P61475 AF NFT

Putative membrane protein insertion efficiency factor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeia7oflafizxyr2fdvay7rd4ac5sspnldzarjicd6jcspalai4mvny/metadata.json
IPFS of structure file: 
bafybeicut6jvywarcu4padx4yveqwnw2iaqcj4mr2pu2wxrstebfh6smii/AF-P61475-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x9823334B175F9f2683922fd5F25c4D9e96Fd15E9
First NFT owner address (bech32): 
genesis1nq3nxjcht70jdquj9l2lyhzdn6t0690f5rsn8h
Current NFT ID #532653 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
532653
Accession (UniProt):
P61475
Name::
Putative membrane protein insertion efficiency factor
Experimental Method:
Predicted structure
Sequence source:
YERSINIA PESTIS

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 P61475 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P61475|YIDD_YERPE Putative membrane protein insertion efficiency factor OS=Yersinia pestis OX=632 GN=YPO4101.1 PE=3 SV=1 MASPLSPGSRILIGLIRGYQLVISPLLGPRCRFHPTCSHYGIEALRRFGMIKGSWLTLKRVLKCHPLNSGGDDPVPPKLDDNREH