Dictyvaric acid
Dictyvaric acid ((+)-Dictyvaric acid) is a novel sesquiterpene-substituted benzoic acid-type marine secondary metabolite isolated from the brown alga Dictyopteris divaricata. Dictyvaric acid’s congeneric analogs exhibit anti-tumor and antibacterial biological potential, and sulfide and sesquiterpene hydroquinone derivatives from congeneric algae can target EGFR and VEGFR kinases. Dictyvaric acid can be used in research related to cancers such as liver cancer and breast cancer.
For research use only. We do not sell to patients.
- CAS No.: 752211-90-8
- Formula: C22H32O4
- Molecular Weight:360.49
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Storage:
Please store the product under the recommended conditions in the Certificate of Analysis.
All Endogenous Metabolite Isoforms
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Biological Activity
Description
Cellular Effect
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Cell Line
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Type | Value | Description | References |
|---|---|---|---|---|
| HepG2 | EC50 |
50 μM
Compound: 34
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Antiproliferative activity against human HepG2 cells assessed as inhibition of cell proliferation incubated for 72 hrs by MTT assay
Antiproliferative activity against human HepG2 cells assessed as inhibition of cell proliferation incubated for 72 hrs by MTT assay
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[PMID: 34653771] |
| MCF7 | EC50 |
50 μM
Compound: 34
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Antiproliferative activity against human MCF7 cells assessed as inhibition of cell proliferation incubated for 72 hrs by MTT assay
Antiproliferative activity against human MCF7 cells assessed as inhibition of cell proliferation incubated for 72 hrs by MTT assay
|
[PMID: 34653771] |
Chemical Information
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CAS No. 752211-90-8
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Molecular Weight 360.49
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Formula C22H32O4
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SMILES
C[C@@]12[C@H]([C@](O)(CC[C@@]1([H])C(C)(CCC2)C)C)CC3=CC(C(O)=O)=CC=C3O
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Synonyms
(+)-Dictyvaric acid
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Structure Classification
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Initial Source
Dictyopteris divaricata
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Shipping
Room temperature in continental US; may vary elsewhere.
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Storage
Please store the product under the recommended conditions in the Certificate of Analysis.
Protocols
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Research Protocol for Infectious Diseases
Infectious-disease experiments test how pathogens interact with host barriers, innate immune receptors, inflammatory signaling, pathogen replication, and tissue injury; pattern-recognition receptors such as TLRs, RIG-I-like receptors, NOD-like receptors, and inflammasomes detect microbial molecules and activate NF-κB, interferon, and cytokine responses. The central hypothesis is that infection severity reflects the balance between pathogen burden and host response: protective inflammation restricts pathogen growth, whereas excessive or mislocalized inflammation contributes to tissue damage and disease phenotype. Unresolved questions include which host pathways are protective versus pathogenic, why some infection models fail to translate to human disease, and which combined readouts best predict clinically relevant infection outcomes.
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Liver Cancer Modeling
Liver cancer can be classified into primary liver cancer and secondary liver cancer. Secondary liver cancer is the metastatic liver cancer. Primary liver cancer includes hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC) and fibrolamellar HCC, of which HCC is the most common form, accounting for approximately 90% of primary liver cancers[1]. HCC mouse models include chemical agent-induced models, transplanted tumor models, and genetic engineered models.
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Breast Cancer Modeling
Breast cancer is a heterogeneous cancer, and it has been distinguished into four subtypes: luminal A, luminal B, HER2-positive and basal-like. Molecular mutations, epigenetic alterations, hormone exposure and immune microenvironment are related to the progression of breast cancer.
Purity & Documentation
References
Calculators
Concentration (start) × Volume (start) = Concentration (final) × Volume (final)