Q3JF27 AF NFT

Arginine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibnu3c7qr2qqpugmafx4jfc3jxbo4wyycgbmc7x755piqohyweajm/metadata.json
IPFS of structure file: 
bafybeiboj566hr6sgmuktdjcct243t4z3c3t6pes4tczrm6dlytumi6jwm/AF-Q3JF27-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x133CEeEaaE94bD85f7dDfB92dd226C748EAE2Ac5
First NFT owner address (bech32): 
genesis1zv7wa64wjj7cta7alwfd6gnvwj82u2k9mz0ret
Current NFT ID #452880 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
452880
Accession (UniProt):
Q3JF27
Name::
Arginine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Nitrosococcus oceani (strain ATCC 19707 / BCRC 17464 / JCM 30415 / NCIMB 11848 / C-107)

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 Q3JF27 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q3JF27|SYR_NITOC Arginine--tRNA ligase OS=Nitrosococcus oceani (strain ATCC 19707 / BCRC 17464 / JCM 30415 / NCIMB 11848 / C-107) OX=323261 GN=argS PE=3 SV=1 MKEHLWNLIADALSSLQQEGILSSWNKDKIQVQRTRDKSHGDFASNISMVLAKEARQKPQKLADLIVARLPEHPWVKKVDIAGPGFINFTLALPAFQAVVSQVLEQKESFGRCRTGHGKTVHLEFVSANPTGPLHVGHGRGAAYGDALARLLTAVGYQVHREYYVNDAGRQMDILAVSVWLRYLELCGETLPFPSNGYQGEYVRNIARSLKAGEEDLPHHSATEILAGLPADAPTGDREKYLDALIQKIKNLLGKNSYQKVFEQALNTILAGIREDLAKFGVTYDAWFSERHLTEMGAIEIAIERLKAAGHLYQKAGAWWFYATNFGDEKDRVVIRENGQPTYFASDIAYHLSKLEQGYHKIIDIWGADHHGYIPRIKASLQALGADLQQLDIQLVQFAILYRGKEKIQMSTRSGEFVTLRELCQEVGKDAARFFYVMRGAEQHMDFDLELAKSQSNENPVYYVQYAHARICSVFRQLKTREFVWNSEQGREHLGKLNEAHEVTLLDRLSCYSEVVESAAIQSAPHLLAYYLLDLARDFHTYYNAHTFLVDIPELRDARLALIAATRQVIKNGLTLLGVSAPESM