Q54LR6 AF NFT

Probable serine/threonine-protein kinase DDB_G0286481

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeie5yc7ohnav7s2bk4f47gbpzmzzdly4jjzrlczfpws7o5vzq3z6om/metadata.json
IPFS of structure file: 
bafybeigthbk3rtikqrfj7evuy3bvn2c2hb3sqco7gccmcisfkkklisduw4/AF-Q54LR6-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x05d2f765e98105817e4C261742F64227ab4eA5Ae
First NFT owner address (bech32): 
genesis1qhf0we0fsyzczljvyct59ajzy745afdw6rlknq
Current NFT ID #520509 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
520509
Accession (UniProt):
Q54LR6
Name::
Probable serine/threonine-protein kinase DDB_G0286481
Experimental Method:
Predicted structure
Sequence source:
DICTYOSTELIUM DISCOIDEUM

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 Q54LR6 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q54LR6|Y6481_DICDI Probable serine/threonine-protein kinase DDB_G0286481 OS=Dictyostelium discoideum OX=44689 GN=DDB_G0286481 PE=3 SV=1 MGKYYQIFFLLYLLCILYVISCGYINPYSPYSSPCLFAPIIGYLYMGGSLSSNSSNNNNNNNNNNNNNNNNNNNNNNNNNNKDSKLTENCNNNSSNNNSDNKSNIKNKQHHHHSNFRNRRGKSNNKNSSDNDDCTKCNKRHHTQSSSYDTSELHQSVSSGLGGSMGSGSQALTDIEKDINEFMNANPSHSLNKQQIQQQQQLQQQQQQLLKQQQQQQQQQQQQQQQQQQQQLEKQRKEQEETEKKKQLELQQQQQLQQQQQNGNGLIIEEDMMEGRILRNISKVYRDVNENQPKSYYDYEGYRINWKNVDRYEVIQKIGRGKYSEVFSGIDIETSDEVVIKVLKPVQKLKIQREIKILESLNGGPNIIPLLDSVKDQSSKVCSLVFPFVNKTDIRELVYTLDDYDIRYYIFELLKAIDYTHSKGIIHRDIKPLNIAIDHSKRKLSLIDWGLAEYYHPGKNYNVRVASRHYKPPELLVNMFDYDYSLDMWSLGCLFAGLILDRDPFFNGDNNNDQLLKIVKVLGTDDLFNFLDKFGLSLTDEQSSLIKPRQKSNWERFIPYENDDIAQPDAIDFLDKLLRYDPTERLTAKEAMKHPYFKDFNQSIL