Q4L7D2 AF NFT

Putative membrane protein insertion efficiency factor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigfpk7l27ykmq43lnudf3h3hkiwd62ijooqsqkqmupavugrbmqpne/metadata.json
IPFS of structure file: 
bafybeig676cw434er7i2koecahk2ztoopjwhollhjdtfnwtfxadj3wn3rq/AF-Q4L7D2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x5094539FB3326c41CCb25b4b551912F9816d2CFb
First NFT owner address (bech32): 
genesis12z2988anxfkyrn9jtd942xgjlxqk6t8mz2pm67
Current NFT ID #532569 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
532569
Accession (UniProt):
Q4L7D2
Name::
Putative membrane protein insertion efficiency factor
Experimental Method:
Predicted structure
Sequence source:
STAPHYLOCOCCUS HAEMOLYTICUS (STRAIN JCSC1435)

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 Q4L7D2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q4L7D2|YIDD_STAHJ Putative membrane protein insertion efficiency factor OS=Staphylococcus haemolyticus (strain JCSC1435) OX=279808 GN=SH1134 PE=3 SV=1 MLKKLFLGIIHIYQRYISPMTPPTCRFYPTCSEYTREAIEVYGPFKGGYMGIRRILKCHPLHKGGFDPVPLKKDKHRH