B7GQ76 AF NFT

UDP-N-acetylmuramoylalanine--D-glutamate ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidjs36itd4ywfydrlkwfd2pt4mxmwdmescsnks6srmkvkswda47da/metadata.json
IPFS of structure file: 
bafybeicoapsmg3lxapyuvmeygmg5wwf327ldcmchdwxsfttazld4ytf5oa/AF-B7GQ76-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xFCd07EE2Dc6A020627FBe36C379d324e4f874651
First NFT owner address (bech32): 
genesis1lng8ackudgpqvflmudkr08fjfe8cw3j3pdd6c0
Current NFT ID #251424 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
251424
Accession (UniProt):
B7GQ76
Name::
UDP-N-acetylmuramoylalanine--D-glutamate ligase
Experimental Method:
Predicted structure
Sequence source:
BIFIDOBACTERIUM LONGUM SUBSP. INFANTIS (STRAIN ATCC 15697 / DSM 20088 / JCM 1222 / NCTC 11817 / S12)

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 B7GQ76 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B7GQ76|MURD_BIFLS UDP-N-acetylmuramoylalanine--D-glutamate ligase OS=Bifidobacterium longum subsp. infantis (strain ATCC 15697 / DSM 20088 / JCM 1222 / NCTC 11817 / S12) OX=391904 GN=murD PE=3 SV=1 MQVADKTVVIAGLGVSGTSLAEVLRERGAHVIGVDERKPEADLRSFDDVDWDHVDYVMSSPVFNPRTPFVLEAQRRGIPVMSEVEFAWQLRVNNERTGTPAPWIGITGTNGKTSTTEMTSEMLTACGLDAPTAGNIASGDMSMSLSRCATNPQHDVLCVELSSFQLHFTDSLALDCAAITNIADDHLDWHGGRENYAADKSKVFHNAKHAIVYNAQDAKVSELAAEAQTAEGCRKVGFTLEAPQAGQIGIEDGWIVDRSGVAGGAVGEPVRLAAITDFTHLAEPDGSLYPHLVADALTALALVLGLGADRDTALKALTSFKPGGHRIETVAEAVVEGGSVRFVDDSKATNGHAARASLSSFPAKSVIWIAGGLAKGSRFEDLVKDQAHTIKAAVIIGKDQQPMIEAFASQAPDIPVTIIDPEDNDTVMDRAVEACGTYAAAGDIVLMAPACASMDQFKSYADRGNRFAAAAKTWSEVHGLH