the same domains.


2021 ◽  
Vol 15 ◽  
Author(s):  
Lichao Zhang ◽  
Zihong Huang ◽  
Liang Kong

Background: RNA-binding proteins establish posttranscriptional gene regulation by coordinating the maturation, editing, transport, stability, and translation of cellular RNAs. The immunoprecipitation experiments could identify interaction between RNA and proteins, but they are limited due to the experimental environment and material. Therefore, it is essential to construct computational models to identify the function sites. Objective: Although some computational methods have been proposed to predict RNA binding sites, the accuracy could be further improved. Moreover, it is necessary to construct a dataset with more samples to design a reliable model. Here we present a computational model based on multi-information sources to identify RNA binding sites. Method: We construct an accurate computational model named CSBPI_Site, based on xtreme gradient boosting. The specifically designed 15-dimensional feature vector captures four types of information (chemical shift, chemical bond, chemical properties and position information). Results: The satisfied accuracy of 0.86 and AUC of 0.89 were obtained by leave-one-out cross validation. Meanwhile, the accuracies were slightly different (range from 0.83 to 0.85) among three classifiers algorithm, which showed the novel features are stable and fit to multiple classifiers. These results showed that the proposed method is effective and robust for noncoding RNA binding sites identification. Conclusion: Our method based on multi-information sources is effective to represent the binding sites information among ncRNAs. The satisfied prediction results of Diels-Alder riboz-yme based on CSBPI_Site indicates that our model is valuable to identify the function site.


2018 ◽  
Vol 2018 (12) ◽  
pp. pdb.top097931 ◽  
Author(s):  
Jennifer C. Darnell ◽  
Aldo Mele ◽  
Ka Ying Sharon Hung ◽  
Robert B. Darnell

2008 ◽  
Vol 9 (Suppl 12) ◽  
pp. S6 ◽  
Author(s):  
Cheng-Wei Cheng ◽  
Emily Su ◽  
Jenn-Kang Hwang ◽  
Ting-Yi Sung ◽  
Wen-Lian Hsu

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5056-5056 ◽  
Author(s):  
Julia Fremerey ◽  
Pavel Morozov ◽  
Cindy Meyer ◽  
Aitor Garzia ◽  
Marianna Teplova ◽  
...  

Abstract Introduction Nucleolin (NCL) is a multifunctional, proliferation-associated factor that is overexpressed in many cancers and has already been demonstrated to play a profound role in leukemogenesis (Abdelmohsen and Gorospe, 2012; Shen et al., 2014). This can be linked to an increased synthesis of ribosomal RNA (rRNA). Thus, in leukemic cells, high expression levels of NCL contribute to malignant transformation through the increase of rRNA synthesis, which is required to sustain high levels of protein synthesis. Physiologically, NCL is a highly abundant, nucleolar RNA-binding protein that is implicated in the regulation of polymerase I transcription, post-transcriptional gene regulation, and plays a central role in ribosome biogenesis (Srivastava and Pollard, 1999). To further elucidate the exact role of NCL, this study focused on the characterization of the RNA-binding properties and protein-interactions of NCL in the context of ribosome biogenesis. Methods In order to identify transcriptome-wide binding sites and the cellular RNA targets of NCL, PAR-CLIP (photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation) and RIP-Seq (RNA immunoprecipitation sequencing) analyses were carried out in HEK 293 cells. PAR-CLIP is characterized by the incorporation of 4-thiouridine into newly transcribed RNA that causes a T to C conversion in the corresponding cDNA of crosslinked RNA (Hafner et al., 2010). The RNA-binding properties and the interaction of NCL with its identified RNA targets were elucidated by electrophoretic mobility shift assays, isothermal titration calorimetry and size-exclusion chromatography. To further define the role of NCL in ribosome biogenesis and the effect on precursor rRNA levels, siRNA mediated knockdown of NCL was employed followed by RNA sequencing. Furthermore, to characterize the interaction network of NCL on a proteome-wide level, mass-spectrometry was performed. Results This study focuses on the characterization of the RNA-binding properties of NCL and provides the first PAR-CLIP data set of NCL and identifies small nucleolar RNAs (snoRNA) and precursor rRNA as main targets of NCL, both of which were further confirmed by RIP-Seq analysis. Binding sites of NCL were identified in the 5'ETS (external transcribed spacer), after the first cleavage site, in ITS1 and ITS2 (internal transcribed spacer) within the precursor rRNA, indicating that NCL might play a role in the early processing steps of ribosome biogenesis within the nucleolus. Biochemical and structural binding analyses reveal that NCL interacts along the complete precursor region and shows high binding affinity to G/C/U-rich repeat sequences, which is in agreement with the nucleotide composition of the primary rRNA transcript. Moreover, we propose that siRNA mediated knockdown of NCL inhibits polymerase I transcription, which is shown by decreased expression levels of the precursor rRNA transcript. On the proteome-wide level, mass-spectrometry analysis of NCL identified several interaction partners including block of proliferation 1 (BOP1), DEAD-box RNA helicase 18 (DDX18), and 5'-3' exoribonuclease 2 (XRN2) and numerous ribosomal proteins of the small and the large ribosomal subunits including RPS24, RPL11, RPL35A, and RPL36. Conclusion This study provides evidence that NCL is highly associated with the process of ribosome biogenesis on the proteome- and transcriptome-wide level. Therefore, NCL might serve as a promising biochemical target in the context of increased ribosome biogenesis in cancer. Disclosures No relevant conflicts of interest to declare.


2018 ◽  
Author(s):  
Alina Munteanu ◽  
Neelanjan Mukherjee ◽  
Uwe Ohler

AbstractMotivationRNA-binding proteins (RBPs) regulate every aspect of RNA metabolism and function. There are hundreds of RBPs encoded in the eukaryotic genomes, and each recognize its RNA targets through a specific mixture of RNA sequence and structure properties. For most RBPs, however, only a primary sequence motif has been determined, while the structure of the binding sites is uncharacterized.ResultsWe developed SSMART, an RNA motif finder that simultaneously models the primary sequence and the structural properties of the RNA targets sites. The sequence-structure motifs are represented as consensus strings over a degenerate alphabet, extending the IUPAC codes for nucleotides to account for secondary structure preferences. Evaluation on synthetic data showed that SSMART is able to recover both sequence and structure motifs implanted into 3‘UTR-like sequences, for various degrees of structured/unstructured binding sites. In addition, we successfully used SSMART on high-throughput in vivo and in vitro data, showing that we not only recover the known sequence motif, but also gain insight into the structural preferences of the RBP.AvailabilitySSMART is freely available at https://ohlerlab.mdc-berlin.de/software/SSMART_137/[email protected]


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