Q54NA3 AF NFT

Autophagy-related protein 9

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiccqwpntzpgc45n3n34eofumdtgbc7isj47nglgbpmi2zaqek4ije/metadata.json
IPFS of structure file: 
bafybeictz63vdi5ssm6z2yk6s33bjoqpubcsw5lkzuscyasbfbizgm2a5e/AF-Q54NA3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7012c0b45c68a2c067644b9d3e5DDa06892c6957
First NFT owner address (bech32): 
genesis1wqfvpdzudz3vqemyfwwnuhw6q6yjc62hg2ks0z
Current NFT ID #31579 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
31579
Accession (UniProt):
Q54NA3
Name::
Autophagy-related protein 9
Experimental Method:
Predicted structure
Sequence source:
DICTYOSTELIUM DISCOIDEUM

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 Q54NA3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q54NA3|ATG9_DICDI Autophagy-related protein 9 OS=Dictyostelium discoideum OX=44689 GN=atg9 PE=2 SV=1 MSHEDRGGDYYPMMDDPEDRNFIQAKYPNSTGHMSSGGGSNHMSFDDNHGIEMLRDDEHSLLHESPVSIPAIHNLDSFLTDVYNYFRGKGFMCIFFNDLFELVSSLFVVLFFTFLVCFVDYSKLFSEQMPPPALRESVNFSAPIPIWLMVFLVIFSLYWLSKLFSFFSSIKTNWEISSFYKNTLKINEDDIQTIEWREVVSKIVLVPRLCIVKENMNALDIANRIMRKENYIIGLINQRILNLSIPFPFLRNLTFITKTLEWSLMYSLFNYIFDENGIIKSEFQDPTQRKRLSRGLSRRFMTIGILGLFTTPFIFFFLLINFFFEYAEELKNRPGSLFSREWSPLARWEFRELNELPHYFQNRLNLSYSHANQYVESFPSQMLSTIAKFISFLFGSVLAVFIVLGIVSDHFIMNYQIFDRTPIWYIGILGTIVAITRSLIVDENQVFQPAKHMARTVQNTHYLPMSWVGKTHTHKVRDEFLVLFEYRIVDFVRDIFSVLFTPFILIFSLPKSSQAIIDFFGNNTVVLEGVGPICQLGDFSNIRKLGDNSFGSLNHSQNKISLTNNAKLEKSIINFKCLNPEWNTDNNELLQNLNEFSKIKNNNNNNNNNGSNNHIGNHSQLPTTSVDDFQFIHDSHYIPHEIIDAVLGTHHHSQQSNNNAPRFKTGRVDQNILNAVNDLHQSFYESQYKHKNDNFVNSI