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.
商品は「研究用試薬」です。人や動物の医療用・臨床診断用・食品用の製品ではありません。
研究用途以外に使用した場合、当社は一切の責任を負いかねます。
- CAS 番号: 752211-90-8
- 分子式: C22H32O4
- 分子量:360.49
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保管条件:
Please store the product under the recommended conditions in the Certificate of Analysis.
Endogenous Metabolite アイソフォーム固有の製品をすべて表示
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生物活性
製品説明
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] |
化学情報
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CAS 番号 752211-90-8
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分子量 360.49
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分子式 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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別名
(+)-Dictyvaric acid
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Structure Classification
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Initial Source
Dictyopteris divaricata
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輸送条件
Room temperature in continental US; may vary elsewhere.
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保管条件
Please store the product under the recommended conditions in the Certificate of Analysis.
プロトコル
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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.
純度とドキュメンテーション
参考文献
Calculators
濃度 (開始) × 体積 (開始) = 濃度 (終了) × 体積 (終了)