Q9FNK4 Ornithine aminotransferase, mitochondrial MolNFT, Molecular NFT on GenesisL1

Ornithine aminotransferase, mitochondrial

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeidy646z7pgqtnw4ammjgcovxfxddwwkvpe5soeskw47e4ug5l2nva/metadata.json

IPFS of structure file:

bafybeicrh7gelsjveqlnpnxk2zb6tljdgnmgki24s4slxzcadd7arx6m2q/AF-Q9FNK4-F1-model_v2.pdb

First NFT owner address (eip-55):

0x38047ce090cAC00B9195040abFba84F85133149B

First NFT owner address (bech32):

genesis18qz8ecysetqqhyv4qs9tlw5ylpgnx9ymh3ewsv

Current NFT ID #279037 owner (web3):

0xBDaba9F1bAE78Bc8b4574B9BB809390289445980

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
279037
Accession (UniProt):
Q9FNK4
Name::
Ornithine aminotransferase, mitochondrial
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 Q9FNK4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9FNK4|OAT_ARATH Ornithine aminotransferase, mitochondrial OS=Arabidopsis thaliana OX=3702 GN=DELTA-OAT PE=1 SV=1 MAATTRRLLYYVSKRFSTAGVRRSYGGLPQSNSKSPPSSSQRLMELESEFSAHNYHPVPVVFSRANGSTIWDPEGKRYIDFLAAYSAVNQGHCHPKIMKALQEQVEKLTLSSRAFYNDKFPVFAERLTNMFGYDMVLPMNTGAEGVETALKLARKWGHEKKNIPKDEAIIVSCCGCFHGRTLAIVSMSCDNDATRGFGPLLPGNLKVDFGDADSLEKIFKEKGDRIAGFLFEPIQGEAGVIIPPDGYLKAVRELCTKYNVLMIADEVQSGLARSGKMLACDWEEIRPDMVILGKALGGGVIPVSAVLADKDVMLHIKPGQHGSTFGGNPLASAVAMASLDVIVEEKLVERSASLGEELRIQLNEIKKQFPKYIKEVRGRGLFNAIEFNSESLSPVSAYDICLSLKERGVLAKPTHNTIVRLTPPLSISSDELRDGSEALHDVLELDLPNLLKINSGKTPVSHITECDRCGRNLYA

Q9FNK4 AF NFT

MOLNFT AF v1

NFT data

MOLNFT Q9FNK4 research and analysis (ICN3D with VR)

FASTA sequences

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