Q57MI5 AF NFT

Methionine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiggyere6mslm7nfve7nxaywz43ilhzjxyffszfinwet6rptdbu57y/metadata.json
IPFS of structure file: 
bafybeicoisb3jguxe3h4u3y3v5apsfqzr3ilz3t4fpndeo27udcgwn4vwa/AF-Q57MI5-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x02399DAD8BAfD11Be4a2f8CC40EC4A6C8116369F
First NFT owner address (bech32): 
genesis1qguemtvt4lg3he9zlrxypmz2djq3vd5l8q6lwd
Current NFT ID #450950 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
450950
Accession (UniProt):
Q57MI5
Name::
Methionine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Salmonella choleraesuis (strain SC-B67)

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 Q57MI5 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q57MI5|SYM_SALCH Methionine--tRNA ligase OS=Salmonella choleraesuis (strain SC-B67) OX=321314 GN=metG PE=3 SV=2 MTQVAKKILVTCALPYANGSIHLGHMLEHIQADVWVRYQRMRGHEVNFICADDAHGTPIMLKAQQLGITPEQMIGEMSQEHQTDFAGFNISYDNYHSTHSDENRELSELIYTRLKENGFIKNRTISQLYDPEKGMFLPDRFVKGTCPKCKSADQYGDNCEVCGATYSPTELIEPKSVVSGATPVMRDSEHFFFDLPSFSEMLQAWTRSGALQEQVANKMQEWFESGLQQWDISRDAPYFGFEIPNAPGKYFYVWLDAPIGYMGSFKNLCDKRGDTTSFDEYWKKDSDAELYHFIGKDIVYFHSLFWPAMLEGSHFRKPTNLFVHGYVTVNGAKMSKSRGTFIKASTWLKHFDADSLRYYYTAKLSSRIDDIDLNLEDFVQRVNADIVNKVVNLASRNAGFINKRFDGVLAAELADPQLYKTFTDAAAVIGEAWESREFGKAIREIMALADVANRYVDEQAPWVVAKQEGRDADLQAICSMGINLFRVLMTYLKPVLPTLSERVEAFLNSELNWDAIEQPLLSHKVNTFKALYNRIDMKQVEALVEASKEEVKAAAAPVTGPLADFPIQETITFDDFAKIDLRVALIENAEFVEGSDKLLRLTLDLGGEKRNVFSGIRSAYPDPQALIGRQTVMVANLAPRKMRFGVSEGMVMAAGPGGKDIFLLSPDDGAKPGQQVK