Suppr超能文献

基于配对色谱的微分析阵列的小分子生物分子编码识别与剂量效应的相互依赖性。

Coding recognition of the dose-effect interdependence of small biomolecules encrypted on paired chromatographic-based microassay arrays.

机构信息

Guangdong Key Laboratory for Research & Development of Natural Drugs, Guangdong Medical University, Zhanjiang, 524023, China.

出版信息

Anal Bioanal Chem. 2022 Aug;414(19):5991-6001. doi: 10.1007/s00216-022-04162-9. Epub 2022 Jun 10.

Abstract

The discovery of small biomolecules has suffered from the lack of a comprehensive framework to express the intrinsic correlation between bioactivity and the contribution from small molecules in complex samples with molecular and bioactivity diversity. Here, by mapping a sample's 2D-HPTLC fingerprint to microplates, paired chromatographic-based microassay arrays are created, which can be used as quasi-chips to characterize multiple attributes of chromatographic components; as the array differential expression of the bioactivity and molecular attributes of irregular chromatographic spots for dose-effect interdependent encoding; and also as the automatic-collimated array mosaics of the multi-attributes of each component itself encrypted by its chromatographic fingerprint. Based on this homologous framework, we propose a correlating recognition strategy for small biomolecules through their self-consistent chromatographic behavior characteristics. In the approach, the small biomolecule recognition in diverse compounds is transformed into a constraint satisfaction problem, which is addressed through examining the dose-effect interdependence of the homologous 2D code pairs by an array matching algorithm, instead of preparing diverse compound monomers of complex test samples for identification item-by-item. Furthermore, considering the dose-effect interdependent 2D code pairs as links and the digital-specific quasimolecular ions as nodes, an extendable self-consistent framework that correlates mammalian cell phenotypic and target-based bioassays with small biomolecules is established. Therefore, the small molecule contributions and the correlations of bioactivities, as well as their pathways, can be comprehensively revealed, so as to improve the reliability and efficiency of screening. This strategy was successfully applied to galangal, and demonstrated the high-throughput digital preliminary screening of small biomolecules in a natural product.

摘要

小分子的发现受到缺乏综合框架的限制,无法表达生物活性与小分子在具有分子和生物活性多样性的复杂样品中的贡献之间的内在相关性。在这里,通过将样品的 2D-HPTLC 指纹映射到微孔板上,创建了基于配对色谱的微检测阵列,可以将其用作准芯片来表征色谱成分的多个属性;作为不规则色谱斑点生物活性和分子属性的阵列差异表达,用于剂量-效应相互依赖的编码;以及作为每个成分本身的多属性的自动准直阵列镶嵌,由其色谱指纹加密。基于这个同源框架,我们提出了一种通过小分子自身一致的色谱行为特征进行相关识别的策略。在该方法中,将复杂混合物中小分子的识别转化为约束满足问题,通过使用阵列匹配算法检查同源 2D 代码对的剂量-效应相关性来解决,而不是为了逐个识别而准备复杂测试样品的各种化合物单体。此外,考虑到剂量-效应相互依赖的 2D 代码对作为链接,以及数字特异性准分子离子作为节点,建立了一个可扩展的自洽框架,将哺乳动物细胞表型和基于靶标的生物测定与小分子相关联。因此,可以全面揭示小分子的贡献和生物活性的相关性及其途径,从而提高筛选的可靠性和效率。该策略成功应用于高良姜,并证明了天然产物中小分子的高通量数字初步筛选。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2283/9183755/8ada9043aa96/216_2022_4162_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验