B5Z3C6 AF NFT

Sulfite reductase [NADPH] hemoprotein beta-component

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigrdq36j4yox4f6o6n4uexsdsaqivveoddc5qvrepaumgib5yw6o4/metadata.json
IPFS of structure file: 
bafybeicobi7narxme52waipc732tmj2vmfd4cdiyp34xi35wvbrc2lznfe/AF-B5Z3C6-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7012c0b45c68a2c067644b9d3e5DDa06892c6957
First NFT owner address (bech32): 
genesis1wqfvpdzudz3vqemyfwwnuhw6q6yjc62hg2ks0z
Current NFT ID #86119 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
86119
Accession (UniProt):
B5Z3C6
Name::
Sulfite reductase [NADPH] hemoprotein beta-component
Experimental Method:
Predicted structure
Sequence source:
Escherichia coli O157:H7 (strain EC4115 / EHEC)

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 B5Z3C6 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B5Z3C6|CYSI_ECO5E Sulfite reductase [NADPH] hemoprotein beta-component OS=Escherichia coli O157:H7 (strain EC4115 / EHEC) OX=444450 GN=cysI PE=3 SV=1 MSEKHPGPLVVEGKLTDAERMKLESNYLRGTIAEDLNDGLTGGFKGDNFLLIRFHGMYQQDDRDIRAERAEQKLEPRHAMLLRCRLPGGVITTKQWQAIDKFAGENTIYGSIRLTNRQTFQFHGILKKNVKPVHQMLHSVGLDALATANDMNRNVLCTSNPYESQLHAEAYEWAKKISEHLLPRTRAYAEIWLDQEKVATTDEEPILGQTYLPRKFKTTVVIPPQNDIDLHANDMNFVAIAENGKLVGFNLLVGGGLSIEHGNKKTYARTASEFGYLPLEHTLAVAEAVVTTQRDWGNRTDRKNAKTKYTLERVGVETFKAEVERRAGIKFEPIRPYEFTGRGDRIGWVKGIDDNWHLTLFIENGRILDYPGRPLKTGLLEIAKIHKGDFRITANQNLIIAGVPESEKAKIEKIAKESGLMNAVTPQRENSMACVSFPTCPLAMAEAERFLPSFIDNIDNLMAKHGVSDEHIVMRVTGCPNGCGRAMLAEVGLVGKAPGRYNLHLGGNRIGTRIPRMYKENITEPEILASLDELIGRWAKEREAGEGFGDFTVRAGIIRPVLDPARDLWD