P45975 AF NFT

Histone-lysine N-methyltransferase Su(var)3-9

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihixk2cdrjl6ncijgqzhwfdpx4mcv756w7ebqasdgwotczbv4hbza/metadata.json
IPFS of structure file: 
bafybeihjz3f5obewh3edb52g5kaupvwdabx5s7jfwrwjt7myogwlmn5mw4/AF-P45975-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xCcE0f7d4E847A12eE8F3c53aeE79dC9c9B1cB849
First NFT owner address (bech32): 
genesis1ens0048gg7sja68nc5awu7wunjd3ewzf4avyrn
Current NFT ID #442371 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
442371
Accession (UniProt):
P45975
Name::
Histone-lysine N-methyltransferase Su(var)3-9
Experimental Method:
Predicted structure
Sequence source:
DROSOPHILA MELANOGASTER

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 P45975 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P45975|SUV39_DROME Histone-lysine N-methyltransferase Su(var)3-9 OS=Drosophila melanogaster OX=7227 GN=Su(var)3-9 PE=1 SV=2 MATAEAQIGVNRNLQKQDLSNLDVSKLTPLSPEVISRQATINIGTIGHVAHGKSTVVKAISGVQTVRFKNELERNITIKLERLSEKKIKNLLTSKQQRQQYEIKQRSMLRHLAELRRHSRFRRLCTKPASSSMPASTSSVDRRTTRRSTSQTSLSPSNSSGYGSVFGCEEHDVDKIPSLNGFAKLKRRRSSCVGAPTPNSKRSKNNMGVIAKRPPKGEYVVERIECVEMDQYQPVFFVKWLGYHDSENTWESLANVADCAEMEKFVERHQQLYETYIAKITTELEKQLEALPLMENITVAEVDAYEPLNLQIDLILLAQYRAAGSRSQREPQKIGERALKSMQIKRAQFVRRKQLADLALFEKRMNHVEKPSPPIRVENNIDLDTIDSNFMYIHDNIIGKDVPKPEAGIVGCKCTEDTEECTASTKCCARFAGELFAYERSTRRLRLRPGSAIYECNSRCSCDSSCSNRLVQHGRQVPLVLFKTANGSGWGVRAATALRKGEFVCEYIGEIITSDEANERGKAYDDNGRTYLFDLDYNTAQDSEYTIDAANYGNISHFINHSCDPNLAVFPCWIEHLNVALPHLVFFTLRPIKAGEELSFDYIRADNEDVPYENLSTAVRVECRCGRDNCRKVLF