Characterization of Putative Kinases with a Solved Structure but Unknown Function from the Protein Data Bank
Characterization of Putative Kinases with a Solved Structure but Unknown Function from the Protein Data Bank
复制标题
蛋白质数据库中具有已解决结构但功能未知的推定激酶的表征
DOI：
10.1096/fasebj.2019.33.1_supplement.478.4
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Hall, Bonnie L.
中科院分区：
文献类型：
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作者：
Dollen, Julia C.;Duplan, Amanda;Hall, Bonnie L.
蛋白质数据库(PDB)包含146,000个结构，其中约有4,300个结构目前被归类为具有“未知功能”。其中，根据PDB中已知的功能结构(S)，预计约有2,500种是酶。生物化学真实科学研究实验室(BASIL)项目定义了一系列电子和体外模块，允许预测和确认这些蛋白质的功能(S)。到目前为止，罗勒主要专注于假定的水解酶，特别是NUDIX水解酶。我们正在调整罗勒模块，以用于一种新的蛋白质类别，假定的激酶(EC2.7.X.X)。之所以选择激酶，是因为它们在人类中含量丰富(超过500个激酶超家族成员)，而且几乎参与细胞功能的方方面面。利用ProMol和机理和催化位点图谱(M-CSA)，我们正在定义单元和测试基序，以确定PDB中功能未知的假定激酶。利用各种电子工具，包括BLAST、PFAM和DALI，对这些可能的激酶进行了进一步表征。同时，我们正在优化细菌蛋白过表达的蛋白(S)、蛋白的亲和层析纯化(S)和体外蛋白分析。这应该允许对通过计算确定的激酶功能(S)进行实验确认。为了支持将这些模块扩展到多个学生的并发分析，我们正在设计可靠的控制和一致的工作流程，用于计算和体外分析激酶功能。总体而言，对罗勒模块的改编使我们能够设计一种方法，用于学生同时表征多个假定的蛋白激酶。FASE期刊上没有发表与这篇摘要相关的全文文章。
The protein databank (PDB) contains 146,000 structures, with approximately 4300 of those currently classified as having “unknown function”. Of those, about 2500 are expected to be enzymes, based on structures with known function(s) in the PDB. The Biochemistry Authentic Scientific Inquiry Lab (BASIL) project has defined a series of in silico and in vitro modules that allow prediction and confirmation of function(s) for these proteins. To date, BASIL has focused primarily on putative hydrolases, especially the NUDIX hydrolases. We are adapting the BASIL modules for use with a novel category of proteins, putative kinases (EC 2.7.X.X). Kinases were selected because of their abundance in humans (over 500 members of the kinase superfamily) and their involvement in almost every aspect of cellular function. Utilizing ProMol and the Mechanism and Catalytic Site Atlas (M‐CSA), we are defining units and test motifs for identification of putative kinases with unknown function within the PDB. These putative kinases are being further characterized utilizing a variety of in silico tools, including BLAST, Pfam, and Dali. In parallel, we are optimizing bacterial protein overexpression of the kinase(s), affinity chromatography purification of the protein(s), and the in vitro kinase assays. This should allow experimental confirmation of the kinase function(s) identified computationally. To support expansion of these modules to concurrent analyses by multiple students, we are designing reliable controls and a consistent workflow for the computational and in vitro analyses of kinase function. Overall, adaptation of the BASIL modules is allowing us to design a method for student characterization of multiple putative kinases simultaneously.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published inThe FASEB Journal.