Q9NT22 AF NFT

EMILIN-3

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidp346poyybews2g2kobb23k5k7jlpsli2uyt6pvzfy5dlpo5cuwi/metadata.json
IPFS of structure file: 
bafybeifw74hvvyc2wtudwxirmwvycowxla4zmm2b7i3iv43wtw2cknjuq4/AF-Q9NT22-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x779b368283e79942739fEb126753AC2b434CE90e
First NFT owner address (bech32): 
genesis1w7dndq5ru7v5yuulavfxw5av9dp5e6gwcymwmf
Current NFT ID #116181 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
116181
Accession (UniProt):
Q9NT22
Name::
EMILIN-3
Experimental Method:
Predicted structure
Sequence source:
HOMO SAPIENS

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 Q9NT22 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9NT22|EMIL3_HUMAN EMILIN-3 OS=Homo sapiens OX=9606 GN=EMILIN3 PE=1 SV=2 MGRRRLLVWLCAVAALLSGAQARGTPLLARPAPPGASRYSLYTTGWRPRLRPGPHKALCAYVVHRNVTCILQEGAESYVKAEYRQCRWGPKCPGTVTYRTVLRPKYKVGYKTVTDLAWRCCPGFTGKRCPEHLTDHGAASPQLEPEPQIPSGQLDPGPRPPSYSRAAPSPHGRKGPGLFGERLERLEGDVQRLAQTYGTLSGLVASHEDPNRMTGGPRAPAVPVGFGVIPEGLVGPGDRARGPLTPPLDEILSKVTEVSNTLQTKVQLLDKVHGLALGHEAHLQRLREAPPSPLTSLALLEEYVDRRLHRLWGSLLDGFEQKLQGVQSECDLRVQEVRRQCEEGQAASRRLHQSLDGRELALRQELSQLGSQLQGLSVSGRGSCCGQLALINARMDGLERALQAVTETQRGPGAPAGDELTRLSAAMLEGGVDGLLEGLETLNGTEGGARGCCLRLDMGGWGVGGFGTMLEERVQSLEERLATLAGELSHDSASPGRSARPLVQTELAVLEQRLVSLETSCTPSTTSAILDSLVAEVKAWQSRSEALLRQVASHAALLQQLNGTVAEVQGQLAEGTGSSLQGEITLLKVNLNSVSKSLTGLSDSVSQYSDAFLAANTSLDERERKVEAEVQAIQEQVSSQGSRLQAGHRQVLNLRGELEQLKAGVAKVASGLSRCQDTAQKLQHTVGHFDQRVAQVEGACRRLGLLAAGLDSLPTEPLRPREGLWSHVDQLNRTLAQHTQDIARLRDDLLDCQAQLAEQVRPGQAN