.png){kind=icon}
返回
Machine learning guided aptamer refinement and discovery
.png){kind=icon}
OA
AI
DOI：10.1038/s41467-021-22555-9.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Aptamers are single-stranded nucleic acid ligands that bind to target molecules with high affinity and specificity. They are typically discovered by searching large libraries for sequences with desirable binding properties. These libraries, however, are practically constrained to a fraction of the theoretical sequence space. Machine learning provides an opportunity to intelligently navigate this space to identify high-performing aptamers. Here, we propose an approach that employs particle display (PD) to partition a library of aptamers by affinity, and uses such data to train machine learning models to predict affinity in silico. Our model predicted high-affinity DNA aptamers from experimental candidates at a rate 11-fold higher than random perturbation and generated novel, high-affinity aptamers at a greater rate than observed by PD alone. Our approach also facilitated the design of truncated aptamers 70% shorter and with higher binding affinity (1.5 nM) than the best experimental candidate. This work demonstrates how combining machine learning and physical approaches can be used to expedite the discovery of better diagnostic and therapeutic agents. Current aptamer discovery approaches are unable to probe the complete space of possible sequences. Here, the authors use machine learning to facilitate the development of DNA aptamers with improved binding affinities, and truncate them without significantly compromising binding affinity.
Keyword:
QUANTITATIVE SCREENING METHOD
IN-VITRO SELECTION
HIGH-AFFINITY
PARTICLE DISPLAY
RNA
MOLECULES
EVOLUTION
DELIVERY
LIGANDS
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
15.7
论文数:
9.4W
被引数:
91.2W
机构
引用论文
Superior Performance of Aptamer in Tumor Penetration over Antibody: Implication of Aptamer-Based Theranostics in Solid Tumors适体在肿瘤穿透中优于抗体的性能: 基于适体的治疗方法在实体瘤中的意义.png)
THERANOSTICSOAAI
THERANOSTICSIF13.3
OAAI分享收藏Real-Time, Aptamer-Based Tracking of Circulating Therapeutic Agents in Living Animals基于适体的实时跟踪活体动物中循环治疗剂
OAAI
OAAI分享收藏AptaTRACE Elucidates RNA Sequence-Structure Motifs from Selection Trends in HT-SELEX ExperimentsCELL SYSTEMSOAAI
CELL SYSTEMSIF7.7
OAAI分享收藏Factors affecting dye sensitised photo-oxidation reactions; the effect of oxygen concentration and its use to probe the mechanism of decarboxylation of α-oxo-carboxylic acids and estersTetrahedron
TetrahedronIF0
PREAI
分享收藏Amplification, Mutation, and Sequencing of a Six-Letter Synthetic Genetic System六字母合成遗传系统的扩增，突变和测序OAAI
OAAI分享收藏
查看更多内容