Q9NAN2 AF NFT

Partitioning defective protein 6

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiaftamf6letu2szbuwrw54kczqpo5epnctl7xcc2vvzino6ak72bu/metadata.json
IPFS of structure file: 
bafybeicmk2kxatwmen6onf7fe5deypfg3dkrmnlfgqxzevqlegyi6axksi/AF-Q9NAN2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x768fbC4124BfF53721BeAa8519dEa78111cF6A4C
First NFT owner address (bech32): 
genesis1w68mcsfyhl6nwgd742z3nh48sygu76jvfkxdrp
Current NFT ID #288348 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
288348
Accession (UniProt):
Q9NAN2
Name::
Partitioning defective protein 6
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 Q9NAN2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9NAN2|PAR6_CAEEL Partitioning defective protein 6 OS=Caenorhabditis elegans OX=6239 GN=par-6 PE=1 SV=2 MSYNGSYHQNHHSTLQVKSKFDSEWRRFSIPMHSASGVSYDGFRSLVEKLHHLESVQFTLCYNSTGGDLLPITNDDNLRKSFESARPLLRLLIQRRGESWEEKYGYGTDSDKRWKGISSLMAQKPPKRSYSISNPEDFRQVSAIIDVDIVPEAHRRVRLCKHGQERPLGFYIRDGTSVRVTERGVVKVSGIFISRLVDGGLAESTGLLGVNDEVLEVNGIEVLGKTLDQVTDMMVANAHNLIITVKPANQRNTLSRGPSQQGTPNASEMSAATAAATGGIQRPMKMNGSSDGSYHPKQHDANDSDSGED