权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

The Center for High Content Functional Annotation of Natural Products

天然产物高内涵功能注释中心

基本信息

批准号：
10700819
负责人：
Nadja B Cech
金额：
$ 97.67万
依托单位：
UNIVERSITY OF CALIFORNIA SANTA CRUZ
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-01 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10700819
关键词：
Address Area Back Belief Bioinformatics Biological Biological Assay Biology Botanicals Cell Line Cells Chemicals Clinical Trials Communities Complex Complex Mixtures Computer Models Constitution Constitutional Cytology Data Data Analytics Databases Development Disease Disparate Epithelial Cells Generations Health Health Benefit Healthcare Industry In Vitro Informatics Link Macrophage Maps Medicine Metabolic Metabolism Modeling Modification Molecular Target Natural Products Natural Products Chemistry Neurons Online Systems Outcome Phenotype Process Reagent Role Signal Pathway Speed Technology Text Work data integration experience gut microbiome improved in vivo innovation interest metabolomics new technology novel programs public health relevance receptor screening success synergism technology platform technology validation tool web site

项目摘要

It has been well documented that the outcomes of success for botanical clinical trials have been poor, leading to greater effort into understanding the basic mechanisms underlying their activity. While it is often hypothesized that botanicals or other complex mixtures work through synergistic or additive processes, there are few proven examples. There is also growing belief to support the role of gut microbiome metabolism for generation of active metabolites, however, relatively few experimental results back this up. This is driven by limitations in obtaining clear biological signatures in relevant biological assays, in accurately defining the chemical constitution of complex mixtures, and in the informatics approaches to bring these disparate data types together. This proposal aims to address these important questions by the development and implementation of technology platforms. In project 1, we will employ highly innovative orthogonal cell-based high content phenotypic screening approaches in primary macrophages, epithelial cells, primary neurons, which will give us comprehensive coverage of signaling pathway and receptor that are believed to be relevant to botanicals. These platforms aim to link botanicals/bioactive molecules of interest together with information about their molecular targets. These platforms have been demonstrated to work with complex mixtures as well as pure compounds and are supported by the development of bioinformatic approaches that allow integration of orthogonal biological activity. Our second project will take advantage of developments in untargeted metabolomics, along with feature reduction, to have a robust pipeline to clearly define the constitution of complex mixtures. Our third project specifically addresses the question of synergy and additivity by the development of informatics approaches that use the comprehensive biological and chemical signatures generated in the other projects. In this project, we will develop universal tools that will allow the community to probe their own biological and chemical assay results to generate compound/activity maps. This program will deliver critical technology platforms for the in-depth study of botanicals and natural products and deliver tools that can be used by the community

有充分的证据表明，植物临床试验的成功结果很差，导致更大的努力来了解其活动的基本机制。虽然它经常假设植物药或其他复杂的混合物通过协同或添加剂过程起作用，很少有被证实的例子。也有越来越多的人相信肠道微生物组代谢的作用，然而，相对较少的实验结果支持这一点。这是由在相关生物测定中获得明确的生物特征、准确定义复杂混合物的化学组成，并在信息学方法中将这些不同的数据类型在一起。该提案旨在通过发展和建立技术平台。在项目1中，我们将采用高度创新的基于正交小区的在原代巨噬细胞，上皮细胞，原代神经元，这将使我们全面覆盖信号通路和受体，到植物这些平台旨在将感兴趣的植物/生物活性分子与信息联系起来它们的分子靶点。这些平台已被证明可以处理复杂的混合物作为纯化合物，并得到生物信息学方法的发展的支持，正交的生物活性。我们的第二个项目将利用无目标的发展，代谢组学，沿着特征减少，有一个强大的管道，清楚地定义的构成，复杂的混合物我们的第三个项目具体解决了协同作用和加和性的问题，开发使用全面生物和化学特征的信息学方法其他项目中产生的。在这个项目中，我们将开发通用工具，使社区能够探测他们自己的生物和化学分析结果，以生成化合物/活性图。此程序将为深入研究植物和天然产品提供关键技术平台，并提供工具可以被社区使用

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Benefiting from big data in natural products: importance of preserving foundational skills and prioritizing data quality.

DOI：
10.1039/d1np00061f
发表时间：
2021-11-17
期刊：
Natural product reports
影响因子：
11.9
作者：
Cech NB;Medema MH;Clardy J
通讯作者：
Clardy J

MIBiG 2.0: a repository for biosynthetic gene clusters of known function

DOI：
10.1093/nar/gkz882
发表时间：
2020-01-08
期刊：
NUCLEIC ACIDS RESEARCH
影响因子：
14.9
作者：
Kautsar, Satria A.;Blin, Kai;Medema, Marnix H.
通讯作者：
Medema, Marnix H.

Reply to Skinnider and Magarvey: Rates of novel natural product discovery remain high.

回复 Skinnider 和 Magarvey：新型天然产品的发现率仍然很高。

DOI：
10.1073/pnas.1711139114
发表时间：
2017
期刊：
Proceedings of the National Academy of Sciences of the United States of America
影响因子：
11.1
作者：
Pye,CameronR;Bertin,MatthewJ;Lokey,RScott;Gerwick,WilliamH;Linington,RogerG
通讯作者：
Linington,RogerG

Annotation of natural product compound families using molecular networking topology and structural similarity fingerprinting.

DOI：
10.1038/s41467-022-35734-z
发表时间：
2023-01-19
期刊：
NATURE COMMUNICATIONS
影响因子：
16.6
作者：
Morehouse, Nicholas J. J.;Clark, Trevor N. N.;McMann, Emily J. J.;van Santen, Jeffrey A. A.;Haeckl, F. P. Jake;Gray, Christopher A. A.;Linington, Roger G. G.
通讯作者：
Linington, Roger G. G.

Development of an NMR-Based Platform for the Direct Structural Annotation of Complex Natural Products Mixtures.