Q1GN72 AF NFT

Putative membrane protein insertion efficiency factor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiehug7i5crcmt2csmbsqom2zqqubtplpdqnexmky3r5tgl2mx7q54/metadata.json
IPFS of structure file: 
bafybeia3vkh7ttla55vv3bft2z5bslo3p25ll56ric2hpt73edce3xtxji/AF-Q1GN72-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x6dc74119484C5151aCc3EF094b7BB769Ff40c87f
First NFT owner address (bech32): 
genesis1dhr5zx2gf3g4rtxrauy5k7ahd8l5pjrl4ysygh
Current NFT ID #532552 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
532552
Accession (UniProt):
Q1GN72
Name::
Putative membrane protein insertion efficiency factor
Experimental Method:
Predicted structure
Sequence source:
SPHINGOPYXIS ALASKENSIS (STRAIN DSM 13593 / LMG 18877 / RB2256)

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 Q1GN72 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q1GN72|YIDD_SPHAL Putative membrane protein insertion efficiency factor OS=Sphingopyxis alaskensis (strain DSM 13593 / LMG 18877 / RB2256) OX=317655 GN=Sala_0005 PE=3 SV=1 MIARLLILIARAWQLGPSRVLPPTCRYAPSCSEYAIVALRRHGAIKGGWIATKRLLRCHPWGGHGYDPVP