High Resolution Mass Spectrometry With Automated Data Analysis to ...

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High Resolution Mass Spectrometry With Automated Data Analysis to Support Late Stage Functionalization Yong Liu1; Fabien Fontaine2; Bella Yao1; Ismael Zamora2; Roy Helmy1; Shane Krska1; Kevin P. Bateman1

1Merck

& Co., Inc., Kenilworth, NJ, USA; 2Molecular Discovery, Barcelona, Spain

Introduction Late stage functionalization (LSF) refers to the use of C-H activation chemistries for the incorporation of structural diversity into a final product or an advanced intermediate. This approach has become a very useful synthetic tool that provides rapid access to otherwise difficult to obtain chemical entities. Its utility spans multiple areas, including discovery chemistry, drug metabolism, and discovery biology. Given the complex structure of the final product or advanced intermediate, LSF chemistry often generates mixtures with multiple products that are regioisomers. Furthermore, LSF employs high throughput synthesis techniques that give rise to many samples for analysis. In this study, we describe an analytical approach for LSF reaction analysis. A rapid liquid chromatography high resolution mass spectrometry (LC-HRMS) workflow was developed for sample analysis. MSe data acquisition and a modified version of Massmetasite were adapted for automated data analysis, with final data review and browsing enabled through WebMetabase.

UPLC-HR-MS/MS data acquisition UPLC: The chromatographic separation is performed by Acquity UPLC system. The mobile phases consist of solvent A (100% water, 0.1% formic acid ), and solvent B (100% acetonitrile, 0.1% formic acid). Column: Acquity UPLC HSS T3 column (1.8 µm, 2.1X100 mm)

Results summary

Results archive and sharing by WebMetabase

HR-MS/MS: The experiments were performed on Waters Premier QTof mass spectrometer. MSe method was developed with low collision energy as channel one to detect intact molecules and high collision energy ramp, as channel two to obtain pseudo MS/MS data.

XIC summary Chromatogram

What is LSF? •• The incorporation of chemical diversity into a final product or advanced intermediate •• A way to quickly access a suite of analogues for a compound of interest R

LSF C-H borylation, oxidation, halogenation, etc.

Biologically relevant molecule HTS hit

R

•• Archive results in a central place; allows chemists view results via Web brower Markush structure

R

R

Lead pharmacophore in a medchem project

Rapid SAR data set –– Hit validation –– On/off-target SAR –– ADME optimization

New scaffold from CM&I

 Molecular probes

Applications •• Block metabolically active sites, metabolite synthesis •• Increase potency, improve selectivity, and reduce off-target liabilities

Scan 1: Q1 nonresolving, collision energy 5 eV, TOF m/z 100-1000, 0.2s scan time, 0.05 s inter-scan delay

HR-MS/MS data analysis

Correlation of fragment ions between substrate and product

Product identity summary

Provide location of substrate and product HRMS/MS data

Microscale reaction screening (HTE)

Automated data processing

Analytical challenge • Multiple isomers • Low product conversion • Large sample quantity

Structure elucidation

Correlation of structures between substrate and product

Data analysis by MetaSite

Select chemical transformation

LC-MS HR-LC-MS/MS

Mass-directed preparative HPLC

Results summary II: MS/MS fragmentation interpretation

Accurate mass and MS/MS data are acquired in one run.

•• Expand access to SAR vectors, enhance IP position Work flow of LSF and major analytical challenge

Results archive and sharing by WebMetabase II

Scan 1: Q1 nonresolving, collision energy ramp 20-40 eV, TOF m/z 100-1000, 0.1s scan time, 0.05 s inter-scan delay

Import substrate structure

•• Generate molecular probes (eg, install radiolabels)

XIC summary

Chromatogram

Registration Distribution Bioassays

Results review

Conclusions ● A general UPLC-HR-MS/MS method was

● MS/MS data analysis to propose possible

● Massmetasite was customized to adopt process

● The data analysis cycle, which is the main

developed to support all LSF chemistries

chemical transformations from late stage chemical transformations

structures is conducted in automated fashion bottleneck for the analytical support of LSF chemistry screening, is greatly shortened

● Data analysis results were deposited into

WebMetabase (centralized online searchable database)

● WebMetabase is a knowledge database based on

the chemical transformations stored, which allows prediction of LSF chemistry for new substrates

Copyright © 2015 Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. All Rights Reserved.

liuyng_186316-0001_ASMS_Poster_V1 05/26/2015 ASMA, Output Size: 44”x92” Scale: 200%

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