52332
Phenylmethylsulfonyl Fluoride
Phenylmethylsulfonyl Fluoride, CAS 329-98-6, is an irreversible inhibitor of serine proteases. It causes sulfonylation of the active-site serine residues.
Synonyme(s) :
Phenylmethylsulfonyl Fluoride, Benzylsulfonyl Fluoride, PMSF
Se connecter pour consulter les tarifs organisationnels et contractuels.
Sélectionner une taille de conditionnement
Changer de vue
A propos de cet article
Formule empirique (notation de Hill) :
C7H7FO2S
Numéro CAS:
Poids moléculaire :
174.19
UNSPSC Code:
12352202
NACRES:
NA.77
MDL number:
Assay:
≥99% (GC)
Form:
crystalline solid
Quality level:
Storage condition:
OK to freeze, desiccated
Service technique
Besoin d'aide ? Notre équipe de scientifiques expérimentés est là pour vous.
Laissez-nous vous aiderQuality Level
description
RTECS - XT8040000
assay
≥99% (GC)
form
crystalline solid
manufacturer/tradename
Calbiochem®
storage condition
OK to freeze, desiccated
color
white to off-white
solubility
ethanol: soluble, isopropanol: soluble, methanol: soluble
shipped in
ambient
storage temp.
10-30°C
SMILES string
F[S](=O)(=O)Cc1ccccc1
InChI
1S/C7H7FO2S/c8-11(9,10)6-7-4-2-1-3-5-7/h1-5H,6H2
InChI key
YBYRMVIVWMBXKQ-UHFFFAOYSA-N
General description
Irreversible inhibitor of serine proteases. Its mechanism of action is analogous to that of diisopropylfluorophosphate. PMSF causes sulfonylation of the active-site serine residues. Also reported to inhibit internucleosomal DNA fragmentation in immature thymocytes. For a related, more stable inhibitor, see AEBSF (Cat. No. 101500).
Biochem/physiol Actions
Cell permeable: no
Primary Target
serine proteases
serine proteases
Product does not compete with ATP.
Reversible: no
Preparation Note
Following reconstitution, refrigerate (4°C). Stock solutions are stable for up to 9 months at 4°C.
t½ = 1 hour at pH 7.5. Effective concentration: 50 μM.
Other Notes
Due to the nature of the Hazardous Materials in this shipment, additional shipping charges may be applied to your order. Certain sizes may be exempt from the additional hazardous materials shipping charges. Please contact your local sales office for more information regarding these charges.
Seitz, R., et al. 1993. Int. J. Cancer53, 514.
Weaver, V.M., et al. 1993. Biochem. Cell. Biol.71, 488.
Bourgain, R.H., et al. 1992. Adv. Exp. Med. Biol.316, 427.
Chang, C.T., et al. 1992. Biochem. Int.28, 707.
Weaver, V.M., et al. 1993. Biochem. Cell. Biol.71, 488.
Bourgain, R.H., et al. 1992. Adv. Exp. Med. Biol.316, 427.
Chang, C.T., et al. 1992. Biochem. Int.28, 707.
Legal Information
CALBIOCHEM is a registered trademark of Merck KGaA, Darmstadt, Germany
Disclaimer
Toxicity: Corrosive (L)
signalword
Danger
hcodes
Hazard Classifications
Acute Tox. 3 Oral - Skin Corr. 1B
Classe de stockage
6.1A - Combustible acute toxic Cat. 1 and 2 / very toxic hazardous materials
wgk
WGK 3
flash_point_f
Not applicable
flash_point_c
Not applicable
Certificats d'analyse (COA)
Recherchez un Certificats d'analyse (COA) en saisissant le numéro de lot du produit. Les numéros de lot figurent sur l'étiquette du produit après les mots "Lot" ou "Batch".
Déjà en possession de ce produit ?
Retrouvez la documentation relative aux produits que vous avez récemment achetés dans la Bibliothèque de documents.
Contenu apparenté
Ming Chang et al.
Bio-protocol, 7(8), e2227-e2227 (2017-04-20)
Arabidopsis pollen is an excellent system for answering important biological questions about the establishment and maintenance of cellular polarity and polar cell growth, because these processes are amenable to the genetic and genomic approaches that are readily available in Arabidopsis.
Siqi Ming et al.
Frontiers in immunology, 12, 736269-736269 (2021-10-01)
Gastric CD4+T cells contribute to Helicobacter pylori (H. pylori)-induced gastritis by amplifying mucosal inflammation and exacerbating mucosal injuries. However, the pathogenic CD4+ T cell subset involved in gastritis and the potential regulators are still unclear. Here we identified an IL-21-producing
Fabrizio Clarelli et al.
PLoS computational biology, 16(8), e1008106-e1008106 (2020-08-17)
Antibiotic resistance is rising and we urgently need to gain a better quantitative understanding of how antibiotics act, which in turn would also speed up the development of new antibiotics. Here, we describe a computational model (COMBAT-COmputational Model of Bacterial