Q62EB0 AF NFT

ATP synthase subunit alpha 2

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiexzewvhyyrkybjou4e3j4gxpd7s5o4u7inylh7liezqkkxi7wux4/metadata.json
IPFS of structure file: 
bafybeiceufglyhmzrhw4hrwtfigsdeylsek2f5zvhpgiwmpp6msxvv4keu/AF-Q62EB0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x9073C46348542FfE4327c3F363F9B51B22058e75
First NFT owner address (bech32): 
genesis1jpeugc6g2shluse8c0ek87d4rv3qtrn44vl0u5
Current NFT ID #32980 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
32980
Accession (UniProt):
Q62EB0
Name::
ATP synthase subunit alpha 2
Experimental Method:
Predicted structure
Sequence source:
BURKHOLDERIA MALLEI (STRAIN ATCC 23344)

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 Q62EB0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q62EB0|ATPA2_BURMA ATP synthase subunit alpha 2 OS=Burkholderia mallei (strain ATCC 23344) OX=243160 GN=atpA2 PE=3 SV=1 MTPTPDAPAAADAATGAGWLARRRGALARVALAPIAQAIGRVERVADGIAFVSGLEDTMLNEVLRFEGGVTGFAHTLDEDLISVVLLDPDAGVRAQTAVARTGAVLEVPAGPQLLGRVVDPLGRPLDGGAPLDAAHTLPIERAAPAIIERDLVSEPLDTGVLIVDALFTIGRGQRELIIGDRATGKTSLAIDAIVNQRHSDVICVYVAIGQRASAVRRVIDAVRRYGAPERCVFVVAPAACAPGLQWIAPFAGFSIAEYFRDRGQHALVVVDDLTKHAATHRELALLTREPPGREAYPGDIFYVHARLLERAAKLSAALGGGSLSALPIAETDAGNLAAYIPTNLISITDGQIVLDSALFAANQRPAVDVGLSVSRVGGKAQHPALRAASGRLRLDYAQFLELEAFTRFGGLTDARLRAQITRGERIRALITQPRFRALRTLDEVVLLKALAAGTLDAMSPDLVAPLRERLPAWLDARIAALTPALAPPRDWLADDAALDALAESVGELIERIAADAARRATAGMPAEDAAGDIGGAFGGEQARGDADRDADHGANREVSREVSPEASREVSREVSREVSHEADRDAAADAARVAGRAPGRAEPDRAVPRAMPDGPPRAQADGDRASASRPPPDARGDAARTAPSPQGGADANVNADANVDAEAEARHKR