Q0I0A8 AF NFT

Elongation factor G 1

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihajmjfp2worfgdc6umbdnqu2ouohvzwnvlhuqfyl3zy2h7ljldhq/metadata.json
IPFS of structure file: 
bafybeic2mizczmngbw3hoc644ljx5hte2uxstzmdxifoz7ifoqfi3pnnly/AF-Q0I0A8-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xbb2F1C7CB3A1eeFAc24fCa72cc627162D5413FD7
First NFT owner address (bech32): 
genesis1hvh3cl9n58h04sj0efevccn3vt25z07h70j2hm
Current NFT ID #111044 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
111044
Accession (UniProt):
Q0I0A8
Name::
Elongation factor G 1
Experimental Method:
Predicted structure
Sequence source:
Shewanella sp. (strain MR-7)

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 Q0I0A8 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q0I0A8|EFG1_SHESR Elongation factor G 1 OS=Shewanella sp. (strain MR-7) OX=60481 GN=fusA1 PE=3 SV=1 MARTTPIERYRNIGICAHVDAGKTTTTERVLFYTGLSHKIGEVHDGAATTDWMVQEQERGITITSAAVTTFWRGMDAQFTEHRINIIDTPGHVDFTIEVERSLRVLDGAVVVFCGSSGVEPQSETVWRQADKYRVPRLVFVNKMDRAGADFERVVKQIRTRLGATCVPIQLNIGAEENFTGVIDLIKMKAINWNEADQGMTFTYEEIPASLAAKAAEMHEYLVEAAAEASDELMDKYLEEGTLSEDEIKKALRQRTINNEIVLATCGSAFKNKGVQAVLDAVVEFLPAPVDVPPIKGIDDDEQEVERPSDDNAPFAALAFKIATDPFVGTLTFIRVYSGVLESGSGVYNSVKQKRERIGRIVQMHANDRTELKEVRAGDIAAAIGLKEVTTGDTLCDPDHKVILERMEFPEPVITIAVEPKSKADQDKMGIALQKLAAEDPSFRVETDEESSQTLISGMGELHLDIIVDRMRREFGVECNVGKPQVAYRETIRASVEAEGKFVRQSGGRGQFGHVWLKLEPNEEGAGYEFINAIVGGVVPREFIPAVDKGIQEQMKNGVLAGFPVLDVKVTLFDGSYHDVDSNEMAFKIAGSMGFKKGALEANPVLLEPCMKVEVTTPENYMGDVVGDLNRRRGLIEGMDDGFGGIKIVHAVVPLSEMFGYATDLRSATQGRASYSMEFLKYSDAPQNIAKAIIESRS