Q9US28 AF NFT

Uncharacterized FAD-binding protein C1783.01

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiacvjlam4pl2uvy6oilunb22rhybjl5re3z266cfcnpldzj4ncrju/metadata.json
IPFS of structure file: 
bafybeiceidxhkavgetsmho3yx757qbut7ys5wnaxy45hd2mw5bfzhomzji/AF-Q9US28-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xBD7ffd264B77f87Ec7a7E1d74C067EAf75f1C4fB
First NFT owner address (bech32): 
genesis1h4ll6fjtwlu8a3a8u8t5cpn74a6lr38mplwqq7
Current NFT ID #533766 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
533766
Accession (UniProt):
Q9US28
Name::
Uncharacterized FAD-binding protein C1783.01
Experimental Method:
Predicted structure
Sequence source:
SCHIZOSACCHAROMYCES POMBE (STRAIN 972 / ATCC 24843)

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 Q9US28 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9US28|YKA1_SCHPO Uncharacterized FAD-binding protein C1783.01 OS=Schizosaccharomyces pombe (strain 972 / ATCC 24843) OX=284812 GN=SPAC1783.01 PE=3 SV=1 MISHVLVKDTSCLKVRTSYKCFVKYFPKCSVQSSFHSYDELAFSRRLYNLPRTLLNSRYYSNHSHGLVHGSKSPPSSQFLVPSFLQFNGQLKALCNNSAFQALPIKLSDLQKHWPSLKPHPLPPKRVSLGIPSISNPPVDTVISDSPTSPHPPSFVQPHPPYGIFAAPILDVRVLTNPGAVKRTYNLCLDISKYPLLEGKDWKIGGSFGIMPPNSDAEVLHLAHLLKIPQHELYVTKVLRTNGGRWPTIWGEDKPRCLYTSLYHIFKWCSDFISKPPTKSLIRLLAEHTLNPVEKSVLLALSDFRQDESYCRICTQSCVTLPDILEAFPSCHPPVDHLISALPQLMPRWYSISNDPSLANKRLEMAFTVQEYHSPNGQSRTGICTGFLEDLALAFLKARHDGSLANKKFTVPMFRGVQQNPFAKEFHNDGPMCLIGAGVGIAPFRGFVQRRLANAACTGKVWIIQGCRDQKLDELYHGEWNTVPGHHKNPKCRAKKLVVESRNGRREYVQDAVRRHGDVIWDVLSHKNGRIYLCGSGNSFVSEIEKALMDVAMKYGKLSKEEAQKELKNWQKPMNCKLIKEVW