Q9PRF8 AF NFT

Beta-2-microglobulin

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeief3obdr4agksqawubrovvnpfb62cdvncf3nf262wmxdttsbmvuyi/metadata.json
IPFS of structure file: 
bafybeiaqhn47onn3nnweoht72rd2dvtyjbmymtnlfxt4wt2zu66wb7c5mu/AF-Q9PRF8-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x80D2ac0F5e3268bC5C1d28BBAA07E3169BB02b79
First NFT owner address (bech32): 
genesis1srf2cr67xf5tchqa9za65plrz6dmq2me66p797
Current NFT ID #40085 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
40085
Accession (UniProt):
Q9PRF8
Name::
Beta-2-microglobulin
Experimental Method:
Predicted structure
Sequence source:
Acipenser baerii

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 Q9PRF8 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9PRF8|B2MG_ACIBE Beta-2-microglobulin OS=Acipenser baerii OX=27689 GN=b2m PE=2 SV=1 MFLRSTFVAALVACLAYIHLGDATEAMPKVQIYSRNVGELGKPNTLICHVSGFHPPNIKLQLLKNDVEIEGAQQSDLAFHQGWHFHLTKSVAFTPKEGEHYSCKVEHSTLREATRFTWTPDM