Literature DB >> 27797491

Compound Property Optimization in Drug Discovery Using Quantitative Surface Sampling Micro Liquid Chromatography with Tandem Mass Spectrometry.

Xiaohui Chen, Panos Hatsis1, Joyce Judge, Upendra A Argikar, Xiaojun Ren1, Jason Sarber, Keith Mansfield, Guiqing Liang, Adam Amaral, Alexandre Catoire1, Adam Bentley1, Luis Ramos1, Paul Moench1, Samuel Hintermann2, David Carcache2, Jim Glick1, Jimmy Flarakos1.   

Abstract

Surface sampling micro liquid chromatography tandem mass spectrometry (SSμLC-MS/MS) was explored as a quantitative tissue distribution technique for probing compound properties in drug discovery. A method was developed for creating standard curves using surrogate tissue sections from blank tissue homogenate spiked with compounds. The resulting standard curves showed good linearity and high sensitivity. The accuracy and precision of standards met acceptance criteria of ±30%. A new approach was proposed based on an experimental and mathematical method for tissue extraction efficiency evaluation by means of consecutively sampling a location on tissue twice by SSμLC-MS/MS. The observed extraction efficiency ranged from 69% to 82% with acceptable variation for the test compounds. Good agreement in extraction efficiency was observed between surrogate tissue sections and incurred tissue sections. This method was successfully applied to two case studies in which tissue distribution was instrumental in advancing project teams' understanding of compound properties.

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Year:  2016        PMID: 27797491     DOI: 10.1021/acs.analchem.6b03449

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


  2 in total

Review 1.  Spatially resolved absolute quantitation in thin tissue by mass spectrometry.

Authors:  Vilmos Kertesz; John F Cahill
Journal:  Anal Bioanal Chem       Date:  2021-04       Impact factor: 4.142

2.  Quantitative MALDI Imaging of Spatial Distributions and Dynamic Changes of Tetrandrine in Multiple Organs of Rats.

Authors:  Weiwei Tang; Jun Chen; Jie Zhou; Junyue Ge; Ying Zhang; Ping Li; Bin Li
Journal:  Theranostics       Date:  2019-01-25       Impact factor: 11.556

  2 in total

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