Q8VC34 AF NFT

Putative RNA polymerase II subunit B1 CTD phosphatase Rpap2

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibbujwomaa2shzol6qo4vyr6g7se4oyqjvd7vgq5i6hfiqsgyxrme/metadata.json
IPFS of structure file: 
bafybeia2uclcdgdybj2gdzmmpyijpxkn4xoprjd7j437c3c2undbol6j3i/AF-Q8VC34-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x603786131b429eaC7e663e5851C902F5dCB72B70
First NFT owner address (bech32): 
genesis1vqmcvycmg202clnx8ev9rjgz7hwtw2msrd9yvr
Current NFT ID #384943 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
384943
Accession (UniProt):
Q8VC34
Name::
Putative RNA polymerase II subunit B1 CTD phosphatase Rpap2
Experimental Method:
Predicted structure
Sequence source:
MUS MUSCULUS

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 Q8VC34 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q8VC34|RPAP2_MOUSE Putative RNA polymerase II subunit B1 CTD phosphatase Rpap2 OS=Mus musculus OX=10090 GN=Rpap2 PE=2 SV=2 MADSAVPCSLGPSTRASSTHRDATGTKQTRALKRGDASKRQAELEAAIQRKVEFERKAVRIVEQLLEENITEEFLKECGMFITPAHYSDVVDERSIIKLCGYPLCQKKLGVIPKQKYRISTKTNKVYDITERKSFCSNFCYRASKFFETQIPKTPVWVREEERPPDFQLLKKGQSGSSGEVVQFFRDAVTAADVDGSGALEAQCDPASSSSWSERASDEEEQGFVSSLLPGNRPKAVDTRPQPHTKSSIMRKKAAQNVDSKEGEQTVSEVTEQLDNCRLDSQEKVATCKRPLKKESTQISSPGPLCDRFNTSAISEHKHGVSQVTLVGISKKSAEHFRSKFAKSNPGSGSASGLVHVRPEVAKANLLRVLSDTLTEWKTEETLKFLYGQNHDSVCLKPSSASEPDEELDEDDISCDPGSCGPALSQAQNTLDATLPFRGSDTAIKPLPSYESLKKETEMLNLRVREFYRGRCVLNEDTTKSQDSKESVLQRDPSFPLIDSSSQNQIRRRIVLEKLSKVLPGLLGPLQITMGDIYTELKNLIQTFRLSNRNIIHKPVEWTLIAVVLLLLLTPILGIQKHSPKNVVFTQFIATLLTELHLKFEDLEKLTMIFRTSC