Q3Z8K3 AF NFT

Formate--tetrahydrofolate ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeih4tavqysrgggd5zzp72m2gpot7yzbprbu3ubrjj3cb2fji3ubrmq/metadata.json
IPFS of structure file: 
bafybeie7kdlzwwhftjhmyoxscmgc2dfnorvqzqhfk4ijfpysltblwnznp4/AF-Q3Z8K3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xd10960F956646DE8b64d3598984c91C2d5Af3D7b
First NFT owner address (bech32): 
genesis16yykp72kv3k73djdxkvfsny3ct2670tm7h5hjv
Current NFT ID #136747 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
136747
Accession (UniProt):
Q3Z8K3
Name::
Formate--tetrahydrofolate ligase
Experimental Method:
Predicted structure
Sequence source:
Dehalococcoides mccartyi (strain ATCC BAA-2266 / KCTC 15142 / 195)

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 Q3Z8K3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q3Z8K3|FTHS_DEHM1 Formate--tetrahydrofolate ligase OS=Dehalococcoides mccartyi (strain ATCC BAA-2266 / KCTC 15142 / 195) OX=243164 GN=fhs1 PE=3 SV=1 MTINNRKSHLKDLDPGLMKDWEIAEKAEEFLKPSKMLAEELGLTEDEIIPHGKYVAKVDFAGVLTRLKDRPNGKYIDVTAITPTPLGEGKSTTTMGLVQGLGNLGKKVTGAIRQPSSGPTFNIKGSAAGGGRSQCLPLSPFTLGLTGDIDAVTNSHNLAMVALQARIQHEANNTDEFLSSRSLKRLDIDPARVELKWAIDFCAQSLREIIMGIGGKTDGYQMHSGFGISVSSEVMAILSVFTGLADLRERMSKIIVAYRQNGEPVTTADLEVDGAMTALLLRAVNPNLLQTIEGQPVFVHAGPFANIAIGQSSIVADRLALKLADYHVTESGFGADIGFEKFWNIKCRLSGLKPDCAVIVATVRALKMHGGGPKVTPGAPLDPAYTTPNAALVEKGCQNMLAHIQTVKTAGINPVVCINHFAADTAQEIDIIRRTAEQAGARVAVSYHWANGGEGAAELAEAVIDACNEPNDFHFLYPEDMPLRERIYTIARKVYGADGVSYTQTALEKLARLENTGNTQFMPSCMVKTHLSLSHDPALKGRPGGFTLPIRDILTYMGAGLVVPVAGDIKLMPGTSSDPNFRRIDIDTHTGKVKGLF