ArticleRNA biology2023
Characterizing RNA-binding ligands on structures, chemical information, binding affinity and drug-likeness.
Article in RNA biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- GRASSP: RNA language model-enhanced graph attention with adaptive gating for RNA-small molecule binding site prediction.Bioinformatics (Oxford, England) · 2026Article
- Article
- Eigenvalue Ratios Reveal Shared Binding Pocket Shapes in RNA and Protein Structures.Computational and structural biotechnology journal · 2026Article
- Advances in Methods for Accurate Prediction of RNA-Small Molecule Binding Sites: From Isolated to AI-Integrated Strategies.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Targeting the SARS-CoV-2 RNA Translation Initiation Element SL1 by Molecules of Low Molecular Weight.Journal of the American Chemical Society · 2025Article
- Contrastive pre-training and 3D convolution neural network for RNA and small molecule binding affinity prediction.Bioinformatics (Oxford, England) · 2024Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Recent studies suggest RNAs act as promising drug targets. However, limited development has been achieved in detecting RNA-ligand interactions. To guide the discovery of RNA-binding ligands, it is necessary to characterize them comprehensively, especially in the binding specificity, binding affinity and drug-like properties. We established a database, RNALID (http://biomed.nscc-gz.cn/RNALID/html/index.html#/database), which collects RNA-ligand interactions validated by low-throughput experiment. RNALID contains 358 RNA-ligand interactions. Comparing to the fellow database, 94.5% of ligands in RNALID are completely or partially novel collections, and 51.78% have novel two-dimensional (2D) structures. Through the analysis of ligand structure, binding affinity and cheminformatic parameters we found that multivalent (MV) ligands mainly binding to RNA repeats are more structurally conserved in both 2D and 3D structures than other ligand types, exhibit higher binding specificity and binding affinity than ligands binding to non-repeat RNAs, but deviate far from the Lipinski's rule of five. In contrary, small molecule (SM) ligands binding to virus RNA exhibit higher affinity and more resemble protein-ligands, but potentially possess low binding specificity. Further analysis on 28 detailed drug-likeness properties indicated that RNA-ligands' development need to balance between the binding affinity and the drug-likeness because of the significant linear co-relationship between the two. Comparing RNALID ligands to FDA-approved drugs and ligands without bioactivity indicated that RNA-binding ligands are different from them in chemical properties, structural properties and drug-likeness. Thus, characterizing the RNA-ligand interactions in RNALID in multiple respects provides new insights into discovering and designing druggable ligands binding with RNA.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.