A1S9I4 AF NFT

Sulfite reductase [NADPH] hemoprotein beta-component

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiam6dcpycdyhjjmvtuhmyzs2rxm3zbyjwnutaekq7vw6jtzuojfue/metadata.json
IPFS of structure file: 
bafybeic6mdulhttno7jmrnee5sx4dcy2ljb434h7tvrdlk4ipxmjwhc5dy/AF-A1S9I4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xf4ED13986579E8e227b3ED6c02276c648754EC27
First NFT owner address (bech32): 
genesis17nk38xr9085wyfana4kqyfmvvjr4fmp80usw7n
Current NFT ID #86190 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
86190
Accession (UniProt):
A1S9I4
Name::
Sulfite reductase [NADPH] hemoprotein beta-component
Experimental Method:
Predicted structure
Sequence source:
Shewanella amazonensis (strain ATCC BAA-1098 / SB2B)

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 A1S9I4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A1S9I4|CYSI_SHEAM Sulfite reductase [NADPH] hemoprotein beta-component OS=Shewanella amazonensis (strain ATCC BAA-1098 / SB2B) OX=326297 GN=cysI PE=3 SV=1 MSQYPIKPELQVQGQLSDNERLKAESNHLRGTITTDLKDEITGGFTGDNFMLVRFHGMYQQDDRDLRAERAEQKLEPLHNVMLRARMPGGIIKPEQWLAIDEFAREHTMYGSIRLTTRQTFQFHGVFKPDIKPMHQMLNKIGIDSIATAGDVNRNVLCTSNPVESELHQQAYEWAAKISEHLLPKTRAYAEIWLGEEKVETTETEPVLGDSYLPRKFKTTVVIPPHNDVDVHANDLNFVAIAENGQLVGFNVLVGGGLAMTHGDKSTYPRRAEDLGFIGLEHVLKVAEHVVTVQRDYGDRVNRKNAKTKYTLDRIGVDAFKSEVEQRVGVAFGPSRPYEFTHRGDRFGWVEGIDGKHHLTLFIENGRLLDYPGKPLKTGVAEIAKVHKGDLRMTANQNLIIAGVAAEDKAQIEQLAREHGLLDNVTTQRKNSMACVSLPTCPLAMAEAERYLPTLVTHVEGILSKHGIADDHIILRVVGCPNGCGRAMLAEAGLVGRGPGKYNLYLGGNTAGTRIPKLYLDNVAEAEILAALDSLIGRWSVERNPGECFGDFVIRVGVVAEVKVSKTDFHA