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MYP_000614
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Basic Information
Antidiuretic factor A
Hormonal / Endocrine ▸ Hormone peptide
Neurological / Signaling ▸ Neuromodulation
Neurological / Signaling ▸ Neuropeptide activity ▸ Neuropeptide
Regulatory peptide ▸ Biological regulation
Standard
14 amino acids
C71H103N19O20
Standard
Sequence
VVNTPGHAVSYHVY
Physicochemical Analysis
1542.69 Da
6.89
-0.09
-0.41
-0.0067
0.19
0.34
0.30
6.65
90.00
0.1429
2980.00
2980.00
The radar chart summarizes major physicochemical dimensions for quick comparison, while exact numerical values remain listed on the left.
Residue Composition
Amino Acid Composition
Chemical Descriptors
614.20
-5.44
21.0
22.0
42.0
110.0
5.0
14.0
Structural Visualization
3D PDB MODEL
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2D CHEMICAL STRUCTURE
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Experimental Records
RECORD: Rec_0017613 VERIFIED: NO
Provenance & Taxonomy
Tenebrio molitor [Animal]
Structure & Mods
linear peptide [Linear]
canonical L-amino-acid peptide [L]
Bio-Activity Profile
Hormone
Malpighian tubules
RECORD: Rec_0100562 VERIFIED: YES
Provenance & Taxonomy
Tenebrio molitor [Animal]
Antidiuretic factor
7067
Structure & Mods
linear peptide [Linear]
canonical L-amino-acid peptide [L]
Bio-Activity Profile
Hormone Endocrine Neuropeptide Neuromodulator Metabolic regulation Physiological regulation
Mammalian: 100 hour; Yeast: >20 hour; E. coli: >10 hour
PaperSource-linked PubMed record(s) for Antidiuretic factor A (Tenebrio molitor): PMID 15235016 PMID15235016 Evidence URLhttps://pubmed.ncbi.nlm.nih.gov/15235016/
RECORD: Rec_0107454 VERIFIED: YES
Provenance & Taxonomy
Tenebrio molitor [Animal]
7067
Structure & Mods
linear peptide [Linear]
canonical L-amino-acid peptide [L]
Bio-Activity Profile
-
PMID11756661 Evidence URLhttps://pubmed.ncbi.nlm.nih.gov/11756661/
RECORD: Rec_0170064 VERIFIED: YES
Provenance & Taxonomy
not reported [other]
Structure & Mods
linear peptide [Linear]
canonical L-amino-acid peptide [L]
Bio-Activity Profile
Neuropeptide
Paper数据库级溯源文献：Wang Y, Wang M, Yin S, et al. NeuroPep: a comprehensive resource of neuropeptides. Database (Oxford). 2015:bav038. PMID 25931458; Bin Y, Zhang W, Tang W, et al. Prediction of Neuropeptides from Sequence Information Using Ensemble Classifier and Hybrid Features. J Proteome Res. 2020;19(9):3732-3740. PMID 32786686. PMID25931458;32786686 Evidence URLhttps://pubmed.ncbi.nlm.nih.gov/25931458/