Jason Deng , Svetlana Belyanskaya, Ninad Prabhu , Christopher Arico-Muendel, Hongfeng Deng , Christopher B. Phelps , David I. Israel , Hongfang Yang , Joseph Boyer , G. Joseph Franklin , Jeremy L. Yap , Kenneth E. Lind , Ching-Hsuan Tsai , Christine Donahue , Jennifer D. Summerfield
{"title":"用 DELs 分析细胞:细胞表面的小分子指纹图谱","authors":"Jason Deng , Svetlana Belyanskaya, Ninad Prabhu , Christopher Arico-Muendel, Hongfeng Deng , Christopher B. Phelps , David I. Israel , Hongfang Yang , Joseph Boyer , G. Joseph Franklin , Jeremy L. Yap , Kenneth E. Lind , Ching-Hsuan Tsai , Christine Donahue , Jennifer D. Summerfield","doi":"10.1016/j.slasd.2024.100171","DOIUrl":null,"url":null,"abstract":"<div><p>DNA-encoded small molecule library technology has recently emerged as a new paradigm for identifying ligands against drug targets. To date, it has been used to identify ligands against targets that are soluble or overexpressed on cell surfaces. Here, we report applying cell-based selection methods to profile surfaces of mouse C2C12 myoblasts and myotube cells in an unbiased, target agnostic manner. A panel of on-DNA compounds were identified and confirmed for cell binding selectivity. We optimized the cell selection protocol and employed a novel data analysis method to identify cell selective ligands against a panel of human B and T lymphocytes. We discuss the generality of using this workflow for DNA encoded small molecule library selection and data analysis against different cell types, and the feasibility of applying this method to profile cell surfaces for biomarker and target identification.</p></div>","PeriodicalId":21764,"journal":{"name":"SLAS Discovery","volume":"29 5","pages":"Article 100171"},"PeriodicalIF":2.7000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2472555224000339/pdfft?md5=c0f34f61b83c77e23483474ae6a68680&pid=1-s2.0-S2472555224000339-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Profiling cells with DELs: Small molecule fingerprinting of cell surfaces\",\"authors\":\"Jason Deng , Svetlana Belyanskaya, Ninad Prabhu , Christopher Arico-Muendel, Hongfeng Deng , Christopher B. Phelps , David I. Israel , Hongfang Yang , Joseph Boyer , G. Joseph Franklin , Jeremy L. Yap , Kenneth E. Lind , Ching-Hsuan Tsai , Christine Donahue , Jennifer D. Summerfield\",\"doi\":\"10.1016/j.slasd.2024.100171\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>DNA-encoded small molecule library technology has recently emerged as a new paradigm for identifying ligands against drug targets. To date, it has been used to identify ligands against targets that are soluble or overexpressed on cell surfaces. Here, we report applying cell-based selection methods to profile surfaces of mouse C2C12 myoblasts and myotube cells in an unbiased, target agnostic manner. A panel of on-DNA compounds were identified and confirmed for cell binding selectivity. We optimized the cell selection protocol and employed a novel data analysis method to identify cell selective ligands against a panel of human B and T lymphocytes. We discuss the generality of using this workflow for DNA encoded small molecule library selection and data analysis against different cell types, and the feasibility of applying this method to profile cell surfaces for biomarker and target identification.</p></div>\",\"PeriodicalId\":21764,\"journal\":{\"name\":\"SLAS Discovery\",\"volume\":\"29 5\",\"pages\":\"Article 100171\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2472555224000339/pdfft?md5=c0f34f61b83c77e23483474ae6a68680&pid=1-s2.0-S2472555224000339-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SLAS Discovery\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2472555224000339\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SLAS Discovery","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2472555224000339","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
摘要
DNA 编码小分子文库技术最近已成为鉴定药物靶标配体的一种新模式。迄今为止,该技术一直被用于鉴定针对可溶性或在细胞表面过度表达的靶点的配体。在此,我们报告了应用基于细胞的筛选方法,以无偏见、不考虑靶点的方式对小鼠 C2C12 肌母细胞和肌管细胞的表面进行剖析。我们鉴定并确认了一组 DNA 上化合物的细胞结合选择性。我们优化了细胞选择方案,并采用了一种新颖的数据分析方法来鉴定针对人类 B 淋巴细胞和 T 淋巴细胞的细胞选择性配体。我们讨论了使用这种工作流程对不同类型细胞进行 DNA 编码小分子库选择和数据分析的通用性,以及应用这种方法对细胞表面进行生物标记物和靶标鉴定的可行性。
Profiling cells with DELs: Small molecule fingerprinting of cell surfaces
DNA-encoded small molecule library technology has recently emerged as a new paradigm for identifying ligands against drug targets. To date, it has been used to identify ligands against targets that are soluble or overexpressed on cell surfaces. Here, we report applying cell-based selection methods to profile surfaces of mouse C2C12 myoblasts and myotube cells in an unbiased, target agnostic manner. A panel of on-DNA compounds were identified and confirmed for cell binding selectivity. We optimized the cell selection protocol and employed a novel data analysis method to identify cell selective ligands against a panel of human B and T lymphocytes. We discuss the generality of using this workflow for DNA encoded small molecule library selection and data analysis against different cell types, and the feasibility of applying this method to profile cell surfaces for biomarker and target identification.
期刊介绍:
Advancing Life Sciences R&D: SLAS Discovery reports how scientists develop and utilize novel technologies and/or approaches to provide and characterize chemical and biological tools to understand and treat human disease.
SLAS Discovery is a peer-reviewed journal that publishes scientific reports that enable and improve target validation, evaluate current drug discovery technologies, provide novel research tools, and incorporate research approaches that enhance depth of knowledge and drug discovery success.
SLAS Discovery emphasizes scientific and technical advances in target identification/validation (including chemical probes, RNA silencing, gene editing technologies); biomarker discovery; assay development; virtual, medium- or high-throughput screening (biochemical and biological, biophysical, phenotypic, toxicological, ADME); lead generation/optimization; chemical biology; and informatics (data analysis, image analysis, statistics, bio- and chemo-informatics). Review articles on target biology, new paradigms in drug discovery and advances in drug discovery technologies.
SLAS Discovery is of particular interest to those involved in analytical chemistry, applied microbiology, automation, biochemistry, bioengineering, biomedical optics, biotechnology, bioinformatics, cell biology, DNA science and technology, genetics, information technology, medicinal chemistry, molecular biology, natural products chemistry, organic chemistry, pharmacology, spectroscopy, and toxicology.
SLAS Discovery is a member of the Committee on Publication Ethics (COPE) and was published previously (1996-2016) as the Journal of Biomolecular Screening (JBS).