Q9CLQ3 AF NFT

Putative membrane protein insertion efficiency factor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibgp6kqgvplewnc56cryqovcmht3iietutfdidyufvqyjzgtx5mmi/metadata.json
IPFS of structure file: 
bafybeihvhtezevxfk5igvdyugxkzhmrymopkllidgrmhhu2j2jfel2de2u/AF-Q9CLQ3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x65Aa444c599a2FAFaA573437756707F24918A5Fe
First NFT owner address (bech32): 
genesis1vk4ygnzengh6l2jhxsmh2ec87fy33f07qm6yk5
Current NFT ID #532453 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
532453
Accession (UniProt):
Q9CLQ3
Name::
Putative membrane protein insertion efficiency factor
Experimental Method:
Predicted structure
Sequence source:
PASTEURELLA MULTOCIDA (STRAIN PM70)

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 Q9CLQ3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9CLQ3|YIDD_PASMU Putative membrane protein insertion efficiency factor OS=Pasteurella multocida (strain Pm70) OX=272843 GN=PM1164 PE=3 SV=1 MAKTHSLSSKILIGLIRVYQVVISPLIGPRCRFTPTCSCYGIEAVKTHGAIKGSWLTLKRILKCHPLNAGGYDPVPPKINNKKEKK