B2VG72 AF NFT

Guanosine-5'-triphosphate,3'-diphosphate pyrophosphatase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiginyenmrzob3d7jrcj2pyvgwky5gfyfkcwdlxeu3jq7ps2rjsvqa/metadata.json
IPFS of structure file: 
bafybeifb3l6yldtecnfyatqnj7biby7lg6bwockeawcwqtlyjghx2d6gqu/AF-B2VG72-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x9Ea1c8D4c1A5bDE0a3a9E14459F06eb4dcf9FEf1
First NFT owner address (bech32): 
genesis1n6su34xp5k77pgafu9z9nurwknw0nlh3tj8jrf
Current NFT ID #157147 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
157147
Accession (UniProt):
B2VG72
Name::
Guanosine-5'-triphosphate,3'-diphosphate pyrophosphatase
Experimental Method:
Predicted structure
Sequence source:
Erwinia tasmaniensis (strain DSM 17950 / CFBP 7177 / CIP 109463 / NCPPB 4357 / Et1/99)

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 B2VG72 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B2VG72|GPPA_ERWT9 Guanosine-5'-triphosphate,3'-diphosphate pyrophosphatase OS=Erwinia tasmaniensis (strain DSM 17950 / CFBP 7177 / CIP 109463 / NCPPB 4357 / Et1/99) OX=465817 GN=gppA PE=3 SV=1 MRSASSLYAAIDLGSNSFHMLVVREVAGSIQTIARIKRKVRLAAGLDADNNLSAEAMDRGWQCLRLFSEQLQDIPPEQIRVVATATLRIAANAGSFLAQAQKLLGCPVNVISGEEEARLIYQGVSHTTGGSDKRLVVDIGGGSTELVTGRGSQPTTLYSLSMGCVTWLERYFSDRQLGKVNFEQAEQAARAMIRPIADSLKAQGWQVCVGASGTVQALQEIMMAQGMDERITLNKLQQLKQRAIECGKLEELEIEGLTLERALVFPSGLSILIAIFSELNISSMTLAGGALREGLLYGMLPLPVDRDIRSRTLHDVQRRFSVDPEQAERVRQLADSFARQVSLQWKLDDRSRELLGSACLLHEIGLSVDFRQAPQHAAYLVRYLDLPGFTPAQKKLLATLLQNQVGNIDLPLLSQQNALLPRIAERLSRLLRLAIIFASRRRDDRLPAVRLQADDDNLTVTLPSGWLEAHPLRAELLEQEARWQGYVHWPLIIA