A4FN47 AF NFT

Arginine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidmzsglshsxi2dwk5n7ghkjohbabfe3esax6bsm7vton6qe4vjqc4/metadata.json
IPFS of structure file: 
bafybeigsfsz2bfpufdfo6psevfi5qjdxz7ff2sf6odaq5omuubgqwg7tqi/AF-A4FN47-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xf87a97E0A4bB354D834857B14296240B167cbe70
First NFT owner address (bech32): 
genesis1lpaf0c9yhv65mq6g27c5993ypvt8e0nsz8y8ua
Current NFT ID #452992 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
452992
Accession (UniProt):
A4FN47
Name::
Arginine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
SACCHAROPOLYSPORA ERYTHRAEA (STRAIN ATCC 11635 / DSM 40517 / JCM 4748 / NBRC 13426 / NCIMB 8594 / NRRL 2338)

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 A4FN47 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A4FN47|SYR_SACEN Arginine--tRNA ligase OS=Saccharopolyspora erythraea (strain ATCC 11635 / DSM 40517 / JCM 4748 / NBRC 13426 / NCIMB 8594 / NRRL 2338) OX=405948 GN=argS PE=3 SV=1 MTPAALAELLRNTAVDVLASRDLDTSVIPAAVTVERPRNPEHGDYATNIAMQVAKKAGVAPRDLAGWLAEALTGQDGIDSVEVAGPGFLNLRLAADAQGQILREVLDATDAYGRGAKYQGLKVNLEFVSANPTGPVHLGGTRWAAVGDALGRTLEAQGAEVTREYYFNDAGAQIDRFVRSLIAAARGEAAPEDGYGGAYIGEIANQVLEAEPTALDLPEAERHETFRRIGVGLMFDEVKRSLHDFGVDFDVYFHEDSLHTSGAVEKSVEQLKESGHLYFADGAWWLRSTEFGDDKDRVLIKSDGTTAYIAGDVAYLRDKRNRGFDLCIYMLGADHHGYIPRLKAAAAAFDDDPDAVEVLIGQMVNLVKDGKPVRMSKRAGTVLRLEDLVDAVGVDAARYSLIRSSVDSALDIDLDLISKRSNENPVFYVQYAHARLSSLQRNAASLGIDRGSVADADLSLLTHEREGDLIRTLGEYPRVVRSAAELREPHRIARYLEDLASAYHKFYDACRVLQPGDDQATPLTIARLQLCEAARQVLANGLGLLGVSAPEQM