Q81G28 AF NFT

Probable multidrug resistance protein NorM

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiaoc7h7k3uwkeqotrxx5epu5r5enxdcinr6k66desgh4pjdcpg3cm/metadata.json
IPFS of structure file: 
bafybeideakt75lcjqekgtpm5p5bkuyonpa3dliyocavgw23rekhmyyebrm/AF-Q81G28-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x3F7c838ccc23133e72aA1c8841D2c157C4B4810a
First NFT owner address (bech32): 
genesis18a7g8rxvyvfnuu42rjyyr5kp2lztfqg2vyg6mc
Current NFT ID #267450 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
267450
Accession (UniProt):
Q81G28
Name::
Probable multidrug resistance protein NorM
Experimental Method:
Predicted structure
Sequence source:
Bacillus cereus (strain ATCC 14579 / DSM 31 / CCUG 7414 / JCM 2152 / NBRC 15305 / NCIMB 9373 / NCTC 2599 / NRRL B-3711)

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 Q81G28 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q81G28|NORM_BACCR Probable multidrug resistance protein NorM OS=Bacillus cereus (strain ATCC 14579 / DSM 31 / CCUG 7414 / JCM 2152 / NBRC 15305 / NCIMB 9373 / NCTC 2599 / NRRL B-3711) OX=226900 GN=norM PE=3 SV=1 MKETTSFSQKLKQFVLLFFPIFVTQMSLFAMSFFDTTMSGHASPTDLSGVAIGTSIWIPVSTGLTGILMATTPIVAQLVGSKKKEDVPHVVIQAVYLAICASFVVILIGFFVVSPILNGMRLEEPVERIAAQFLSIIAIGIIPLFTYTVLRGFIDALGKTRTTMIITLLSLPINVILNYLLIFGNFGFPKLGGVGAAIASTATYWCILIITVIIIQTKEPFASFNIFKQLYRPSLSSWIAFLKLGVPIGFAIFFETSIFAAVTLMMSNFSTTTIAAHQAAMNFASLLYMTPLSLAMAMTIAVGFEVGAKRYDNAKQYGLIGIGLALAFALLYSILLYFFDDQIASIYTTDAKVHHLAKEFLIFAILFQISDAIATPVQGALRGYKDVNVALIMTLIAYWIIGLPLGYILATYTEWAAKGYWIGLIIGLAFGAAFLLIRLFQVQRKYTTQNSR