A9VLF7 AF NFT

Putative membrane protein insertion efficiency factor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeieup4st4a43i5ti76rciw2fkgc2xlt4bxtcxfulddzwsvi7eurplu/metadata.json
IPFS of structure file: 
bafybeih7kk43ykmk77ujacefxzxsqqm3csx42i2mfqoujbqywxxrvu5ej4/AF-A9VLF7-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x436734896adb728ed1D6B04Bc625c53841648Fff
First NFT owner address (bech32): 
genesis1gdnnfzt2mdega5wkkp9uvfw98pqkfrllxxenmf
Current NFT ID #532195 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
532195
Accession (UniProt):
A9VLF7
Name::
Putative membrane protein insertion efficiency factor
Experimental Method:
Predicted structure
Sequence source:
Bacillus mycoides (strain KBAB4)

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 A9VLF7 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A9VLF7|YIDD_BACMK Putative membrane protein insertion efficiency factor OS=Bacillus mycoides (strain KBAB4) OX=315730 GN=BcerKBAB4_4627 PE=3 SV=1 MKQIFIGIIRFYQKFISPMTPPTCRFYPTCSHYGLEAFQKHGTFKGFWLTCKRILKCHPFHPGGFDPVPDKKDDKVNS