Q9K6W0 AF NFT

Flagellar hook-associated protein 2

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigzjcltpu3up2j4n6vfzqsbjg6lrwwroyc7jbdqjqkr7rxq5zsire/metadata.json
IPFS of structure file: 
bafybeibtjmltqgdje5ktg725yvuf6oko2uv6ftjfps4syl3klhnq4tyv6i/AF-Q9K6W0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x29EAdEfF44bDA42f96B33481D606dd403a9e4547
First NFT owner address (bech32): 
genesis1984dal6yhkjzl94nxjqavpkagqafu328nrfzya
Current NFT ID #132062 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
132062
Accession (UniProt):
Q9K6W0
Name::
Flagellar hook-associated protein 2
Experimental Method:
Predicted structure
Sequence source:
Alkalihalobacillus halodurans (strain ATCC BAA-125 / DSM 18197 / FERM 7344 / JCM 9153 / C-125)

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 Q9K6W0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9K6W0|FLID_ALKHC Flagellar hook-associated protein 2 OS=Alkalihalobacillus halodurans (strain ATCC BAA-125 / DSM 18197 / FERM 7344 / JCM 9153 / C-125) OX=272558 GN=fliD PE=3 SV=1 MRIGGIASGIDTESMIKQLMQVERIPLNKFTQRKITLEWQRDAYREVNLLLKKLDDAAANIRLRSSLNTKEASTTSKAFTAQPNAQVRNGSYQLKVNQIATQSRNISSEAISNGSTKISTTRALNEQNVYADGLNIEDYHGQTFTITTYNSSGAAVEKSFTIDTSKSLDSLFKDINSAGLGVRMSYNSTYDKVIIERTETGAFNAADGSNDYQIVFGGDTGFLNDVLKLNQANEVSGTNAEVEFIDPIMSSEPIVVSDSRTNRVTVGGITFSLTGTTEGFETLNVSSNTDAAFEKVMEFVDTYNATITELRSLLSEPRYRDYPPLTEEQRRELSEREAELWDEKAKSGLLRNDSMLNSLLAQMRADLYAPVQTNGQFSSITQIGITTSSDYRLGGFLEVDEDKLRAALEADPDSVHQLLNGTANSSLTSIPVKDRTSQQRSEIYSQTGLVGRIRSSLSSTMNDIVARAGNERRTEQQFTIGRQILDVDKRIDHFQQRLIQIENRYWAQFSRMEQMMNQANAQYASLQQFFVT