Q8PF09 AF NFT

Acetyl-coenzyme A synthetase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeif2aevb2uarzqx36fjyp7mclhx2l2xayer6v43iodh5nnx4rcfdou/metadata.json
IPFS of structure file: 
bafybeiawkklsiyauwilwgsmyef7yt2lrujil4xcm4nyeovchupmyrlwi3y/AF-Q8PF09-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7a1388B6Aad67B04634A32f63b8A6D6005eab86c
First NFT owner address (bech32): 
genesis10gfc3d426easgc62xtmrhzndvqz74wrv0qh3l8
Current NFT ID #8076 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
8076
Accession (UniProt):
Q8PF09
Name::
Acetyl-coenzyme A synthetase
Experimental Method:
Predicted structure
Sequence source:
XANTHOMONAS AXONOPODIS PV. CITRI (STRAIN 306)

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 Q8PF09 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q8PF09|ACSA_XANAC Acetyl-coenzyme A synthetase OS=Xanthomonas axonopodis pv. citri (strain 306) OX=190486 GN=acsA PE=3 SV=1 MADVYPVDPAFAADARVTREQYAALYRESIQHPEQFWGKAAQRLEWFKQPTQIKDVSYALDDFHIRWFGDGELNASVNCLDRQLATRGDKTALLFEPDSPDAASYPVTYRELYERVCKLGNALRNLGVKKGDRVTIYLPMIVDAAVAMLACARIGAVHSVVFGGFAANSIADRVIDCQSKLIITADEGLRGGKKIPLKANVDAALKIPGTNTVETVLVVRHTGGAVEMQAPRDRWFHDVVDGQPAACEPERMNAEDPLFILYTSGSTGKPKGVLHTTAGYLLFASYTHEVVFDLREDDIYWCTADVGWVTGHSYIVYGPLANGATAVMFEGVPNYPNVSRFWEVIDKHQVTIFYTAPTAIRALMRDGADPVKKTSRKSLRLLGSVGEPINPEAWRWYYEVVGDSRCPIVDTWWQTETGGILISPLAGAVDLKPGSATLPFFGVQPALVDAEGKILEGATEGNLVLLDSWPGQMRSVYGDHQRFIDTYFRTYPGSYFTGDGCRRDADGYYWITGRVDDVINVSGHRIGTAEVESALVSHPKVAEAAVVGFPHDVKGQGIYAYVTLIAGQTPSEDLHKELVSWVRKEIGPIASPDHLQWAPGLPKTRSGKIMRRILRKIAENAPDQLGDTSTLADPSVVDSLVNERLAR