Q9HFE1 AF NFT

Low-affinity iron/zinc ion transport protein fet4

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibvoyguzcdn5hrw5bfnr6mrkms2vzw7t4a53m7jqvuc7isfeh2o7u/metadata.json
IPFS of structure file: 
bafybeide3lzm72bbj7ocqfgqd5kzbui7jtmvpvmts4omut32ytp23rgcpm/AF-Q9HFE1-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x48cAFA58220078394F6FF347a5D7047Dbd6CD9CB
First NFT owner address (bech32): 
genesis1fr905kpzqpurjnm07dr6t4cy0k7kekwtw0mkg3
Current NFT ID #129429 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
129429
Accession (UniProt):
Q9HFE1
Name::
Low-affinity iron/zinc ion transport protein fet4
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 Q9HFE1 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9HFE1|FET4_SCHPO Low-affinity iron/zinc ion transport protein fet4 OS=Schizosaccharomyces pombe (strain 972 / ATCC 24843) OX=284812 GN=fet4 PE=2 SV=1 MTASITEIDSISEESNVESVSHLQHSPSFEKKGADFSISLNEKKDFASPITEEIPSPDGIATPEPETKKKLSFGARVWDLICSPGRQHDVCVAAPTQLVRSCDDYANSASTLVTNDDGTKTKVDSDEKKHKHKNVRDYIRFKHVDIGGRIFDLITRLAGTSFTFILMLIILIVWAIVGGIYRAPDNWQIVMQDGSSIQCYVSDTLLMRQQQNQHIQVLTMISQLRSRLLTTSRLLGPVLNDKTKISSVNVALMKDDVGDAEKLPTENWFDFICNYVSFMVGSIIFLVVYWIGIFIWIGFGRMLGWSDEWQLYINTAVAVELTFTSVFLQNVRHRHMKYIDRCVTSIFRIDSVIEEELRRMMGDKEPNEEITIKMDKINLGERSIDYYADLIGSGVGVVVSTCVFVAWIAIGNVMHWDSNWWLIIGTYTGLVGFLDGFVLRNVYFRESSKEATEIQTLIDEDYALYQKLDLPLPHEHITNYKSTFGGSLSQWIGWLCALPISVLFSVFVILGLIIAAGSLRFNETAQLFCNTPTMIIEGALLIVLIEAHNIANLKRRIQFRQIHLRRLTILKMLAGDNYSTTSTV