ASOptimizer：通过深度学习优化反义寡核苷酸的化学多样性。

IF 16.6 2区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Nucleic Acids Research Pub Date : 2025-05-16 DOI:10.1093/nar/gkaf392

Seokjun Kang,Daehwan Lee,Gyeongjo Hwang,Kiwon Lee,Mingeun Kang

{"title":"ASOptimizer：通过深度学习优化反义寡核苷酸的化学多样性。","authors":"Seokjun Kang,Daehwan Lee,Gyeongjo Hwang,Kiwon Lee,Mingeun Kang","doi":"10.1093/nar/gkaf392","DOIUrl":null,"url":null,"abstract":"Antisense oligonucleotides (ASOs) are a promising class of gene therapies that can modulate the gene expression. However, designing ASOs manually is resource-intensive and time-consuming. To address this, we introduce a user-friendly web server for ASOptimizer, a deep learning-based computational framework for optimizing ASO sequences and chemical modifications. Given a user-provided ASO sequence, the web server systematically explores modification sites within the nucleic acid and returns a ranked list of promising modification patterns. With an intuitive interface requiring no expertise in deep learning tools, the platform makes ASOptimizer easily accessible to the broader research community. The web server is freely available at https://asoptimizer.s-core.ai/.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"76 1","pages":""},"PeriodicalIF":16.6000,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ASOptimizer: optimizing chemical diversity of antisense oligonucleotides through deep learning.\",\"authors\":\"Seokjun Kang,Daehwan Lee,Gyeongjo Hwang,Kiwon Lee,Mingeun Kang\",\"doi\":\"10.1093/nar/gkaf392\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Antisense oligonucleotides (ASOs) are a promising class of gene therapies that can modulate the gene expression. However, designing ASOs manually is resource-intensive and time-consuming. To address this, we introduce a user-friendly web server for ASOptimizer, a deep learning-based computational framework for optimizing ASO sequences and chemical modifications. Given a user-provided ASO sequence, the web server systematically explores modification sites within the nucleic acid and returns a ranked list of promising modification patterns. With an intuitive interface requiring no expertise in deep learning tools, the platform makes ASOptimizer easily accessible to the broader research community. The web server is freely available at https://asoptimizer.s-core.ai/.\",\"PeriodicalId\":19471,\"journal\":{\"name\":\"Nucleic Acids Research\",\"volume\":\"76 1\",\"pages\":\"\"},\"PeriodicalIF\":16.6000,\"publicationDate\":\"2025-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nucleic Acids Research\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/nar/gkaf392\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nucleic Acids Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/nar/gkaf392","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

反义寡核苷酸（ASOs）是一类很有前途的基因疗法，可以调节基因表达。然而，手动设计aso是一种资源密集型和耗时的工作。为了解决这个问题，我们为ASOptimizer引入了一个用户友好的web服务器，ASOptimizer是一个基于深度学习的计算框架，用于优化ASO序列和化学修饰。给定用户提供的ASO序列，web服务器系统地探索核酸中的修饰位点，并返回有希望的修饰模式的排序列表。借助直观的界面，无需深度学习工具方面的专业知识，该平台使更广泛的研究社区可以轻松访问ASOptimizer。web服务器可以在https://asoptimizer.s-core.ai/上免费获得。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

ASOptimizer: optimizing chemical diversity of antisense oligonucleotides through deep learning.

Antisense oligonucleotides (ASOs) are a promising class of gene therapies that can modulate the gene expression. However, designing ASOs manually is resource-intensive and time-consuming. To address this, we introduce a user-friendly web server for ASOptimizer, a deep learning-based computational framework for optimizing ASO sequences and chemical modifications. Given a user-provided ASO sequence, the web server systematically explores modification sites within the nucleic acid and returns a ranked list of promising modification patterns. With an intuitive interface requiring no expertise in deep learning tools, the platform makes ASOptimizer easily accessible to the broader research community. The web server is freely available at https://asoptimizer.s-core.ai/.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Nucleic Acids Research 生物-生化与分子生物学

CiteScore

27.10

自引率

4.70%

发文量

1057

审稿时长

2 months

期刊介绍： Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.