Q6M0E5 AF NFT

Methionine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihbcnnhmqvv2j2b6dx335dcz4xle5t22flyysmyg7wvvb3qima7te/metadata.json
IPFS of structure file: 
bafybeicidvgnm4vbxil7igvrzqlphicjmdnicj6ervev6p5eezfrqe3vfq/AF-Q6M0E5-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x5e58272ea25a05e06901A2eAe9f63939b344e0c6
First NFT owner address (bech32): 
genesis1tevzwt4ztgz7q6gp5t4wna3e8xe5fcxxnzlgjh
Current NFT ID #450847 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
450847
Accession (UniProt):
Q6M0E5
Name::
Methionine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
METHANOCOCCUS MARIPALUDIS (STRAIN S2 / LL)

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 Q6M0E5 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q6M0E5|SYM_METMP Methionine--tRNA ligase OS=Methanococcus maripaludis (strain S2 / LL) OX=267377 GN=metG PE=3 SV=1 MRHLVTTALAYTNGPLHLGHARSTYIPADIFTRYLKLKGEEVIHVGGTDNHGVPITLTAEKEGVKPIDIVDRYHNAIKADLDSLNICFDNFGRTHSDIHIETAQEFYSKLKENGYIYEKEIEQFYCEKCDMYLADRYVEGICPFCEGEARGDHCEVCGRHLEPTELVNPYCIHCNSKPEIKRTTHYFFKLSAMQDSLKEYIENSPEMPEHVKNMALRWIEELHDWDVSRNIKWGVPIPGCDDQVMYVWIEAPIGYVSFTKQLGDIWKSYWLENTDDSKISHFIGKDITVHHAVFWPGILKGIGGYKMPNAVVSGGYLTLENKKMSTSKNWVVWVKDFVENFSSDYLRYFFMINAPLNRDTDFSWDDFQKRINTELIDIIGNFTHRTLVFTERKFGSTPIVDLNQLKDEDKKLISKCDDTEKLVDSLIREYNFKDALMEIIHLAKEGNGYFQGMAPWAIKNEERLKEVMYTCSVVLKYIIYLLSSFMPEKTALLLEYMNEELDLKVRGNPLKKPKVIFTKVSDEDISRMKENLMKATKKAETKSDEKSKKVKSGEKMDIIDIDYFGNIDLRVGQILEVEEVPRSKKLYKIIADLGDEKRQIVSGLIGAYDAEELVGKKVIIICNLKPAKLCGVESQGMLLAAEDDSIVSLLSLDRDLPVGSKIH