Q5APK7 AF NFT

Cytosolic Fe-S cluster assembly factor NAR1

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiekcdmqxsdi55xtf54yjsfiwtjszsh4bm7fozrcbi5gqxasj3nhse/metadata.json
IPFS of structure file: 
bafybeiaqe4asdnjv4bawrvc2ng4eted5c36dr42obxymiv6sqgdplw7nga/AF-Q5APK7-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x3aC9742557B5a280CCBE5c6e54942967FB5201eD
First NFT owner address (bech32): 
genesis18tyhgf2hkk3gpn97t3h9f9pfvla4yq0d3xuj9h
Current NFT ID #259404 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
259404
Accession (UniProt):
Q5APK7
Name::
Cytosolic Fe-S cluster assembly factor NAR1
Experimental Method:
Predicted structure
Sequence source:
CANDIDA ALBICANS (STRAIN SC5314 / ATCC MYA-2876)

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 Q5APK7 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q5APK7|NAR1_CANAL Cytosolic Fe-S cluster assembly factor NAR1 OS=Candida albicans (strain SC5314 / ATCC MYA-2876) OX=237561 GN=NAR1 PE=3 SV=2 MSALLSADDLNDFISPGVACIKPLASSSTNTTTTNTTDSYNENGEVEIQIDSQGNPLEISKIDDKQFQTNKLTPAQISLADCLACSGCITSAEEVLVAQHSHQELIKALQSQKETNKVFVVSISHQSRASLAMAYNVSIENMDKCLIDLFIRQMGFTYIVGTSLGRKLSLINEAKEIINRKTKGSGTGGIDSDSSSGPILSSICPGWVLYAEKTHPYIIPKMSTVKSPQQITGCLLKNLTSNSLNIEKSKIYHLSIMPCFDKKLESARPEVYEEEEEEEEEKDKALVSVPDVDCVITAKELITLLEECPQYQLIPPTLPQEELIGGGCLSMTEIYKQYAPPNWPFIEISWSNDSGSASGGYAYNYLTIYRNDLILKGYDGNKFTINLINGRNPDIYEMRLMYNGENKEKLASAAVVNGFRNIQNLVRKLKPNTGKSTNTTTTTTKSKVNPLAARRRARIANNRGKPETKSTSEVNSQEMEIVADASKVDYVEIMACPNGCINGGGQISAPNTTTTSITLPQKEIEKQWINAVLEKYNSIPMFDLSSQSSSSSSPNEIIKFIEWSKKFENQFNISDNRLFKTHFNPVEKNIIMSVDDPATALLVGSKW