B5BDB0 AF NFT

1-deoxy-D-xylulose-5-phosphate synthase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiheq5cmpyeijt2abq4dfklhifyxa3ira2u5iho266oqzzgpvg6vum/metadata.json
IPFS of structure file: 
bafybeifo4gv5ye6dxms2253eqi5xpohzltqbm2me4on47ils7xl2dns7pu/AF-B5BDB0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x81957cf22C1850f268Ea6B427f0c14A4D40792f1
First NFT owner address (bech32): 
genesis1sx2heu3vrpg0y682ddp87rq55n2q0yh3fa04ws
Current NFT ID #108483 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
108483
Accession (UniProt):
B5BDB0
Name::
1-deoxy-D-xylulose-5-phosphate synthase
Experimental Method:
Predicted structure
Sequence source:
Salmonella paratyphi A (strain AKU_12601)

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 B5BDB0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B5BDB0|DXS_SALPK 1-deoxy-D-xylulose-5-phosphate synthase OS=Salmonella paratyphi A (strain AKU_12601) OX=554290 GN=dxs PE=3 SV=1 MSFDIAKYPTLALVDSTQELRLLPKESLPKLCDELRRYLLDSVSRSSGHFASGLGTVELTVALHYVYNTPFDQLIWDVGHQAYPHKILTGRRDKIGTIRQKGGLHPFPWRGESEYDVLSVGHSSTSISAGIGIAVAAEKEGKDRHTVCVIGDGAITAGMAFEAMNHAGDIRPDMLVILNDNEMSISENVGALNNHLAQLLSGKLYSSLREGGKKVFSGVPPIKELLKRTEEHIKGMVVPGTLFEELGFNYIGPVDGHDVMGLISTLKNMRDLKGPQFLHIMTKKGRGYEPAEKDPITFHAVPKFDPSSGCLPKSSGGLPGYSKIFGDWLCETAAKDSKLMAITPAMREGSGMVEFSRKFPDRYFDVAIAEQHAVTFAAGLAIGGYKPVVAIYSTFLQRAYDQVIHDVAIQKLPVMFAIDRAGIVGADGQTHQGAFDLSYLRCIPDMVIMTPSDENECRQMLFTGYHYNDGPTAVRYPRGNAQGVALTPLEKLPIGKGLVKRHGEKLAILNFGTLMPEAAKVAEALNATLVDMRFVKPLDDTLILEMAAQHDALVTLEENAIMGGAGSGVNEVLMAHRKPVPVLNIGLPDLFIPQGTQEEARAELGLDAAGIEAKIKAWQA