B7LM75 AF NFT

Probable 4-deoxy-4-formamido-L-arabinose-phosphoundecaprenol deformylase ArnD

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiamv5x5fjvcmzpiiqfx6fjzot4yr3273clfvly36mmpbfnusfkj5e/metadata.json
IPFS of structure file: 
bafybeibscbzkcjabpzypedsmqnq4aiibey2wtlv6uwf7vgoupmfuvicww4/AF-B7LM75-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x362a6d063b1B7E1B6EfD3A9A7CA3612e3FE037AA
First NFT owner address (bech32): 
genesis1xc4x6p3mrdlpkmha82d8egmp9cl7qda2uxz2xy
Current NFT ID #23870 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
23870
Accession (UniProt):
B7LM75
Name::
Probable 4-deoxy-4-formamido-L-arabinose-phosphoundecaprenol deformylase ArnD
Experimental Method:
Predicted structure
Sequence source:
Escherichia fergusonii (strain ATCC 35469 / DSM 13698 / CCUG 18766 / IAM 14443 / JCM 21226 / LMG 7866 / NBRC 102419 / NCTC 12128 / CDC 0568-73)

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 B7LM75 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B7LM75|ARND_ESCF3 Probable 4-deoxy-4-formamido-L-arabinose-phosphoundecaprenol deformylase ArnD OS=Escherichia fergusonii (strain ATCC 35469 / DSM 13698 / CCUG 18766 / IAM 14443 / JCM 21226 / LMG 7866 / NBRC 102419 / NCTC 12128 / CDC 0568-73) OX=585054 GN=arnD PE=3 SV=1 MTKVGLRIDVDTFRGTREGVPRLLETLDKHNIQASFFFSVGPDNMGRHLWRLVKPQFLWKMLRSNAASLYGWDILLAGTAWAGKEIGKANAAIIREAAKHHEIGLHAWDHHAWQTHSGNWDQQTLVNDIARGLRVLEEIIGQPVSCSAVAGWRADQQVVEAKEFFHLRYNSDCRGTMPFRPQLESGKSGTPQIPVTLPTWDEVVGREVKTADFNGWLLNRILRDRGTPVYTIHAEVEGCAYHLDFVDLLKRAAREGITFCPLSELLPATQDALPLGEIVRGHIAGREGWLGCQQCVSLSQ