A9IYZ3 AF NFT

Acetyl-coenzyme A synthetase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibhqusiu3ke34spjgk2kvwzoblovgxjyc5jolgrnk2fh42s2vx5vq/metadata.json
IPFS of structure file: 
bafybeidh5lb5polo33yyopsnfbvh3lizb3od5pj46rmnr5sur7kp2dfiga/AF-A9IYZ3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x827Dcb147886372317f263288bc31c7eeFc7876c
First NFT owner address (bech32): 
genesis1sf7uk9rcscmjx9ljvv5ghscu0mhu0pmveqly78
Current NFT ID #7923 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
7923
Accession (UniProt):
A9IYZ3
Name::
Acetyl-coenzyme A synthetase
Experimental Method:
Predicted structure
Sequence source:
Bartonella tribocorum (strain CIP 105476 / IBS 506)

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 A9IYZ3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A9IYZ3|ACSA_BART1 Acetyl-coenzyme A synthetase OS=Bartonella tribocorum (strain CIP 105476 / IBS 506) OX=382640 GN=acsA PE=3 SV=1 MTEKIYPISEEIKKNTLLDEETYQKWYRESINDPESFWAKHGQCIEWFKPFTKVKNTSFNDGVSIQWYEDGITNVAYNCIDRHLKTHGDQIALIWEGDNPYHDKKITYNELYEHVCRFANLLKNHGVKKGDKVTIYLPMIPEAAYAMLACARIGAVHSVIFAGFSAEAIAGRIVDCESTFIITADHGLRGGKRINLKDNVDHAIEIAARQNVRVDQVMVIRRTCGPIDWIEGRDFWYHEEITHAKTNCPAEPMNAEDPLFILYTSGSTGKPKGVLHSTGGYLVYAAITHKYVFDYHPGEIYWCTADIGWITGHSYLVYGPLCNGATTLMFEGTPTFPDKGRFWEIVDKHKVNTLYTAPTAIRALMGAGNSFVEHSKRTSLRLLGTVGEPINPEAWEWFYHTVGNDRCPILDTWWQTETGGHMITPLPGATPLKAGSATRPFFGVQLQIIDEQGNILEGEAEGNLCIIDSWPGQMRTLYKDHERFIETYFSTYKGKYFTGDGCRRDSDGYYWITGRVDDILNVSGHRLGTAEIESALVLHPAVSEAAVVGYPHPIKGQGVYSFVTLMEGTAPSEELQKDLIKHVRKEIGSIAILDKIQFAPQLPKTRSGKIMRRILRKIAENNFDNLGDISTLAEPQVVEDLIANRQN