Bereczki Zoltán, Benczik Bettina, Balogh Olivér M, Marton Szandra, Puhl Eszter, Pétervári Mátyás, Váczy-Földi Máté, Papp Zsolt Tamás, Makkos András, Glass Kimberly, Locquet Fabian, Euler Gerhild, Schulz Rainer, Ferdinandy Péter, Ágg Bence
Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary.
Center for Pharmacology and Drug Research & Development, Semmelweis University, Budapest, Hungary.
Br J Pharmacol. 2025 Jan;182(2):340-379. doi: 10.1111/bph.17302. Epub 2024 Sep 18.
Three types of highly promising small RNA therapeutics, namely, small interfering RNAs (siRNAs), microRNAs (miRNAs) and the RNA subtype of antisense oligonucleotides (ASOs), offer advantages over small-molecule drugs. These small RNAs can target any gene product, opening up new avenues of effective and safe therapeutic approaches for a wide range of diseases. In preclinical research, synthetic small RNAs play an essential role in the investigation of physiological and pathological pathways as silencers of specific genes, facilitating discovery and validation of drug targets in different conditions. Off-target effects of small RNAs, however, could make it difficult to interpret experimental results in the preclinical phase and may contribute to adverse events of small RNA therapeutics. Out of the two major types of off-target effects we focused on the hybridization-dependent, especially on the miRNA-like off-target effects. Our main aim was to discuss several approaches, including sequence design, chemical modifications and target prediction, to reduce hybridization-dependent off-target effects that should be considered even at the early development phase of small RNA therapy. Because there is no standard way of predicting hybridization-dependent off-target effects, this review provides an overview of all major state-of-the-art computational methods and proposes new approaches, such as the possible inclusion of network theory and artificial intelligence (AI) in the prediction workflows. Case studies and a concise survey of experimental methods for validating in silico predictions are also presented. These methods could contribute to interpret experimental results, to minimize off-target effects and hopefully to avoid off-target-related adverse events of small RNA therapeutics. LINKED ARTICLES: This article is part of a themed issue Non-coding RNA Therapeutics. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v182.2/issuetoc.
三种极具潜力的小RNA疗法，即小干扰RNA（siRNA）、微小RNA（miRNA）和反义寡核苷酸（ASO）的RNA亚型，相较于小分子药物具有优势。这些小RNA可以靶向任何基因产物，为多种疾病开辟了有效且安全的治疗新途径。在临床前研究中，合成小RNA作为特定基因的沉默剂，在生理和病理途径的研究中发挥着重要作用，有助于在不同条件下发现和验证药物靶点。然而，小RNA的脱靶效应可能会使临床前阶段的实验结果难以解释，并可能导致小RNA疗法出现不良事件。在两种主要的脱靶效应类型中，我们重点关注依赖杂交的脱靶效应，尤其是类似miRNA的脱靶效应。我们的主要目的是讨论几种方法，包括序列设计、化学修饰和靶点预测，以减少依赖杂交的脱靶效应，即使在小RNA疗法的早期开发阶段也应予以考虑。由于目前尚无预测依赖杂交的脱靶效应的标准方法，本综述概述了所有主要的最新计算方法，并提出了新的方法，例如在预测工作流程中可能纳入网络理论和人工智能（AI）。还介绍了案例研究以及用于验证计算机模拟预测的实验方法的简要概述。这些方法有助于解释实验结果，将脱靶效应降至最低，并有望避免小RNA疗法的脱靶相关不良事件。相关文章：本文是主题为“非编码RNA疗法”的一期特刊的一部分。若要查看本节中的其他文章，请访问http://onlinelibrary.wiley.com/doi/10.1111/bph.v182.2/issuetoc。
