Q8G6P9 AF NFT

Probable serine/threonine-protein kinase PknB

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidzkfhvqk6uwimltna2gilg4ubhjx33zfi635cjhrmdecivqjuh2a/metadata.json
IPFS of structure file: 
bafybeia7csabi6wk3o6uumqklb6xzie3sijnxbs2nhqhsiokck6kvkupyi/AF-Q8G6P9-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x07c85d409125bF6733584D6f9a3330A838724e87
First NFT owner address (bech32): 
genesis1qly96sy3yklkwv6cf4he5ves4qu8yn58yp8kkr
Current NFT ID #300600 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
300600
Accession (UniProt):
Q8G6P9
Name::
Probable serine/threonine-protein kinase PknB
Experimental Method:
Predicted structure
Sequence source:
Bifidobacterium longum (strain NCC 2705)

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 Q8G6P9 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q8G6P9|PKNB_BIFLO Probable serine/threonine-protein kinase PknB OS=Bifidobacterium longum (strain NCC 2705) OX=206672 GN=pknB PE=3 SV=1 MSTSMPTALAGGRYQLGQLIGRGGMAEVHVALDTRLGRTVAVKIMRADLANDDIFLARFRREAHAVAQMNNPNIVNIYDSGEELVSSESGDAERLPYIVMEYVKGQTLRDIIKVNGALSQRDCEQVMLGVLNALDYSHRMGIIHRDIKPGNIMISEQGVVKVMDFGIARALDDSAATMTQSQGVVGTAQYLSPEQARGETVDMRSDLYSAGCVLYEMLTGRPPFTGDSAVAIAYQHVSEVATPPSAAVPGLPKMWDSICAKAMAKDRQNRYATASEFKTDILTYMNGGVPVAAAFNPLTDLSNMKARKEAERDLPTTPVEPHQQPTQAFNPVTGQFEQIPPANGANAAALQSRAQQRAAAAKAKKRKKIIIGSVIAAIVAVLVIVGIVFAMNGSGNKSSEDTVTIPEVCNASTSKDNIKLKLEASGLKMTEKQDTDSTEPEGTCTKMSPDAGSKVAKGSAVKVWFSAGPQSTQVPDVKERSQEEARSILESAGFKVNAAVKTEDSADIAKDMVTKTDPAAGQSVPKGTTITIYVSSGMTTVPSNLVGQSKDSVLQQYEGKFSFTVEQESSDTVEAGLITRVSPDSGSSIAQGGFITIWVSTGKEKVAVPNITAGTDYVTAELMLKAVGLKAQANGPTGSTAVVVSINPGAGSQVDAGSTVTITTKAGSTGGGTGTGDGGNGTGNGGGTGE