P54269 AF NFT

Homeobox protein caupolican

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeianj6eubowtvp2o3gsrtcdsnah2v466gvfmw4kiu55gjlthst6i4u/metadata.json
IPFS of structure file: 
bafybeibfvmaewq4bchmdezbyc3rtl7bt6lhn2mdgfhwwu4lmcal4iovopa/AF-P54269-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x362a6d063b1B7E1B6EfD3A9A7CA3612e3FE037AA
First NFT owner address (bech32): 
genesis1xc4x6p3mrdlpkmha82d8egmp9cl7qda2uxz2xy
Current NFT ID #52218 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
52218
Accession (UniProt):
P54269
Name::
Homeobox protein caupolican
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 P54269 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P54269|CAUP_DROME Homeobox protein caupolican OS=Drosophila melanogaster OX=7227 GN=caup PE=2 SV=2 MAAYAQFGYAGYPTANQLTTANTDSQSGHGGGSPLSGTNEASLSPSGGSTATGLTAGPLSPGAVSQSSHHAGHKGLSTSPAEDVVGGDVPVGLSSAAQDLPSRGSCCENGRPIITDPVSGQTVCSCQYDPARLAIGGYSRMALPSGGVGVGVYGGPYPSNEQNPYPSIGVDNSAFYAPLSNPYGIKDTSPSTEMSAWTSASLQSTTGYYSYDPTLAAYGYGPNYDLAARRKNATRESTATLKAWLSEHKKNPYPTKGEKIMLAIITKMTLTQVSTWFANARRRLKKENKMTWEPKNKTEDDDDGMMSDDEKEKDAGDGGKLSTEAFDPGNQLIKSELGKAEKEVDSSGDQKLDLDREPHNLVAMRGLAPYATPPGAHPMHAAYSSYAQSHNTHTHPHPQQMQHHQQQQQQQQNQQQLQHHQMDQPYYHPGGYGQEESGEFAAQKNPLSRDCGIPVPASKPKIWSVADTAACKTPPPTAAYLGQNFYPPSSADQQLPHQPLQQHQQQQLQQLQQQQQHHHHPHHHHPHHSMELGSPLSMMSSYAGGSPYSRIPTAYTEAMGMHLPSSSSSSSSTGKLPPTHIHPAPQRVGFPEIQPDTPPQTPPTMKLNSSGGSSSSSGSSHSSSMHSVTPVTVASMVNILYSNTDSGYGHGHSHGHGHGHGHGLGHGHGLGHGHGHMGVTSNAYLTEGGRSGS