A1KAG3 AF NFT

Methionine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifobmtioqxk3622vatapb7j2ne3c2v2jdrzwf6zr25gaflzl73zmq/metadata.json
IPFS of structure file: 
bafybeiev5hmr4dslyfnbkgtyqauj4d5pfbkt2gu67qzwfdnuyui3xnfsfy/AF-A1KAG3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x5659035936050aC2c0e7124CfC7caB9D45fEB205
First NFT owner address (bech32): 
genesis12evsxkfkq59v9s88zfx0cl9tn4zlavs92hmazf
Current NFT ID #450622 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
450622
Accession (UniProt):
A1KAG3
Name::
Methionine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Azoarcus sp. (strain BH72)

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 A1KAG3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A1KAG3|SYM_AZOSB Methionine--tRNA ligase OS=Azoarcus sp. (strain BH72) OX=418699 GN=metG PE=3 SV=1 MSRKILVTNALPYANGDIHLGHLVGYIQGDIWVRFQRMRGNSVHYVCADDTHGTPIMLRAEKEGITPEQLIDRVHGEHLRDFTDFGVGFDHYHSTHSAENRAYAEEIYGKLLGAGFIETRSIEQFYDPVKEMFLPDRFIKGECPKCGAGDQYGDNCEVCGAAYAPTELKNPYSAVSGAKPVLRTSEHYFFRLSDPRAVEFLRDWTRGTNAGGERRLQAEAANKMKEWLGEAGENKLSDWDISRDAPYFGFEIPGAPGKYFYVWLDAPIGYLASFRHYAERRGDIAVADYTDAARAESHGTELVHFIGKDILYFHALFWPAMLKFAGYRTPTQLCVNGFLTVDGAKMSKSRGTFITARSYIVQGLNPEWLRYYFASKSNGTMEDVDLNLDDMIAKVNSDLVGKYVNIASRCAGFIAKRFDGKLGASDPKATADFESAYESAQIAQAYDERDYGRALREIMRLADLANQYVNDHKPWELAKQDGQDAQLHVVCSTALTLFRDLTLYLKPVLPGLAAKVEAFLALPPLQWNDSWKPLPAGHAITAYQHLMTRVERKQIDALLEANRESLAPAAATAPAKDAKPAKEAGSQQRHAEKQQHAAGVSETASPHISIDDFTKVDLRIAKIVDAQHVEGADKLIRLQLDIGETDEAGNPKPRQVFAGIKSAYDPATLVGRLTVMVANLAPRKMKFGMSEGMVLAASDPDGKTGGLYILAPDEGAQAGMRVK