Record Information |
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Version | 1.0 |
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Created at | 2024-02-22 12:28:48 UTC |
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Updated at | 2024-04-19 10:11:09 UTC |
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NP-MRD ID | NP0332554 |
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Secondary Accession Numbers | None |
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Natural Product Identification |
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Common Name | Methyl 2-(4-hydroxyphenyl) acetate |
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Description | 3-Acetamido-4-hydroxybenzoic acid belongs to the class of organic compounds known as hydroxybenzoic acid derivatives. Hydroxybenzoic acid derivatives are compounds containing a hydroxybenzoic acid (or a derivative), which is a benzene ring bearing a carboxyl and a hydroxyl groups. It was first documented in 2024 (PMID: 38385307). Based on a literature review a significant number of articles have been published on 3-acetamido-4-hydroxybenzoic acid (PMID: 38385306) (PMID: 38385285) (PMID: 38385217) (PMID: 38385191) (PMID: 38385188) (PMID: 38385167). |
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Structure | CC(=O)NC1=CC(=CC=C1O)C(O)=O InChI=1S/C9H9NO4/c1-5(11)10-7-4-6(9(13)14)2-3-8(7)12/h2-4,12H,1H3,(H,10,11)(H,13,14) |
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Synonyms | Value | Source |
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3-(Acetylamino)-4-hydroxybenzoic acid | ChEBI | 3-Acetylamino-4-hydroxybenzoic acid | ChEBI | 3-(Acetylamino)-4-hydroxybenzoate | Generator | 3-Acetylamino-4-hydroxybenzoate | Generator | 3-Acetamido-4-hydroxybenzoate | Generator |
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Chemical Formula | C9H9NO4 |
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Average Mass | 195.1740 Da |
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Monoisotopic Mass | 195.05316 Da |
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IUPAC Name | 3-acetamido-4-hydroxybenzoic acid |
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Traditional Name | 3-acetamido-4-hydroxybenzoic acid |
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CAS Registry Number | Not Available |
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SMILES | CC(=O)NC1=CC(=CC=C1O)C(O)=O |
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InChI Identifier | InChI=1S/C9H9NO4/c1-5(11)10-7-4-6(9(13)14)2-3-8(7)12/h2-4,12H,1H3,(H,10,11)(H,13,14) |
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InChI Key | BXBFVCYLJXGOGI-UHFFFAOYSA-N |
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Experimental Spectra |
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| Spectrum Type | Description | Depositor Email | Depositor Organization | Depositor | Deposition Date | View |
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1D NMR | [13C, ] NMR Spectrum (2D, 151 MHz, C2D6OS, experimental) | yijing0212@163.com | 南方医科大学 | Jing Yi | 2024-02-22 | View Spectrum | 1D NMR | [1H, ] NMR Spectrum (2D, 600 MHz, C2D6OS, experimental) | yijing0212@163.com | 南方医科大学 | Jing Yi | 2024-02-22 | View Spectrum | 1D NMR | 1H NMR Spectrum (1D, 600.133705802 MHz, C2D6OS, simulated) | Wishart Lab | Wishart Lab | David Wishart | 2021-06-20 | View Spectrum | 1D NMR | 13C NMR Spectrum (1D, 150.918653341 MHz, C2D6OS, simulated) | Wishart Lab | Wishart Lab | David Wishart | 2021-06-20 | View Spectrum |
| Predicted Spectra |
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| Not Available | Chemical Shift Submissions |
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| Not Available | Species |
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Species of Origin | Not Available |
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Chemical Taxonomy |
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Description | Belongs to the class of organic compounds known as hydroxybenzoic acid derivatives. Hydroxybenzoic acid derivatives are compounds containing a hydroxybenzoic acid (or a derivative), which is a benzene ring bearing a carboxyl and a hydroxyl groups. |
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Kingdom | Organic compounds |
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Super Class | Benzenoids |
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Class | Benzene and substituted derivatives |
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Sub Class | Benzoic acids and derivatives |
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Direct Parent | Hydroxybenzoic acid derivatives |
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Alternative Parents | |
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Substituents | - Hydroxybenzoic acid
- Benzoic acid
- Benzoyl
- 1-hydroxy-2-unsubstituted benzenoid
- Phenol
- Carboximidic acid
- Carboximidic acid derivative
- Organic 1,3-dipolar compound
- Propargyl-type 1,3-dipolar organic compound
- Carboxylic acid derivative
- Carboxylic acid
- Organic nitrogen compound
- Organonitrogen compound
- Organooxygen compound
- Hydrocarbon derivative
- Organic oxide
- Organic oxygen compound
- Aromatic homomonocyclic compound
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Molecular Framework | Aromatic homomonocyclic compounds |
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External Descriptors | Not Available |
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Physical Properties |
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State | Not Available |
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Experimental Properties | Property | Value | Reference |
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Melting Point | Not Available | Not Available | Boiling Point | Not Available | Not Available | Water Solubility | Not Available | Not Available | LogP | Not Available | Not Available |
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Predicted Properties | |
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General References | - Jimenez JAM, Egan J, Randle RI, Rezig AO, Orimolade BO, Ginesi RE, Schweins R, Riehle MO, Draper ER: Tuning conductivity while maintaining mechanical properties in perylene bisimide hydrogels at physiological pH. Chem Commun (Camb). 2024 Feb 22. doi: 10.1039/d3cc04557a. [PubMed:38385307 ]
- Chung JT, Rafiei M, Chau Y: Self-adjuvanted L-arginine-modified dextran-based nanogels for sustained local antigenic protein delivery to antigen-presenting cells and enhanced cellular and humoral immune responses. Biomater Sci. 2024 Feb 22. doi: 10.1039/d3bm01150j. [PubMed:38385306 ]
- Pavlovic M, Margetic A, Leonardi A, Krizaj I, Kojic M, Vujcic Z, Sokarda Slavic M: Improvement of fruit juice quality: novel endo-polygalacturonase II from Aspergillus tubingensis FAT 43 for enhanced liquefaction, clarification, and antioxidant potential. Food Funct. 2024 Feb 22. doi: 10.1039/d3fo05297d. [PubMed:38385285 ]
- Sarkar R, Korell A, Schneider C: Organocatalytic enantioselective oxa-Piancatelli rearrangement. Chem Commun (Camb). 2024 Feb 22. doi: 10.1039/d4cc00708e. [PubMed:38385217 ]
- Antequera CM, Orleck K, Jacob R, Kenneally A, Wright WL: Potassium-competitive acid blockers: rethinking acid suppression for gastroesophageal reflux disease and Helicobacter pylori. Postgrad Med. 2024 Feb 22. doi: 10.1080/00325481.2024.2320081. [PubMed:38385191 ]
- Edvinsson C, Bjornsson O, Erlandsson L, Hansson SR: Predicting intensive care need in women with preeclampsia using machine learning - a pilot study. Hypertens Pregnancy. 2024 Dec;43(1):2312165. doi: 10.1080/10641955.2024.2312165. Epub 2024 Feb 22. [PubMed:38385188 ]
- Alzahrani AY, Gomha SM, Zaki ME, Farag B, Abdelgawad FE, Mohamed MA: Chitosan-sulfonic acid-catalyzed green synthesis of naphthalene-based azines as potential anticancer agents. Future Med Chem. 2024 Feb 22. doi: 10.4155/fmc-2023-0351. [PubMed:38385167 ]
- Li Y, Li C, Fu Y, Zhang Q, Ma J, Zhou J, Li J, Du G, Liu S: A CRISPR/Cas9-based visual toolkit enabling multiplex integration at specific genomic loci in Aspergillus niger. Synth Syst Biotechnol. 2024 Feb 10;9(2):209-216. doi: 10.1016/j.synbio.2024.01.014. eCollection 2024 Jun. [PubMed:38385153 ]
- He J, Wu W, Wang X: DIProT: A deep learning based interactive toolkit for efficient and effective Protein design. Synth Syst Biotechnol. 2024 Feb 8;9(2):217-222. doi: 10.1016/j.synbio.2024.01.011. eCollection 2024 Jun. [PubMed:38385151 ]
- Uemura Y, Tsukagoshi H: Quantitative analysis of lateral root development with time-lapse imaging and deep neural network. Quant Plant Biol. 2024 Feb 13;5:e1. doi: 10.1017/qpb.2024.2. eCollection 2024. [PubMed:38385121 ]
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