Q0A4U4 AF NFT

ATP-dependent lipid A-core flippase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidp6c5iuldwsllujgkq3j4s2hnjqrt2a57sce2lxicjhs4ijt3pky/metadata.json
IPFS of structure file: 
bafybeidewzswzbzyyod6fkmubsl47qx3mpw666dqfqeedvzhbjenu7enhq/AF-Q0A4U4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x18b6aa73f166Dd46ca6E15d135DF8033C4C01318
First NFT owner address (bech32): 
genesis1rzm25ul3vmw5djnwzhgnthuqx0zvqyccy20q40
Current NFT ID #244422 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
244422
Accession (UniProt):
Q0A4U4
Name::
ATP-dependent lipid A-core flippase
Experimental Method:
Predicted structure
Sequence source:
Alkalilimnicola ehrlichii (strain ATCC BAA-1101 / DSM 17681 / MLHE-1)

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 Q0A4U4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q0A4U4|MSBA_ALKEH ATP-dependent lipid A-core flippase OS=Alkalilimnicola ehrlichii (strain ATCC BAA-1101 / DSM 17681 / MLHE-1) OX=187272 GN=msbA PE=3 SV=1 MSKGHSDHPSAGESWHLYKRIFGFIKPYWRLGVLAIVCMVLAAAGQAAFAWIIQPLVDGTFIEQDPGARLWVPATLVGIFLFHGVTTFASDYTVAWVGRRVVKDVRQAVFEQYLRLPTSYFDKNSPGTLLAKLTYNVNQISAAASKAVVVLVRDTFTVIFLLAYMTYLSGWLVMIVFGLGPLVAVVVTAANKRFRKLSRRMQASVGEYAQIAEDGIRGQAEVKIFGGQRYEAERFDRTNTRHHRQLMRYKAVQAASQPLAQLGAVIALAIILYLATMDVILETISPGGMISFIAAMLLMLPPLKRVIGVNAEIQKALAAGESVFEVLDAPPEPDHGQRPLERARGLIEFDRVAFRYPESEDWVLRDINLSIQPGETVALVGRSGSGKTTLASLLPRFYDPQRGEIRLDGHPLAEYRLQALRSQMSLVNQQVVLFNDSLANNIAYGLSERPTAAQLQAAARAANALEFIEELPEGFDTVIGENGVMLSGGQRQRIAIARALLKDAPILILDEATSALDSESEKRIQEALEKLMRGRTTLVIAHRLSTIEDADRIVVLDAGRVVETGTHRELLDHNGHYASLHRVQFNGPS