Q03353 AF NFT

Period circadian protein (Fragments)

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidtm5cvqxjnra7rdipipp76fmmgagkmphyzbpqyygneslvvpexxgu/metadata.json
IPFS of structure file: 
bafybeidny7gdd72au63okplsd4ea3mmsa4hbknp5eh5b6s35nwgif6jdle/AF-Q03353-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xa8A1c7BA6D7bAf815aeb7e38575A232686180e38
First NFT owner address (bech32): 
genesis14zsu0wnd0whczkht0cu9wk3ry6rpsr3c9ug7sa
Current NFT ID #294207 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
294207
Accession (UniProt):
Q03353
Name::
Period circadian protein (Fragments)
Experimental Method:
Predicted structure
Sequence source:
DROSOPHILA MAURITIANA

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 Q03353 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q03353|PER_DROMA Period circadian protein (Fragments) OS=Drosophila mauritiana OX=7226 GN=per PE=3 SV=2 KVSDSAYSNSCSNSQSQRSGSSKSRLSGSHSSGSSGYGGKPSTQASSSDMIIKRNKDKSRKKKKNKGAGQGAGQAQTLISASTSLEGRDEEKPRPSGTGCVEQQICRELQDQQHGEDHSEPQATEQLQQEEEDQSGSESEADRVEGVAKSEAAQSFPIPSPLSVTIVPPSMGGCGGVGHAAGLDSGLAKFDKTWEAGPGKLESMTGVGAAAAGTGQRGERVKEDSFCCVISMHDGIVLYTTPSITDVLGYPRDMWLGRSFIDFVHLKDRATFASQITTGIPIAESRGSVPKDAKSTFCVMLRRYRGLKSGGFGVIGRPVSYEPFRLGLTFREAPEEARPDNYMVSNGTNMLLVICATPIKSSYKVPDEILSQKSPKFAIRHTATGIISHVDSAAVSALGYLPQDLIGRSIMDFYHHEDLSVMKETYETVMKKGQTAGASFCSKPYRFLIQNGCYVLLETEWTSFVNPWSRKLEFVVGHHRVFQGPKQCNVFEAAPTCKLKISEEAQSRNTRIKEDIVKRLAETVSRPSDTVKQEVSRRCQALASFMETLMDEVSRADLKEGSGGSGSSGNFTTASNIHMSSVTNTSIAGTGGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGNGTNSCTGTGTTSSSRGGSAAIPPVTLTESLLNK