Q9LV48 AF NFT

Proline-rich receptor-like protein kinase PERK1

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeie6inssl2llunktuptutduj4nf2gvyha55tlvtbcllaa3qpycsequ/metadata.json
IPFS of structure file: 
bafybeiem46v2ybkmvna6zebjtupjgyyvigxa2tc4jcqnfaj7jg2r7mzg3i/AF-Q9LV48-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x0787bC904B7be1a8Bd84a0CF1b68B9B4567D88eb
First NFT owner address (bech32): 
genesis1q7rmeyzt00s630vy5r83k69ek3t8mz8tr6xpum
Current NFT ID #294132 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
294132
Accession (UniProt):
Q9LV48
Name::
Proline-rich receptor-like protein kinase PERK1
Experimental Method:
Predicted structure
Sequence source:
ARABIDOPSIS THALIANA

NFT data

MolNFT AF v1 is an AlphaFold database of AI predicted Swiss-Prot protein sequences preserved as regular ERC-721 NFT tokens on GenesisL1 blockchain for public free use, research and entertainment:

https://alphafold.ebi.ac.uk/
Jumper, J., Evans, R., Pritzel, A. et al. Highly accurate protein structure prediction with AlphaFold. 
Nature 596, 583–589 (2021). https://doi.org/10.1038/s41586-021-03819-2

MOLNFT Q9LV48 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9LV48|PERK1_ARATH Proline-rich receptor-like protein kinase PERK1 OS=Arabidopsis thaliana OX=3702 GN=PERK1 PE=1 SV=1 MSTAPSPGTTPSPSPPSPPTNSTTTTPPPAASSPPPTTTPSSPPPSPSTNSTSPPPSSPLPPSLPPPSPPGSLTPPLPQPSPSAPITPSPPSPTTPSNPRSPPSPNQGPPNTPSGSTPRTPSNTKPSPPSDSSDGLSTGVVVGIAIGGVAILVILTLICLLCKKKRRRRHDDEAAYYVPPPPPSGPKAGGPYGGQQQYWQQQNASRPSDNHVVTSLPPPKPPSPPRKPPPPPPPPAFMSSSGGSDYSDLPVLPPPSPGLVLGFSKSTFTYEELSRATNGFSEANLLGQGGFGYVHKGILPSGKEVAVKQLKAGSGQGEREFQAEVEIISRVHHRHLVSLIGYCMAGVQRLLVYEFVPNNNLEFHLHGKGRPTMEWSTRLKIALGSAKGLSYLHEDCNPKIIHRDIKASNILIDFKFEAKVADFGLAKIASDTNTHVSTRVMGTFGYLAPEYAASGKLTEKSDVFSFGVVLLELITGRRPVDANNVYVDDSLVDWARPLLNRASEEGDFEGLADSKMGNEYDREEMARMVACAAACVRHSARRRPRMSQIVRALEGNVSLSDLNEGMRPGHSNVYSSYGGSTDYDTSQYNDDMIKFRKMALGTQEYGTTGEYSNPTSDYGLYPSGSSSEGQATREMEMGKIKKTGQGYSGPSL