Q1ME33 AF NFT

UDP-N-acetylglucosamine--N-acetylmuramyl-(pentapeptide) pyrophosphoryl-undecaprenol N-acetylglucosamine transferase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeif33wn2kys36fgfagq4hbsgd5yzr7fhs55pqnjq6bbmmmhggwa66m/metadata.json
IPFS of structure file: 
bafybeibymeiohhwdx5yo2k34pipapjxbd3ywwmlaro3lgt5s5zomupn7du/AF-Q1ME33-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x24c1edb3DD9C691e235aB9D784325EA74d43a870
First NFT owner address (bech32): 
genesis1ynq7mv7an353ug66h8tcgvj75ax582rs639se7
Current NFT ID #252539 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
252539
Accession (UniProt):
Q1ME33
Name::
UDP-N-acetylglucosamine--N-acetylmuramyl-(pentapeptide) pyrophosphoryl-undecaprenol N-acetylglucosamine transferase
Experimental Method:
Predicted structure
Sequence source:
RHIZOBIUM LEGUMINOSARUM BV. VICIAE (STRAIN 3841)

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 Q1ME33 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q1ME33|MURG_RHIL3 UDP-N-acetylglucosamine--N-acetylmuramyl-(pentapeptide) pyrophosphoryl-undecaprenol N-acetylglucosamine transferase OS=Rhizobium leguminosarum bv. viciae (strain 3841) OX=216596 GN=murG PE=3 SV=1 MSKGIVLLAAGGTGGHVFPAEALAFKLKERGYSVHLVTDSRAERYAGKFPAEEIHVVPSATIGSKNPVAVARSLWTLWSGMRAAKKLIQRLQPVIVVGFGGYPTVPPLLAATRLGVPSMIHEQNAVMGRANKALATRVQAIAGGFLPEGGAAFPDKTVTTGNPVRPAIIAAAEVPYTPSHPGEAFNLVVFGGSQGAQYFSKALPTAISLLDDALRVRLRITQQVRPEDMEMVSGCVARLEMGADIAPFFTDMAERLARAHLVICRSGASTVSEISVIGRPAVLVPYPHALDHDQAANAAALAATGGAKVIAQSELSPEKIAAILTAVMNDPEKLSHMAAAAKLAGKPDAANLLADMVEAIAARRTIAEFKRTRA