A new biotransformation prediction engine integrated into a
metabolite identification solution
METID CHALLENGE
MetID typically requires analysis of MS data to identify
metabolic “hot spots” and elucidate biotransformation pathways.
This remains the primary challenge despite significant instrumental
and software advances.
RAT MICROSOMAL STUDY
Samples: Test articles were added to rat liver microsomal
protein and samples were collected at 4 incubation time points.
Data Acquisition: • Elite Hybrid Velos Pro Ion Trap/
Orbitrap MS• ESI source in positive mode• Data-dependent
acquisition
based on a list of m/z values of potential metabolites
• Resolution of 30,000 (full scan),15,000 (HCD) MS2
METID SOLUTION
MetaSense™ overcomes these challenges and allows users to save
time and improve collaborations via:
AUTOMATED identification of predicted and unexpected
metabolitesAUTOGENERATED biotransformation maps, stability and
pharmacokinetic plots, and reportsINTERACTIVE SEARCHABLE DATABASE
associates spectral and chromatographic data WEB PORTAL offers
customer access to your results and reports
AUTOMATED WORKFLOW
INTERACTIVE KNOWLEDGE DATABASE
All data shown is interactive and associated with their
corresponding metabolites
Biotransformation Map
Kinetic & Stability Plot
Summary Table
BPC & XIC
Metabolite Detection and Identi�cation Knowledge ManagementData
Input
CH3
O
N
CH3
N
CH3
CH3
OCH3
O
CH3OCH3
CH3
ON
CH3
N
CH3
CH3
OCH3
O
CH3OCH3
CH3
N
CH3
CH3
OCH3
O
CH3
NH
CH3
O
N
CH3
CH3
OCH3
O
CH3O
CH3
N
O
OH
OH
OHO
OH
CH3
O
O
CH3
O
CH3
O
N
CH3
CH3
OCH3
O
CH3OCH3
NH
CH3
O
N
CH3
CH3
OCH3
O
CH3OCH3
N
SO
OOH
O
OH
OOH
CH3
O
N
CH3
CH3
OCH3O
CH3
N
O
CH3
OH
Results
Manual Review and UpdateAutomation Option
Web Portal
ACD/Spectrus Processor
Report
ACD/Spectrus
Data Input Metabolite Prediction and Verification Knowledge
Management
Richard Lee,1 Vitaly Lashin,2 Andrey Paramonov,2 Alexandr
Sakharov21Advanced Chemistry Development, Inc. (ACD/Labs), 8 King
Street East, Toronto, ON. M5C 1B5. Canada2ACD/Labs, Moscow,
Russia
1-800-304-3988 www.acdlabs.com/metasense
[email protected]
METABOLITE PREDICTION AND VERIFICATION
Predicted metabolites were restricted to phase 1 and 2, and
metabolite target lists were generated in 3 parts:
1. A regio-selective model was used to predict expected
metabolite structures.
2. Predicted metabolites were detected based on their accurate
mass and theoretical isotope pattern. Unexpected metabolites were
detected employing a fractional mass filter.
3. Structures were verified by comparing the MS2 spectra of the
parent and metabolite.
REGIO-SELECTIVE MODEL Markush structures could also be generated
in lieu of discrete structures.
WEB PORTAL
A java based web portal communicates the results and increases
collaborative efforts. The viewer shown includes a display of the
biotransformation map as the main feature.
Search capabilities:• Metadata searching• Structure search by
exact, substructure or similar
structure• Similar structure, and exact structure, search
via
a drawing applet
Identify Hotspots Apply Biotransformation Rules Generate
Metabolites
