Discovery of RNA-Targeting Small Molecules: Challenges and Future Directions

IF 10.7 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
MedComm Pub Date : 2025-08-24 DOI:10.1002/mco2.70342
Zhengguo Cai, Hongli Ma, Fengcan Ye, Dingwei Lei, Zhenfeng Deng, Yongge Li, Ruichu Gu, Han Wen
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引用次数: 0

Abstract

RNA-targeting small molecules represent a transformative frontier in drug discovery, offering novel therapeutic avenues for diseases traditionally deemed undruggable. This review explores the latest advancements in the development of RNA-binding small molecules, focusing on the current obstacles and promising avenues for future research. We highlight innovations in RNA structure determination, including X-ray crystallography, nuclear magnetic resonance spectroscopy, and cryo-electron microscopy, which provide the foundation for rational drug design. The role of computational approaches, such as deep learning and molecular docking, is emphasized for enhancing RNA structure prediction and ligand screening efficiency. Additionally, we discuss the utility of focused libraries, DNA-encoded libraries, and small-molecule microarrays in identifying bioactive ligands, alongside the potential of fragment-based drug discovery for exploring chemical space. Emerging strategies, such as RNA degraders and modulators of RNA–protein interactions, are reviewed for their therapeutic promise. Specifically, we underscore the pivotal role of artificial intelligence and machine learning in accelerating discovery and optimizing RNA-targeted therapeutics. By synthesizing these advancements, this review aims to inspire further research and collaboration, unlocking the full potential of RNA-targeting small molecules to revolutionize treatment paradigms for a wide range of diseases.

Abstract Image

rna靶向小分子的发现:挑战与未来方向
rna靶向小分子代表了药物发现的变革前沿,为传统上被认为无法治疗的疾病提供了新的治疗途径。本文综述了rna结合小分子的最新研究进展,重点介绍了目前存在的障碍和未来研究的前景。我们重点介绍了在RNA结构测定方面的创新,包括x射线晶体学、核磁共振波谱学和低温电子显微镜,这些技术为合理的药物设计提供了基础。强调了深度学习和分子对接等计算方法在提高RNA结构预测和配体筛选效率方面的作用。此外,我们还讨论了聚焦文库、dna编码文库和小分子微阵列在识别生物活性配体方面的应用,以及基于片段的药物发现在探索化学空间方面的潜力。新兴策略,如RNA降解剂和RNA -蛋白相互作用调节剂,对其治疗前景进行了综述。具体来说,我们强调了人工智能和机器学习在加速发现和优化rna靶向治疗方面的关键作用。通过综合这些进展,本综述旨在激发进一步的研究和合作,释放rna靶向小分子的全部潜力,以彻底改变各种疾病的治疗模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.70
自引率
0.00%
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0
审稿时长
10 weeks
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