Literature DB >> 22793685

Automatic analysis of quantitative NMR data of pharmaceutical compound libraries.

Xuejun Liu1, Michael X Kolpak, Jiejun Wu, Gregory C Leo.   

Abstract

In drug discovery, chemical library compounds are usually dissolved in DMSO at a certain concentration and then distributed to biologists for target screening. Quantitative (1)H NMR (qNMR) is the preferred method for the determination of the actual concentrations of compounds because the relative single proton peak areas of two chemical species represent the relative molar concentrations of the two compounds, that is, the compound of interest and a calibrant. Thus, an analyte concentration can be determined using a calibration compound at a known concentration. One particularly time-consuming step in the qNMR analysis of compound libraries is the manual integration of peaks. In this report is presented an automated method for performing this task without prior knowledge of compound structures and by using an external calibration spectrum. The script for automated integration is fast and adaptable to large-scale data sets, eliminating the need for manual integration in ~80% of the cases.

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Year:  2012        PMID: 22793685     DOI: 10.1021/ac301544u

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  3 in total

Review 1.  Universal quantitative NMR analysis of complex natural samples.

Authors:  Charlotte Simmler; José G Napolitano; James B McAlpine; Shao-Nong Chen; Guido F Pauli
Journal:  Curr Opin Biotechnol       Date:  2013-09-14       Impact factor: 9.740

2.  Validation of a generic quantitative (1)H NMR method for natural products analysis.

Authors:  Tanja Gödecke; José G Napolitano; María F Rodríguez-Brasco; Shao-Nong Chen; Birgit U Jaki; David C Lankin; Guido F Pauli
Journal:  Phytochem Anal       Date:  2013-06-05       Impact factor: 3.373

3.  Automated NMR fragment based screening identified a novel interface blocker to the LARG/RhoA complex.

Authors:  Jia Gao; Rongsheng Ma; Wei Wang; Na Wang; Ryan Sasaki; David Snyderman; Jihui Wu; Ke Ruan
Journal:  PLoS One       Date:  2014-02-05       Impact factor: 3.240

  3 in total

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