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Key Documents

M0876

Sigma-Aldrich

L-Methionine sulfone

≥98% (TLC)

Synonym(s):

L-2-Amino-4-(methylsulfonyl)butanoic acid

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About This Item

Empirical Formula (Hill Notation):
C5H11NO4S
CAS Number:
Molecular Weight:
181.21
Beilstein:
1725510
EC Number:
MDL number:
UNSPSC Code:
12352209
PubChem Substance ID:
NACRES:
NA.26

product name

L-Methionine sulfone,

Assay

≥98% (TLC)

Quality Level

form

powder or crystals

mp

275 °C

application(s)

detection
peptide synthesis

SMILES string

CS(=O)(=O)CC[C@H](N)C(O)=O

InChI

1S/C5H11NO4S/c1-11(9,10)3-2-4(6)5(7)8/h4H,2-3,6H2,1H3,(H,7,8)/t4-/m0/s1

InChI key

UCUNFLYVYCGDHP-BYPYZUCNSA-N

Gene Information

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Biochem/physiol Actions

L-Methionine sulfone may be used to study pupae development of the silkworm Bombyx mori L. L-Methionine sulfone may be used as a complexing agent to study conformational structures and stereospecificity of enzymes such as glutamate synthase and gamma-glutamyl transpeptidase.

Storage Class Code

11 - Combustible Solids

WGK

WGK 3

Flash Point(F)

Not applicable

Flash Point(C)

Not applicable

Personal Protective Equipment

dust mask type N95 (US), Eyeshields, Gloves

Certificates of Analysis (COA)

Search for Certificates of Analysis (COA) by entering the products Lot/Batch Number. Lot and Batch Numbers can be found on a product’s label following the words ‘Lot’ or ‘Batch’.

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The amino acid profile of plants is an important parameter in assessments of their growth potential, resource-use efficiency and/or quality as food and feed. Screening studies may involve large number of samples but the classical amino acid analysis is limited
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The origin of smooth muscle cells in developing atherosclerotic lesions is a controversial topic with accumulating evidence indicating that at least some arterial smooth muscle cells might originate from bone marrow-derived smooth muscle cell precursors circulating in the blood. The
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Cellular metabolism is dynamic, but quantifying non-steady metabolic fluxes by stable isotope tracers presents unique computational challenges. Here, we developed an efficient 13C-tracer dynamic metabolic flux analysis (13C-DMFA) framework for modeling central carbon fluxes that vary over time. We used

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