Q92QB2 AF NFT

Putative membrane protein insertion efficiency factor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeih3klrmw2czy57xdw2taulf5cywz5vwpvbu3nu3cgjwja7aluvmnu/metadata.json
IPFS of structure file: 
bafybeido6vy7fgm23guywi6juf2bvdnqumh2ja4oboce4k65ywhyvevwxe/AF-Q92QB2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x8e0F1Df221a58B7fE4C88E1480570C897b8f9D7b
First NFT owner address (bech32): 
genesis13c83mu3p5k9hlexg3c2gq4cv39acl8tm8aezc5
Current NFT ID #532491 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
532491
Accession (UniProt):
Q92QB2
Name::
Putative membrane protein insertion efficiency factor
Experimental Method:
Predicted structure
Sequence source:
RHIZOBIUM MELILOTI (STRAIN 1021)

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 Q92QB2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q92QB2|YIDD_RHIME Putative membrane protein insertion efficiency factor OS=Rhizobium meliloti (strain 1021) OX=266834 GN=R01422 PE=3 SV=1 MCPQPHADHAITRGDTGAAGGRNWSGPFRKTPGRLVGMTLIRAYQLTLSSFIGNSCRHLPTCSEYGFEAIARYGLWAGGWLTLFRVVRCGPGGTHGFDPVPDSLAPRQRWYTPWRYWQPRRKDA