P9WHF2 AF NFT

Transcription termination factor Rho

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigmrenhk5yrasxwuaxvmb7u72eilfsaefy45veqktfljfgygqnmwm/metadata.json
IPFS of structure file: 
bafybeihyvs2erlhtgb7sslpeb76wrtkbhy7scaaycao533cqrmio3luzf4/AF-P9WHF2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x24BCD69B8A95498596A2729d0C645Ec0B75463E7
First NFT owner address (bech32): 
genesis1yj7ddxu2j4yct94zw2wscez7czm4gcl8zfqhf2
Current NFT ID #342994 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
342994
Accession (UniProt):
P9WHF2
Name::
Transcription termination factor Rho
Experimental Method:
Predicted structure
Sequence source:
MYCOBACTERIUM TUBERCULOSIS (STRAIN CDC 1551 / OSHKOSH)

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 P9WHF2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P9WHF2|RHO_MYCTO Transcription termination factor Rho OS=Mycobacterium tuberculosis (strain CDC 1551 / Oshkosh) OX=83331 GN=rho PE=3 SV=1 MTDTDLITAGESTDGKPSDAAATDPPDLNADEPAGSLATMVLPELRALANRAGVKGTSGMRKNELIAAIEEIRRQANGAPAVDRSAQEHDKGDRPPSSEAPATQGEQTPTEQIDSQSQQVRPERRSATREAGPSGSGERAGTAADDTDNRQGGQQDAKTEERGTDAGGDQGGDQQASGGQQARGDEDGEARQGRRGRRFRDRRRRGERSGDGAEAELREDDVVQPVAGILDVLDNYAFVRTSGYLPGPHDVYVSMNMVRKNGMRRGDAVTGAVRVPKEGEQPNQRQKFNPLVRLDSINGGSVEDAKKRPEFGKLTPLYPNQRLRLETSTERLTTRVIDLIMPIGKGQRALIVSPPKAGKTTILQDIANAITRNNPECHLMVVLVDERPEEVTDMQRSVKGEVIASTFDRPPSDHTSVAELAIERAKRLVEQGKDVVVLLDSITRLGRAYNNASPASGRILSGGVDSTALYPPKRFLGAARNIEEGGSLTIIATAMVETGSTGDTVIFEEFKGTGNAELKLDRKIAERRVFPAVDVNPSGTRKDELLLSPDEFAIVHKLRRVLSGLDSHQAIDLLMSQLRKTKNNYEFLVQVSKTTPGSMDSD