A5VSF3 AF NFT

Acetyl-coenzyme A synthetase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifkscn7ilp35iupjo6qv6orxpppzkrvanf2czfznpzctjrdfeacj4/metadata.json
IPFS of structure file: 
bafybeihaoahuaguolmn6hqiopfvfoy5ffhcxprujh4v2i44epqdzxbopoq/AF-A5VSF3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x4BE1cF35Da14aE929555183fb31BD9CE38270CaE
First NFT owner address (bech32): 
genesis1f0su7dw6zjhf9924rqlmxx7eecuzwr9wnja000
Current NFT ID #7935 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
7935
Accession (UniProt):
A5VSF3
Name::
Acetyl-coenzyme A synthetase
Experimental Method:
Predicted structure
Sequence source:
BRUCELLA OVIS (STRAIN ATCC 25840 / 63/290 / NCTC 10512)

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 A5VSF3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A5VSF3|ACSA_BRUO2 Acetyl-coenzyme A synthetase OS=Brucella ovis (strain ATCC 25840 / 63/290 / NCTC 10512) OX=444178 GN=acsA PE=3 SV=1 MSEKLYPVLPEAKKNTLIDNETYLEWYEESVSDPDGFWAKHGRRIDWFKPFTKVKNTDFNGDVTIKWYEDGVTNVSYNCIDRHLKSRGDKVAIIWEGDNPYIDKKITYRELYENVCRMANVLKKHGVKKGDRVTIYLPMIPEAAYAMLACARIGAVHSVVFAGFSPEALAGRIVDCESTFVITADEGVRGGKPVALKENTDTAIDIAAKQYVMVNKVLVVRRTGGKVSWGRGRDLWYHQEVASVEPHCEPEPMNAEDPLFILYTSGSTGKPKGVLHTTGGYLVYASMTHQYVFDYHDGEIYWCTADVGWVTGHSYIVYGPLANGATTLMFEGVPNFPDQGRFWEVVDKHHVNIFYTAPTALRALMGAGDEFVTRSSRSTLRLLGSVGEPINPEAWEWYYNVVGDQKCPIVDTWWQTENGGILITPLPGATDLKPGSATRPFFGVKPVLVDNEGNVQEGVADGNLCISDSWPGQMRTVYGDHKRFIETYFSTYKGMYFSGDGCRRDEDGYYWITGRVDDVLNISGHRLGTAEIESALVSHHSVSEAAVVGYPHPIKGQGIYCYVTLMTGADAQDPDELRKELVQHVRKEIGPIATPDKIQFAPGLPKTRSGKIMRRILRKIAEDESGALGDTSTLADPGVVDDLIENRQNKK