Q9ZJG9 AF NFT

Putative membrane protein insertion efficiency factor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeietu6yo5qwnshjy3j3zhsr4xatxxnoa5upqzqgxm6lx6sdtxxxskm/metadata.json
IPFS of structure file: 
bafybeiaejnmj3dqcwhnymfqla5rnxunee5h23ibitpjqy27ofecx5vi7v4/AF-Q9ZJG9-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7a1388B6Aad67B04634A32f63b8A6D6005eab86c
First NFT owner address (bech32): 
genesis10gfc3d426easgc62xtmrhzndvqz74wrv0qh3l8
Current NFT ID #532362 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
532362
Accession (UniProt):
Q9ZJG9
Name::
Putative membrane protein insertion efficiency factor
Experimental Method:
Predicted structure
Sequence source:
HELICOBACTER PYLORI (STRAIN J99 / ATCC 700824)

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 Q9ZJG9 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9ZJG9|YIDD_HELPJ Putative membrane protein insertion efficiency factor OS=Helicobacter pylori (strain J99 / ATCC 700824) OX=85963 GN=jhp_1342 PE=3 SV=1 MRNNKTPFLSAIFTASIRGYQRFFSAFTFSSCRFYPTCSNYALWLLCFESPLVAMGKIAIRILSCNPFCSGGIAYPTTRLKRPSLLQSHKDFNRNFKTITFWLVPTTKSRATYYIIKV