ASOG:反义寡核苷酸发生器

IF 4.1 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-09-16 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.09.022
Jonah Kimi, Patricia Korczak, Brune Vialet, Eric Roubin, Philippe Barthélémy, Sébastien Campagne, Florian Malard
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引用次数: 0

摘要

反义寡核苷酸(ASOs)通过靶向特定基因的RNA转录物来调节基因表达,在基础研究和临床应用中都有应用。从历史上看,ASO是手工设计的,这是一个耗时的过程,限制了对ASO空间的详尽搜索。最近,一些基于传统或深度学习方法的资源被开发出来,以促进ASO设计,每种方法都有其特定的用例和局限性。在这种情况下,我们提出了一个基于明确的标准、原始算法和第三方软件的ASO设计的原始和通用的管道,封装在一个我们称为反义寡核苷酸生成器(ASOG)的web应用程序中。ASOG管道只需要一个目标基因序列作为输入,它就可以生成ASO,预测目标子序列的结构特性,预测剪接位点掩蔽,检测脱靶效应,并计算热力学杂交参数,考虑到一些最常见的RNA修饰。ASOG旨在使用户能够快速浏览ASO空间,帮助他们做出明智的决策。ASOG web服务器可在ASOG .iecb.u-bordeaux.fr获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ASOG: AntiSense Oligonucleotide Generator.

Antisense oligonucleotides (ASOs) are used in both fundamental research and clinical applications to modulate gene expression by targeting the RNA transcript of specific genes. Historically, ASOs were designed manually, a time-consuming process that limited exhaustive searches through the ASO space. More recently, resources have been developed based on traditional or deep learning approaches to facilitate ASO design, each with their specific use cases and limitations. In this context, we propose an original and generalistic pipeline for ASO design, based on explicit criteria, original algorithms, and third-party software, encapsulated in a web application we named AntiSense Oligonucleotide Generator (ASOG). The ASOG pipeline requires only a target gene sequence as input, and it proceeds with ASO generation, predicts the structural properties of target subsequences, predicts splice site masking, detects off-target effects, and computes thermodynamic hybridization parameters, taking into account some of the most common RNA modifications. ASOG is designed to enable users to quickly navigate the ASO space, assisting them in making informed decisions. The ASOG webserver is available at asog.iecb.u-bordeaux.fr.

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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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