Q3JJP7 AF NFT

ATP synthase subunit alpha 2

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihdugm23g3nydq74psqs7c3wqm4hobxulwiivdljfckejf4wx3bwe/metadata.json
IPFS of structure file: 
bafybeif37uqwlp6s4eaynbzh74xjkxt3u4vpwbmijsln6xvyipe7rpst6e/AF-Q3JJP7-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x33DDd87D6476a8e5277F2A859860A0611e9762aA
First NFT owner address (bech32): 
genesis1x0wasltyw65w2fml92zesc9qvy0fwc42ve0shj
Current NFT ID #32983 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
32983
Accession (UniProt):
Q3JJP7
Name::
ATP synthase subunit alpha 2
Experimental Method:
Predicted structure
Sequence source:
BURKHOLDERIA PSEUDOMALLEI (STRAIN 1710B)

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 Q3JJP7 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q3JJP7|ATPA2_BURP1 ATP synthase subunit alpha 2 OS=Burkholderia pseudomallei (strain 1710b) OX=320372 GN=atpA2 PE=3 SV=1 MTPTPDAPAAADAATGAGWLARRRGALARVALAPVAQAIGRVERVADGIAFVSGLEDTMLNEVLRFEGGVTGFAHTLDEDLISVVLLDPDAGVRAQTAVARTGAVLEVPAGPQLLGRVVDPLGRPLDGGAPLDAAHTLPIERAAPAIIERDLVSEPLDTGVLIVDALFTIGRGQRELIIGDRATGKTSLAIDAIVNQRHSDVICVYVAIGQRASAVRRVIDAVRRYGAPERCVFVVAPAACAPGLQWIAPFAGFSIAEYFRDRGQHALVVVDDLTKHAATHRELALLTREPPGREAYPGDIFYVHARLLERAAKLSAALGGGSLSALPIAETDAGNLAAYIPTNLISITDGQIVLDSALFAANQRPAVDVGLSVSRVGGKAQHPALRAASGRLRLDYAQFLELEAFTRFGGLTDARLRAQITRGERIRALITQPRFRALRTLDEVVLLKALAAGALDAMSPDLVAPLRERLPAWLDARIAALTPALAPPRDWLADDAALDALAESVGELIERIAADAARRATAGMPAEDAAGDIGGAFGGEQARGDADRDADHGANREVSREVSPEASREVSREVSCEVSHEADRDAAADAARVAGRAPGRAEPDRAAPRAMPDGPPRAQADGDRASASRPRPDARGDAARTAPSPQGGADANVDAEAEARHKR