Issue 2, 2016

Application of the ultrafiltration-based LC-MS approach for screening PTP1B inhibitors from Chinese red yeast rice

Abstract

Ultrafiltration-based affinity selection combined with liquid chromatography-mass spectrometry (LC-MS) is an efficient tool for screening complex mixtures, such as traditional medicines. And this approach has many advantages over the more conventional bioassay-guided isolation, which is time-consuming and laborious. This paper presents an application of an ultrafiltration-based LC-MS approach to screen potential protein tyrosine phosphatase 1B (PTP1B) inhibitors from Chinese red yeast rice (RYR), and the reliable potential active compounds were determined based on the optimized evaluation criteria of binding behavior. As a result, at least one compound in the RYR extract was identified as a potential PTP1B inhibitor, and its structure was confirmed to be that of monascorubramine using mass spectrometry elevated energy (MSE). The binding behavior of monascorubramine to T cell protein tyrosine phosphatase (TCPTP, a homolog of PTP1B) and other randomly chosen proteins (proprotein convertase subtilisin/kexin type 9, PCSK9; low-density lipoprotein receptor, LDLR; phosphomannomutase 2, PMM2; serine hydroxymethyltransferase, SHMT; bromodomain-containing protein 4 domain 1, BRD4-1; and jumonji domain-containing 2A, JMJD2A) was evaluated. RYR was verified to exhibit a selective PTP1B inhibitory activity, partially because monascorubramine showed selectivity towards PTP1B versus TCPTP and the other randomly chosen proteins.

Graphical abstract: Application of the ultrafiltration-based LC-MS approach for screening PTP1B inhibitors from Chinese red yeast rice

Article information

Article type
Paper
Submitted
08 Jul 2015
Accepted
14 Nov 2015
First published
19 Nov 2015

Anal. Methods, 2016,8, 353-361

Author version available

Application of the ultrafiltration-based LC-MS approach for screening PTP1B inhibitors from Chinese red yeast rice

Y. Jin, X. Cheng, F. Jiang, Z. Guo, J. Xie and L. Fu, Anal. Methods, 2016, 8, 353 DOI: 10.1039/C5AY01767J

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