Q2KCN7 AF NFT

UPF0262 protein RHE_CH00582

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihuxcrez4mjg3pofjox4rnlnlhty3nl6mtns2bouc3vqpekcde2py/metadata.json
IPFS of structure file: 
bafybeiewysfppck6tojqhcmaevmxtgvkpeizy3ja7sk425wlstnwunqdum/AF-Q2KCN7-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xa73BAb1DabE4333A884D03393eAa10c3B4215494
First NFT owner address (bech32): 
genesis15ua6k8dtusen4zzdqvuna2sscw6zz4y5hahjw0
Current NFT ID #519844 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
519844
Accession (UniProt):
Q2KCN7
Name::
UPF0262 protein RHE_CH00582
Experimental Method:
Predicted structure
Sequence source:
RHIZOBIUM ETLI (STRAIN CFN 42 / ATCC 51251)

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 Q2KCN7 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q2KCN7|Y582_RHIEC UPF0262 protein RHE_CH00582 OS=Rhizobium etli (strain CFN 42 / ATCC 51251) OX=347834 GN=RHE_CH00582 PE=3 SV=1 MAAGDFRLCDVVLDDTIGRSTPDVEHERAVAIFDLIEENRFEPLGHSGGPYRLNISLMDSKLVFAIKTEEGGDVATHILSLTPFRRIVKDYFMICESYYEAIRSATPSRIEAIDMGRRGIHNEGSQTLKDRLAGKIEVDFDTARRLFTLVCVLYWRG