P0C8F0 AF NFT

Catalase-peroxidase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiapmjpxiq765m53xnhpgct5slagoddkqxhgvxaku6l5777x3tlqy4/metadata.json
IPFS of structure file: 
bafybeichmgmxhjk343pxn35w4sb7f4s2a4op2wfremojrdeyjrmanu5jzi/AF-P0C8F0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xBEb7EaCd930759b1c8b58cDFfac29530C219e051
First NFT owner address (bech32): 
genesis1h6m74nvnqavmrj943n0l4s54xrppncz3jyg3r3
Current NFT ID #198530 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
198530
Accession (UniProt):
P0C8F0
Name::
Catalase-peroxidase
Experimental Method:
Predicted structure
Sequence source:
ESCHERICHIA COLI

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 P0C8F0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P0C8F0|KATG_ECOLX Catalase-peroxidase OS=Escherichia coli OX=562 GN=katG PE=3 SV=1 MIKKTLPVLILLALSGSFSTAVAADKKETQNFYYPETLDLTPLRLHSPESNPWGADFDYATRFQQLDMEALKKDIKDLLTTSQDWWPADYGHYGPFFIRMAWHGAGTYRTYDGRGGASGGQQRFEPLNSWPDNVNLDKARRLLWPVKKKYGSSISWGDLMVLTGNVALESMGFKTLGFAGGREDDWESDLVYWGPDNKPLADNRDKNGKLQKPLAATQMGLIYVNPEGPGGKPDPLASAKDIREAFSRMAMDDEETVALIAGGHTFGKAHGAASPEKCIGAGPDGAPVEEQGLGWKNKCGTGNGKYTITSGLEGAWSTSPTQFTMQYLKNLYKYEWELHKSPAGAYQWKPKKAANIVQDAHDPSVLHPLMMFTTDIALKVDPEYKKITTRFLNDPKAFEQAFARAWFKLTHRDMGPAARYLGNEVPAESFIWQDPLPAADYTMIDGKDIKSLKEQVMDLGIPASELIKTAWASASTFRVTDYRGGNNGARIRLQPEINWEVNEPEKLKKVLASLTSLQREFNKKQSDGKKVSLADLIVLSGNAAIEDAARKAGVELEIPFTPGRTDASQEQTDVASFSVLEPTADGFRNYYSKSRSHISPVESLIDKASQLDLTVPEMTALLGGLRVMDINTNNSSLGVFTDTPGVLDNKFFVNLLDMSTRWSKADKEDTYNGFDRKTGALKWKASSVDLIFSSNPELRAVAEVYASDDARNKFIHDFVKSWNKVMNSDRFDLNNK