Q3K7L0 AF NFT

Methionine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifjltontampt6evf5y75x6cer4cgpv7uq2cxl7palidiadk4odc2u/metadata.json
IPFS of structure file: 
bafybeibwzqiusnygf4vztf2ium5442c4ekoo262yanoycq3gmhi2x2vyvu/AF-Q3K7L0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xa73BAb1DabE4333A884D03393eAa10c3B4215494
First NFT owner address (bech32): 
genesis15ua6k8dtusen4zzdqvuna2sscw6zz4y5hahjw0
Current NFT ID #450907 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
450907
Accession (UniProt):
Q3K7L0
Name::
Methionine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
PSEUDOMONAS FLUORESCENS (STRAIN PF0-1)

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 Q3K7L0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q3K7L0|SYM_PSEPF Methionine--tRNA ligase OS=Pseudomonas fluorescens (strain Pf0-1) OX=205922 GN=metG PE=3 SV=1 MSEPRKILVTSALPYANGSIHLGHMLEYIQTDMWVRFQKHRGNQCIYVCADDAHGSAIMLRAEKEGITPEQLIANVQAEHSADFAEFLVDFDNFHSTHAEENRELSSQIYLKLRDAGHIAQRSITQYFDPEKKMFLADRFIKGTCPKCGTEDQYGDNCEKCGATYAPTDLKDPKSAISGATPVLKDSQHFFFKLPDFQEMLQAWTRSGTLQDAVANKIAEWLDAGLQQWDISRDAPYFGFEIPGEPGKYFYVWLDAPIGYMASFKNLCNRTPELDFDAFWGKDSTAELYHFIGKDIVNFHALFWPAMLEGAGFRKPTGINVHGYLTVNGQKMSKSRGTFIKARTYLDHLSPEYLRYYYAAKLGRGVDDLDLNLEDFVQKVNSDLVGKVVNIASRCAGFIQKGNAGLLVDTNAAPELTEAFLAAAPSIADAYEARDFARAMRETMALADRANAWIADKAPWSLNKQEGKQDEVQAVCATAINLFRQLVIFLKPVLPVLAADAEAFLNVAPLTWNDHTTLLANHQLNEFKPLMTRIDPVKVQAMTDASKEDLTASQTDTGAAAPAGNGELAKDPLSPEIDFDTFAAVDLRVALIVKAEHVEGADKLLRLTLDIGDEQRNVFSGIKSAYPDPSKLDGRLTMMIANLKPRKMKFGISEGMVMAAGPGGEEIYLLSPDSGAKPGQRIK