C3MAS0 AF NFT

Acetyl-coenzyme A synthetase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiczdd6winb2ucfk7bat2y7qw6hva7rl4eho65vethb3kl5mdunq6e/metadata.json
IPFS of structure file: 
bafybeibviruegjayvbu7emum3utxtlfvjuwalkqyer2u3m7twcylaz7tmq/AF-C3MAS0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x80D2ac0F5e3268bC5C1d28BBAA07E3169BB02b79
First NFT owner address (bech32): 
genesis1srf2cr67xf5tchqa9za65plrz6dmq2me66p797
Current NFT ID #8059 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
8059
Accession (UniProt):
C3MAS0
Name::
Acetyl-coenzyme A synthetase
Experimental Method:
Predicted structure
Sequence source:
Sinorhizobium fredii (strain NBRC 101917 / NGR234)

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 C3MAS0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|C3MAS0|ACSA_SINFN Acetyl-coenzyme A synthetase OS=Sinorhizobium fredii (strain NBRC 101917 / NGR234) OX=394 GN=acsA PE=3 SV=1 MDVKTYPVLEAAKNRTLVDNATYLKWYEESVADPEKFWGEHGKRIEWFEPYTTVKNTSFDGNVSIKWFEDGLTNVSYNCIDRHLKTHGEKTAIIWEGDNPYIDKRITYNELYDKVCRLANVLKKHGVEKGDRVTIYMPMVPEAAYAMLACARIGAIHSVVFGGFSPEALAGRIVDCESTFVITCDEGLRGGKPVPLKENTEKAIDIAARQHVMVNKVLVVRRTGGKVPWAPGRDVWYHQEIATVEPHCPPEKMRAEDPLFILYTSGSTGKPKGVLHTTGGYLVYASMTHQYVFDYHDGDIYWCTADVGWVTGHSYIVYGPLANAATTLMFEGVPNFPDAGRFWEVIDKHKVNIFYTAPTAIRSLMGAGDDFVNRSSRSSLRLLGTVGEPINPEAWEWYYHVVGAERSPIVDTWWQTETGGILITPLPGATDLKPGSATRPFFGVKPQIVDNEGNVIDGPADGNLCITDSWPGQMRTVYGDHERFIQTYFSTYKGKYFTGDGCRRDEDGYYWITGRVDDVLNVSGHRLGTAEVESALVSHHLVSEAAVVGYPHPIKGQGIYCYVSLMAGEVGSDELRQELVKHVRSEIGPIATPDKIQFAPGLPKTRSGKIMRRILRKIAEDDFGSLGDTSTLADPAVVDDLIANRQNRG