4.8 Article

Solvent-Induced Protein Precipitation for Drug Target Discovery on the Proteomic Scale

Journal

ANALYTICAL CHEMISTRY
Volume 92, Issue 1, Pages 1363-1371

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.9b04531

Keywords

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Funding

  1. China State Key Basic Research Program Grants [2016YFA0501402, 2017YFA0505004]
  2. National Natural Science Foundation of China [21675061, 21535008, 91753105]
  3. LiaoNing Revitalization Talents Program
  4. innovation program of science and research from the DICP, CAS [DICP TMSR201601, DICPQIBEBT UN201802, DICP 1201935]
  5. National Science Fund of China for Distinguished Young Scholars [21525524]

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High-throughput drug discovery is highly dependent on the targets available to accelerate the process of candidates screening. Traditional chemical proteomics approaches for the screening of drug targets usually require the immobilization/modification of the drug molecules to pull down the interacting proteins. Recently, energetics-based proteomics methods provide an alternative way to study drug-protein interaction by using complex cell lysate directly without any modification of the drugs. In this study, we developed a novel energetics-based proteomics strategy, the solvent-induced protein precipitation (SIP) approach, to profile the interaction of drugs with their target proteins by using quantitative proteomics. The method is easy to use for any laboratory with the common chemical reagents of acetone, ethanol, and acetic acid. The SIP approach was able to identify the well-known protein targets of methotrexate, SNS-032, and a pan-kinase inhibitor of staurosporine in cell lysate. We further applied this approach to discover the off-targets of geldanamycin. Three known protein targets of the HSP90 family were successfully identified, and several potential off-targets including NADH dehydrogenase subunits NDUFV1 and NDUFAB1 were identified for the first time, and the NDUFV1 was validated by using Western blotting. In addition, this approach was capable of evaluating the affinity of the drug-target interaction. The data collectively proved that our approach provides a powerful platform for drug target discovery.

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