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MYP_002270
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Basic Information
Periviscerokinin-3
Neurological / Signaling ▸ Neuromuscular and muscle activity ▸ Myoactive peptide
Neurological / Signaling ▸ Neuromuscular and muscle activity ▸ Myotropic activity
Neurological / Signaling ▸ Neuropeptide activity ▸ Neuropeptide
Neurological / Signaling ▸ Visceral muscle modulation
Standard
9 amino acids
C51H82N14O12
Standard
Sequence
QNLIPFPRV
Physicochemical Analysis
1083.28 Da
9.75
0.76
0.56
0.0845
0.07
0.46
0.09
40.11
118.89
0.1111
0.00
0.00
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
426.62
-2.32
13.0
13.0
31.0
77.0
3.0
10.0
Structural Visualization
3D PDB MODEL
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2D CHEMICAL STRUCTURE
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Experimental Records
RECORD: Rec_0123124 VERIFIED: YES
Provenance & Taxonomy
Daphnia pulex [Animal]
Periviscerokinin
6669
Structure & Mods
linear peptide [Linear]
canonical L-amino-acid peptide [L]
Bio-Activity Profile
Myotropic
Mammalian: 0.8 hour; Yeast: 10 min; E. coli: >10 hour
PaperGenomics, transcriptomics, and peptidomics of Daphnia pulex neuropeptides and protein hormones PMID21830762 Evidence URLhttps://pubmed.ncbi.nlm.nih.gov/21830762/
RECORD: Rec_0361263 VERIFIED: YES
Provenance & Taxonomy
Daphnia pulex [Animal]
Periviscerokinin
6669
Structure & Mods
linear peptide [Linear]
canonical L-amino-acid peptide [L]
Pyroglutamate
Amidation
Bio-Activity Profile
Neuropeptide Visceral activity Myoactive
PaperGenomics, transcriptomics, and peptidomics of Daphnia pulex neuropeptides and protein hormones PMID21830762 Evidence URLhttps://pubmed.ncbi.nlm.nih.gov/21830762/
RECORD: Rec_0389833 VERIFIED: YES
Provenance & Taxonomy
not reported [other]
CAPA
Structure & Mods
linear peptide [Linear]
canonical L-amino-acid peptide [L]
Amidation
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/