Q9K3C5 AF NFT

B-type flagellar hook-associated protein 2

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifjd65ztjfw76j2wpbmoasbfkrc6xq325zyrya462uh3zvr44ohna/metadata.json
IPFS of structure file: 
bafybeigmsayl7no5c5r5a5zwj334yibuk2mdbhzagexri4ld37vin7vrwy/AF-Q9K3C5-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x836d97bfE95909D1F0f696DC2319364607dcbE8E
First NFT owner address (bech32): 
genesis1sdke00lftyyaru8kjmwzxxfkgcrae05wgtpsna
Current NFT ID #132058 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
132058
Accession (UniProt):
Q9K3C5
Name::
B-type flagellar hook-associated protein 2
Experimental Method:
Predicted structure
Sequence source:
PSEUDOMONAS AERUGINOSA (STRAIN ATCC 15692 / DSM 22644 / CIP 104116 / JCM 14847 / LMG 12228 / 1C / PRS 101 / PAO1)

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 Q9K3C5 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9K3C5|FLID2_PSEAE B-type flagellar hook-associated protein 2 OS=Pseudomonas aeruginosa (strain ATCC 15692 / DSM 22644 / CIP 104116 / JCM 14847 / LMG 12228 / 1C / PRS 101 / PAO1) OX=208964 GN=fliD PE=1 SV=1 MAGISIGVGSTDYTDLVNKMVNLEGAAKTNQLATLEKTTTTRLTALGQFKSAISAFQTALTALNSNAVFMARTAKSSNEDILKASATQSAVAGTYQIQVNSLATSSKIALQAIADPANAKFNSGTLNISVGDTKLPAITVDSSNNTLAGMRDAINQAGKEAGVSATIITDNSGSRLVLSSTKTGDGKDIKVEVSDDGSGGNTSLSQLAFDPATAPKLSDGAAAGYVTKAANGEITVDGLKRSIASNSVSDVIDGVSFDVKAVTEAGKPITLTVSRDDAGVKDNVKKFVEAYNTLTKFINEQTVVTKVGEDKNPVTGALLGDASVRALVNTMRSELIASNENGSVRNLAALGITTTKDGTLEIDEKKLDKAISADFEGVASYFTGDTGLAKRLGDKMKPYTDAQGILDQRTTTLQKTLSNVDTQKADLAKRLAALQEKLTTQFNLLSAMQDEMTKRQKSITDNLASLPYGSGKKT