Q09543 AF NFT

Probable serine/threonine-protein phosphatase PP2A regulatory subunit

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifmcfxiznwsbqianpfsmqq7xzcrdtykdijxelz2w35cczy7chw2gi/metadata.json
IPFS of structure file: 
bafybeia46ti5rrexijtjy6o4gohye6ewcixjlhjnluqktz3lotcp3ahspm/AF-Q09543-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x41C049aD5427907F76fA6Cdd2DB97E59526d6E41
First NFT owner address (bech32): 
genesis1g8qynt25y7g87ah6dnwjmwt7t9fx6mjpcyz7yn
Current NFT ID #366 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
366
Accession (UniProt):
Q09543
Name::
Probable serine/threonine-protein phosphatase PP2A regulatory subunit
Experimental Method:
Predicted structure
Sequence source:
CAENORHABDITIS ELEGANS

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 Q09543 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q09543|2AAA_CAEEL Probable serine/threonine-protein phosphatase PP2A regulatory subunit OS=Caenorhabditis elegans OX=6239 GN=paa-1 PE=1 SV=2 MSVVEEATDDALYPIAVLIDELRNEDVTLRLNSIRKLSTIALALGVERTRNELIQFLTDTIYDEDEVLLVLAEQLGNFTPLVGGPDHVHCLLLPLENLATVEETVVRDKAVESLRKIADKHSSASLEEHFVPMLRRLATGDWFTSRTSACGLFSVVYPRVSPAIKSELKSMFRTLCRDDTPMVRRAAAAKLGEFAKVFEKTAVIEGLHSSLTDLHVDEQDSVRLLTVESAIAFGTLLDKANKKKLIEPILIELFDDKSWRVRYMVAEKLIEIQNVLGEDMDTTHLVNMYTNLLKDPEGEVRCAATQRLQEFALNLPEDKRQNIICNSLLNVAKELVTDGNQLVKSELAGVIMGLAPLIGKEQTVSELLPIYMQLLNDQTPEVRLNIISSLDKVNEVIGAAQLSTSLLPAIVGLAEDGKWRVRLAIVQFMPLLASQLGQEFFDEKLLPLCLNWLTDHVFSIREASTLIMKELTQKFGGQWASTNIVPKMQKLQKDTNYLQRMTCLFCLNTLSEAMTQEQILKEIMPIVKDLVEDDVPNVRFNAAKSLKRIGKNLTPSTLTSEVKPLLEKLGKDSDFDVRYFSEEAKNSLGL