ReviewPharmaceuticals (Basel, Switzerland)2025
Advances in Methods for Accurate Prediction of RNA-Small Molecule Binding Sites: From Isolated to AI-Integrated Strategies.
Review in Pharmaceuticals (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Computational Methods in Drug Development: From Molecular Modeling to Artificial Intelligence Technologies.Pharmaceuticals (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Predicting RNA-small molecule binding sites is essential for developing RNA-targeted drugs. Identifying these sites experimentally is often costly, making computational methods essential for drug discovery. While traditional approaches rely on limited information, recent AI advancements allow the integration of diverse features, improving prediction accuracy. As methods for predicting RNA-small molecule binding sites continue to evolve, this review provides a timely overview of recent developments. It systematically traces the evolution from physics-based, isolated strategies to AI-integrated approaches, explains the fundamental principles behind different features, compares the tendencies of various features between binding and non-binding sites, evaluates the performance of approaches using different feature combinations on various test sets, and outlines remaining opportunities and challenges, offering guidance for researchers aiming for higher prediction accuracy.
Indexed as
Identifiers
What OpenQuestion holds
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.