C1D6H9 AF NFT

Putative membrane protein insertion efficiency factor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigpy6lagxm5h5fmmzhplfxgpnh6jbcomebzcccrubruyrn2xt46pe/metadata.json
IPFS of structure file: 
bafybeiextb4tfnqwrwphjb2dqm2fq44w64zw2kegdqvpcxxkioelbo4vbu/AF-C1D6H9-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x31C2b8Dda9af930b8C9df8eCc4E387b89CF5fc9A
First NFT owner address (bech32): 
genesis1x8pt3hdf47fshryalrkvfcu8hzw0tly6zdtfjr
Current NFT ID #532386 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
532386
Accession (UniProt):
C1D6H9
Name::
Putative membrane protein insertion efficiency factor
Experimental Method:
Predicted structure
Sequence source:
Laribacter hongkongensis (strain HLHK9)

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 C1D6H9 research and analysis (ICN3D with VR)

FASTA sequences

>sp|C1D6H9|YIDD_LARHH Putative membrane protein insertion efficiency factor OS=Laribacter hongkongensis (strain HLHK9) OX=557598 GN=LHK_03237 PE=3 SV=1 MSRIVLALIRFYQLAISPWLPPRCRYQPTCSQYAIEAVQKHGALKGGWLALRRIGRCHPWGSSGYDPVP