Q1CE37 AF NFT

Acetyl-coenzyme A synthetase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifkmk6bqo5hr37pydljmlsap377todftxa3relgaxwpuprkykjbvi/metadata.json
IPFS of structure file: 
bafybeif5lcnlnhjfdmk2fhs5qywwg3ivhjudiz3yykupycfca724lrztpu/AF-Q1CE37-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x0439fF960F7A476d7DF12a352C5Bf831a73cDfEb
First NFT owner address (bech32): 
genesis1qsull9s00frk6l039g6jcklcxxnnehltv0j3rf
Current NFT ID #8087 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
8087
Accession (UniProt):
Q1CE37
Name::
Acetyl-coenzyme A synthetase
Experimental Method:
Predicted structure
Sequence source:
Yersinia pestis bv. Antiqua (strain Nepal516)

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 Q1CE37 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q1CE37|ACSA_YERPN Acetyl-coenzyme A synthetase OS=Yersinia pestis bv. Antiqua (strain Nepal516) OX=377628 GN=acs PE=3 SV=1 MSQIHKHPIPAAIAEHALITPEKYQHYYQQSVQNPDEFWGEQGKIIDWIKPYKTVKNTSFDPGHVSIRWFEDGTLNLAANCLDRHLAERGDQTAIIWEGDDPNQSKTVTYKQLHHDVCQFANVLKSLGVKKGDVVAIYMPMVPEAAVAMLACARIGAVHSVIFGGFSPDAVAGRIIDSHSKLVITADEGIRAGRAIPLKKNVDEALKNPAITSIKNVVVFQRTGNASYWEDGRDVWWHDLIKEASADCPPEEMNAEDPLFILYTSGSTGKPKGVVHTTGGYLVYAALTFKYVFDYHPGDIYWCTADVGWVTGHSYLLYGPLACGAITLMFEGVPNYPGVNRLSQVVDKHKVNILYTAPTAIRALMAEGDKAIEGTKRDSLRIMGSVGEPINPEAWEWYYNKIGNSKCPIVDTWWQTETGGFMITPLPGATELKAGSATRPFFGVQPALVDNLGNPQEGVAEGNLVITDSWPGQARTLFGDHERFEQTYFSTFKGMYFSGDGARRDEDGYYWITGRVDDVLNVSGHRLGTAEIESALVAHPKIAEAAVVGVPHNIKGQAIYAYITLNHGEEPTPELYTEVRNWVRKEIGPLATPDILHWTDSLPKTRSGKIMRRILRKIATGDTSNLGDTSTLADPSVVEKLLEEKQSMQTPS