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Elements: The ThYme database and identifying representative amino acid sequences that originate thioester-active enzyme families

Elements: The ThYme database and identifying representative amino acid sequences that originate thioester-active enzyme families
元素:ThYme 数据库并鉴定产生硫酯活性酶家族的代表性氨基酸序列
批准号:
2001385
负责人:
David Cantu
金额:
$60.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-07-01 至 2024-06-30

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中文摘要
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英文摘要
The ThYme database includes most enzymes involved in the formation of fatty acids and polyketides. These are ultimately converted into valuable products. Such products include cosmetics, detergents, insecticides, fungicides, antibiotics, and other medicinal compounds. The updated ThYme database will provide vital support to research related to these products. Metabolic engineers, plant biologists, natural products and medicinal chemists will all benefit from improved access to enzyme structure and function. High school students from underrepresented populations will be recruited and trained in various aspects of coding. They will then have the opportunity to work with graduate students and postdocs to contribute to the improvement of the platform. This should ultimately strengthen the STEM workforce in Nevada, and nationally.The ThYme database contains most known sequences and structures of enzymes that act on thioesters, classified by sequence similarity into families. The advantage of classifying enzymes by sequence similarity is that one can infer that all enzymes in a family will have very similar structures and nearly identical catalytic residues and mechanisms. The goal of this project is to launch a new and updated ThYme database by identifying the current families of thioester active enzymes, developing a new approach to identify representative sequences, improving the database management scheme, and modernizing the online user interface. We will develop an efficient method, using submodular functions, to select the representative sequence(s) of an enzyme family among sequences experimentally verified to have a particular enzymatic activity. The database will be disseminated by a website, where every enzyme family will have its own webpage including relevant knowledge and an open query field where users will be able to search by organism, sequence accession code, function, name, sequence, or crystal structure. With input from the user community, the new website will have features to make the content more interactive and allow automated data querying. The user community will be engaged and supported with a forum page to pose questions and begin discussions to which both developers and users can contribute, as well as with tutorials of useful website functionalities.This award by the NSF Office of Advanced Cyberinfrastructure is jointly supported by the ivision of Chemical, Bioengineering, Environmental and Transport Systems within the NSF Directorate of Engineering.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(10)
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DOI: 10.1002/pro.4263
发表时间: 2022-01-04
期刊: PROTEIN SCIENCE
影响因子: 8
作者: [Caswell, Benjamin T., de Carvalho, Caio C., Cantu, David C.]
通讯作者: Cantu, David C.
DWEN: A novel method for accurate estimation of cell type compositions from bulk data samples
DWEN:一种从大量数据样本中准确估计细胞类型组成的新方法
DOI: 10.1109/kse56063.2022.9953757
发表时间: 2022
期刊: 2022 14th International Conference on Knowledge and Systems Engineering (KSE
影响因子: --
作者: [Tran, Duc, Nguyen, Ha, Nguyen, Hung, Nguyen, Tin]
通讯作者: Nguyen, Tin
CAREER: The solution structure of lanthanide-extractant complexes across liquid-liquid interfaces
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