P9WHF3 AF NFT

Transcription termination factor Rho

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifmhpcs32hh3iwmqh3ztyy46lteckljncfcm5axukkcsml3c7u7ly/metadata.json
IPFS of structure file: 
bafybeih3vrraloafxdojo5izgaghcgmx76pzdrmhxy543oiwhwsafm2o6m/AF-P9WHF3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x8E8D80fE94Dd5e533A2E21A78270Ddf47E8CB724
First NFT owner address (bech32): 
genesis136xcpl55m409xw3wyxncyuxa73lgedeyuuu5ds
Current NFT ID #342995 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
342995
Accession (UniProt):
P9WHF3
Name::
Transcription termination factor Rho
Experimental Method:
Predicted structure
Sequence source:
MYCOBACTERIUM TUBERCULOSIS (STRAIN ATCC 25618 / H37RV)

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 P9WHF3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P9WHF3|RHO_MYCTU Transcription termination factor Rho OS=Mycobacterium tuberculosis (strain ATCC 25618 / H37Rv) OX=83332 GN=rho PE=1 SV=1 MTDTDLITAGESTDGKPSDAAATDPPDLNADEPAGSLATMVLPELRALANRAGVKGTSGMRKNELIAAIEEIRRQANGAPAVDRSAQEHDKGDRPPSSEAPATQGEQTPTEQIDSQSQQVRPERRSATREAGPSGSGERAGTAADDTDNRQGGQQDAKTEERGTDAGGDQGGDQQASGGQQARGDEDGEARQGRRGRRFRDRRRRGERSGDGAEAELREDDVVQPVAGILDVLDNYAFVRTSGYLPGPHDVYVSMNMVRKNGMRRGDAVTGAVRVPKEGEQPNQRQKFNPLVRLDSINGGSVEDAKKRPEFGKLTPLYPNQRLRLETSTERLTTRVIDLIMPIGKGQRALIVSPPKAGKTTILQDIANAITRNNPECHLMVVLVDERPEEVTDMQRSVKGEVIASTFDRPPSDHTSVAELAIERAKRLVEQGKDVVVLLDSITRLGRAYNNASPASGRILSGGVDSTALYPPKRFLGAARNIEEGGSLTIIATAMVETGSTGDTVIFEEFKGTGNAELKLDRKIAERRVFPAVDVNPSGTRKDELLLSPDEFAIVHKLRRVLSGLDSHQAIDLLMSQLRKTKNNYEFLVQVSKTTPGSMDSD