C0RF62 AF NFT

Acetyl-coenzyme A synthetase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiddiin6bi74p6se3ggh6nw6diy6cceaoc3p56qb6yupgduh7etuwi/metadata.json
IPFS of structure file: 
bafybeidx7gvywetpqa6ydkywd3j677mcdp63arw5hxc6ok6dmdusfpdzwu/AF-C0RF62-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x9188600a0FCa2914254C94299b1bd9721Bc4D500
First NFT owner address (bech32): 
genesis1jxyxqzs0eg53gf2vjs5ekx7ewgduf4gquehckf
Current NFT ID #7933 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
7933
Accession (UniProt):
C0RF62
Name::
Acetyl-coenzyme A synthetase
Experimental Method:
Predicted structure
Sequence source:
BRUCELLA MELITENSIS BIOTYPE 2 (STRAIN ATCC 23457)

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 C0RF62 research and analysis (ICN3D with VR)

FASTA sequences

>sp|C0RF62|ACSA_BRUMB Acetyl-coenzyme A synthetase OS=Brucella melitensis biotype 2 (strain ATCC 23457) OX=546272 GN=acsA PE=3 SV=1 MSEKLYPVLPEAKKNTLIDNETYLEWYEESVSDPDGFWAKHGRRIDWFKPFTKVKNTDFNGDVTIKWYEDGVTNVSYNCIDRHLKSRGDKVAIIWEGDNPYIDKKITYRELYENVCRMANVLKKHGVKKGDRVTIYLPMIPEAAYAMLACARIGAVHSVVFAGFSPEALAGRIVDCESTFVITADEGVRGGKPVALKENTDTAIDIAAKQYVMVNKVLVVRRTGGKVSWGRGRDLWYHQEVASVEPHCEPEPMNAEDPLFILYTSGSTGKPKGVLHTTGGYLVYASMTHQYVFDYHDGEIYWCTADVGWVTGHSYIVYGPLANGATTLMFEGVPNFPDQGRFWEVVDKHHVNIFYTAPTALRALMGAGDEFVTRSSRSTLRLLGSVGEPINPEAWEWYYNVVGDQKCPIVDTWWQTENGGILITPLPGATDLKPGSATRPFFGVKPVLVDNEGNVQECVADGNLCISDSWPGQMRTVYGDHKRFIETYFSTYKGMYFSGDGCRRDEDGYYWITGRVDDVLNISGHRLGTAEIESALVSHHSVSEAAVVGYPHPIKGQGIYCYVTLMTGADAQDPDELRKELVQHVRKEIGPIATPDKIQFAPGLPKTRSGKIMRRILRKIAEDEFGALGDTSTLADRGVVDDLIENRQNKK