Q04475 AF NFT

Beta-2-microglobulin

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiaepmvhfgvmlr7opzykd4uzpmkcxy3elghq6i35o3xnatsg3f32gq/metadata.json
IPFS of structure file: 
bafybeiekqc4xwtfu3nyxsooihrei2natve4bl3ufrkg5cocijgs6boc6um/AF-Q04475-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xb02E74c86192B00dF2693793b13c66490cFD7e29
First NFT owner address (bech32): 
genesis1kqh8fjrpj2cqmunfx7fmz0rxfyx06l3ferggcp
Current NFT ID #40111 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
40111
Accession (UniProt):
Q04475
Name::
Beta-2-microglobulin
Experimental Method:
Predicted structure
Sequence source:
DANIO RERIO

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 Q04475 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q04475|B2MG_DANRE Beta-2-microglobulin OS=Danio rerio OX=7955 GN=b2m PE=1 SV=1 MRALITFALLCLLYITVQGKVSTPKVHVYSHFPGEYGKPNTLICYVSSFHPPDISIELLKNGQVMSDTKQTDLAFEKGWQFHLTKSVAFTPEKGDEYTCSVRHMKETKKFSWEPNM