A6LAR6 AF NFT

Formate--tetrahydrofolate ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeienuwpp7cyzslmkzo6zsj66uvo2csze6h7t4pqduy2givtntzscya/metadata.json
IPFS of structure file: 
bafybeiafjf64e4robtqskduad7que3q6hs6pzslqqk2dazgtyc7wjmwwc4/AF-A6LAR6-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x1c1083b2b9F8218b30361b06d1ca8579b816008C
First NFT owner address (bech32): 
genesis1rsgg8v4elqsckvpkrvrdrj590xupvqyvuhdjhh
Current NFT ID #136825 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
136825
Accession (UniProt):
A6LAR6
Name::
Formate--tetrahydrofolate ligase
Experimental Method:
Predicted structure
Sequence source:
PARABACTEROIDES DISTASONIS (STRAIN ATCC 8503 / DSM 20701 / CIP 104284 / JCM 5825 / NCTC 11152)

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 A6LAR6 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A6LAR6|FTHS_PARD8 Formate--tetrahydrofolate ligase OS=Parabacteroides distasonis (strain ATCC 8503 / DSM 20701 / CIP 104284 / JCM 5825 / NCTC 11152) OX=435591 GN=fhs PE=3 SV=1 MKSDIEIARETDLRKIKEVATTLGIPREEVQNYGRYIAKVPIHLIDKKQMDQHNLILVTAITPTKAGIGKTTVSIGLALGLNKIGKKAVVALREPSLGPCFGMKGGAAGGGYAQVLPMENINLHFTGDFHAVTSAHNMITALLDNYIYQTRNTCEGLKEIKWKRVLDVNDRSLRNIVSGLGGSANGVPTETGFDITPASEIMAILCLATDIEDLKRRVGNILLGYTNEDKPFTVNDLGIAGAITVLLKDALLPNLVQTTENTPAFVHGGPFANIAHGCNSISATQMALTYGDYVITEAGFGADLGAEKFFNIKCRKAGLSPKLTVIVATAQSLKLHGGVPEKEIKEPNIEGLKNGFANLDKHIENMKSFGQQVIVTFNRFATDTDEEIALVAEHCEEKGVGFAMNNVFAEGGEGGTELARLVVDTIENHPSAPLQYTYDLNDPIRTKVQKVAQKIYGASSIVYTTLADKKLRQIESLGISHYPICIAKTQYSFSSDPKAYGVAKDFELKVRDVIINNGAEMIVVVMGEIMRMPGLPKEPQARKIDIVDGMIEGLS