Q0HNU0 AF NFT

Elongation factor G 1

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeie5egxjq6yj6tndwslpjq6metmgdkmff4tbi6pzmcaxi7n642k6ja/metadata.json
IPFS of structure file: 
bafybeie63ew7zkkahywqgw7ccvh3axzwwgwqholva4keaxfktuky53hg7a/AF-Q0HNU0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x9e5E98E011361C5888c92e2CDb7652E02Bd5C7Ed
First NFT owner address (bech32): 
genesis1ne0f3cq3xcw93zxf9ckdkajjuq4at3ldwq49kv
Current NFT ID #111043 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
111043
Accession (UniProt):
Q0HNU0
Name::
Elongation factor G 1
Experimental Method:
Predicted structure
Sequence source:
Shewanella sp. (strain MR-4)

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 Q0HNU0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q0HNU0|EFG1_SHESM Elongation factor G 1 OS=Shewanella sp. (strain MR-4) OX=60480 GN=fusA1 PE=3 SV=1 MARTTPIERYRNIGICAHVDAGKTTTTERVLFYTGLSHKIGEVHDGAATTDWMVQEQERGITITSAAVTTFWRGMDAQFTEHRINIIDTPGHVDFTIEVERSLRVLDGAVVVFCGSSGVEPQSETVWRQADKYRVPRLVFVNKMDRAGADFERVVKQIRTRLGATCVPIQLNIGAEENFTGVIDLIKMKAINWNEADQGMTFTYEEIPASLAAKAAEMHEYLVEAAAEASDELMDKYLEEGTLSEDEIKKALRQRTINNEIVLATCGSAFKNKGVQAVLDAVVEFLPAPVDVPPIKGIDDDEQEVERPSDDNAPFAALAFKIATDPFVGTLTFIRVYSGVLESGSGVYNSVKQKRERIGRIVQMHANDRTELKEVRAGDIAAAIGLKEVTTGDTLCDPDHKVILERMEFPEPVITIAVEPKSKADQDKMGIALQKLAAEDPSFRVETDEESSQTLISGMGELHLDIIVDRMRREFGVECNVGKPQVAYRETIRASVEAEGKFVRQSGGRGQFGHVWLKLEPNEEGAGYEFINAIVGGVVPREFIPAVDKGIQEQMKNGVLAGFPVLDVKVTLFDGSYHDVDSNEMAFKIAGSMGFKKGALEANPVLLEPCMKVEVTTPENYMGDVVGDLNRRRGLIEGMDDGFGGIKIVHAVVPLSEMFGYATDLRSATQGRASYSMEFLKYSDAPQNIAKAIIESRS