O23924 AF NFT

Phenylalanine ammonia-lyase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibfxpxjafnq2wi6fpmuo2wqiz6h63hjpfzy2wflfiup6bfktx4hf4/metadata.json
IPFS of structure file: 
bafybeiazumakyp4o52hfebfxidfhxsnwse3aywww7z75zpdo45jbba4qdm/AF-O23924-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x40d493EFAf4E1A5cEa89C0e7b040C1bCa1C66C81
First NFT owner address (bech32): 
genesis1gr2f8ma0fcd9e65fcrnmqsxphjsuvmypsp0jjf
Current NFT ID #286299 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
286299
Accession (UniProt):
O23924
Name::
Phenylalanine ammonia-lyase
Experimental Method:
Predicted structure
Sequence source:
DIGITALIS LANATA

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 O23924 research and analysis (ICN3D with VR)

FASTA sequences

>sp|O23924|PALY_DIGLA Phenylalanine ammonia-lyase OS=Digitalis lanata OX=49450 PE=2 SV=1 MAAVVENGHHGNNGFCVKQNDPLNWVAAAEELKGSHLDEVKRMVEEFRKTVVKLGGETLTISQVAAIAARDNEVAVQLAESSRAGVKASSDWVMESMNKGTDSYGVTTGFGATSHRRTKQGGALQKELIRFLNAGIFGNGTESTHTLPHSATRAAMLVRINTLLQGYSGIRFEILETITKFLNHNITPCLPLRGTITASGDLVPLSYIAGLLTGRPNSKAVGPNGESLNAEQAFKLAGANSGLFFELQPKEGLALVNGTAVGSGLASIALYEANILSLLAEVMSAVFAEVMNGKPEFTDHLTHKLKHHPGQIEAAAIMEHILDGSSYVKAAQKMHEMDPLQKPKQDRYALRTSPQWLGPQIEVIRTATKMIEREINSVNDNPLIDVSRNKALHGGNFQGTPIGVSMDNSRLAIASIGKLMFAQFSELVNDFYNNGLPSNLSGGRNPSLDYGFKGSEIAMASYCSELQFLANPVTNHVQSAEQHNQDVNSLGLISSRKTVEALDILKLMSSTYLVALCQAIDLRHLEENLRLSVKNTISQVAKRTLTTGVNGELHPSRFCELDLLRVVDREYVFAYVDDPCSATYPLMQKLRQVLVEHALKNGENEKNASTSIFQKIEAFEAELKAVLPKEVESARVALEDGKPAIANRITECRSYPLYKFIREELGTNFLTGEKVMSPGEECDRVFTAMSKGLIVDPLLKCLEGWNGAPLPIC