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Targeting protein-protein interactions as drug targets

Targeting protein-protein interactions as drug targets
将蛋白质-蛋白质相互作用作为药物靶点
批准号:
10306398
负责人:
Michael D. Burkart
金额:
$19.75万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-12-01 至 2024-11-30

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7. Project Summary. This proposal describes a program to identify drug targets for tuberculosis and Escherichia coli infections through the combination of computational and experimental methods to elucidate targets within mycobacterial and bacterial fatty acid synthesis. In Escherichia coli, the pathway involves 27 discrete interactions between AcpP and its partner proteins. In tuberculosis, the FAS-II pathway is involved the production of mycolic acids, which serve a pivotal role in the virulence of Mycobacterium tuberculosis (Mtb). As both pathways require an acyl carrier protein (ACP) to deliver growing fatty acyl substrates and intermediates to associated partner proteins (PPs), protein-protein interactions within the AcpP.PP complex are an essential for effective substrate processivity. Resolution of the structures of these assemblies and the interactions responsible for their formation will not only further our knowledge of the mechanisms by which these proteins function and are regulated but will also enable structure-based drug discovery work. In order to elucidate these structures, we will leverage our knowledge of the Escherichia coli AcpP.PP interfaces to identify a computational docking protocol that produces novel Mtb AcpP.PP structures. Our computational methodology will be optimized by evaluating its effectiveness in recapitulating known structures of E. coli AcPP.PP complexes resolved via NMR and X-ray crystallography studies. This computational protocol, once tested, will be used to predict both AcpP.PP and AcpM.PP complexes. The structures of the resulting complexes will then be validated using NMR titration and mutagenesis experiments. The resulting models will be refined using molecular dynamics simulations, which yield a dynamical understanding protein structure that will inform computer-aided drug discovery efforts.
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DOI: 10.1039/d3sc02864j
发表时间: 2023-10-11
期刊: CHEMICAL SCIENCE
影响因子: 8.4
作者: [Jiang, Ziran, Chen, Aochiu, Chen, Jeffrey, Sekhon, Arman, Louie, Gordon V., Noel, Joseph P., La Clair, James J., Burkart, Michael D.]
通讯作者: Burkart, Michael D.
Targeting Metal-Dependent Epigenetic Modulators via MetalloPROTACs
Enabling synthetic biology through single cell functional genomics
Chemistry-Biology Interfaces at UCSD
Human mitochondrial ACP interactions
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