C3KBZ7 AF NFT

Methionine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiforrddn3ndfgssmu4in3vmarq33ewr6duzz34oaexd4nc7zurm5e/metadata.json
IPFS of structure file: 
bafybeigmzjbxge24hiihqsyj62aucny36xnkewl7rfncjpyrulerzf6tc4/AF-C3KBZ7-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x473a866D01BaacC5B3b6058eD2e8CFa195DE4d05
First NFT owner address (bech32): 
genesis1guagvmgph2kvtvakqk8d96x05x2aung9ramqyn
Current NFT ID #450904 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
450904
Accession (UniProt):
C3KBZ7
Name::
Methionine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
PSEUDOMONAS FLUORESCENS (STRAIN SBW25)

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 C3KBZ7 research and analysis (ICN3D with VR)

FASTA sequences

>sp|C3KBZ7|SYM_PSEFS Methionine--tRNA ligase OS=Pseudomonas fluorescens (strain SBW25) OX=216595 GN=metG PE=3 SV=1 MSEPRKILVTSALPYANGSIHLGHMLEYIQTDMWVRFQKHRGNQCIYVCADDAHGSAIMLRAEKEGITPEQLIANVQAEHSADFAEFLVDFDNFHSTHSDENRELSSQIYLRLKEAGHIATRSITQYFDPEKKMFLADRFIKGTCPKCGTEDQYGDNCEKCGATYAPTDLKNPKSAISGATPVLKDSQHFFFKLPDFQQMLQTWTRSGTLQDAVANKIAEWLDAGLQQWDISRDAPYFGFEIPGEPGKYFYVWLDAPIGYMASFKNLCDRTPELDFDAFWAKDSTAELYHFIGKDIVNFHALFWPAMLEGSGYRKPTGIAVHGYLTVNGQKMSKSRGTFIKARTYLDHLSPEYLRYYYASKLGRGVDDLDLNLEDFVQKVNSDLVGKVVNIASRCAGFIHKGNAGVLVAENAAPELTDAFLAAAPSIADAYEARDFARAMREIMGLADRANAWIADKAPWSLNKQEGKQAEVQAICATGVNLFRQLVIFLKPVLPLLAADAEAFLNVAPLTWNDHATLLSNHQLNEFKPLMTRIDPVKVQAMTDASKEDLVASQTDTGESAPAGNGELAKDPISAEIEFDAFAAVDLRVALIVKAEAVEGADKLLRLTLDLGGEQRNVFSGIKSAYPDPSKLDGRLTMMIANLKPRKMKFGISEGMVMAAGPGGEEIYLLSPDSGAKPGQRIK