B5E7Q3 Glycerol-3-phosphate dehydrogenase [NAD(P)+] MolNFT, Molecular NFT on GenesisL1

Glycerol-3-phosphate dehydrogenase [NAD(P)+]

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeihw3yhvivvzd7uo5iviojfu7wvkvvvvulihbo6k52mwtjou4punue/metadata.json

IPFS of structure file:

bafybeibverfcbvc6dl4rktdop5t3tqk3x3egdeuyxhzr2vgckfx25pwkaa/AF-B5E7Q3-F1-model_v2.pdb

First NFT owner address (eip-55):

0x445FcaF410c19e7D2CA84b4B533389046f16f516

First NFT owner address (bech32):

genesis1g30u4aqscx086t9gfd94xvufq3h3dagkanmt9c

Current NFT ID #155611 owner (web3):

0x445FcaF410c19e7D2CA84b4B533389046f16f516

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
155611
Accession (UniProt):
B5E7Q3
Name::
Glycerol-3-phosphate dehydrogenase [NAD(P)+]
Experimental Method:
Predicted structure
Sequence source:
Citrifermentans bemidjiense (strain ATCC BAA-1014 / DSM 16622 / JCM 12645 / Bem)

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 B5E7Q3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B5E7Q3|GPDA_CITBB Glycerol-3-phosphate dehydrogenase [NAD(P)+] OS=Citrifermentans bemidjiense (strain ATCC BAA-1014 / DSM 16622 / JCM 12645 / Bem) OX=404380 GN=gpsA PE=3 SV=1 MAEKIAVIGAGSWGTTLADLLAKKGHEVTLWAYEPELVLEMRDNRENSLFLPGIKLNERLAFTNDLAEAYRGCSMVLCVVPSQLVRRVMTNSLPFLPKEAIIVSASKGIEVDTLATVSEIYQEILPPEQFQVLAALSGPSFAREVALEMPTAVTAAASSEAVARRVQEAFTTDYFRVYRNSDVVGVELGGAIKNVIAIAAGISDGLGFGSNTRAALITRGLAEMTRLGVAMGAQPSTFAGLAGMGDLVLTCTGDLSRNRSVGIQIGQGRTLSEILGEMRMVAEGVKTTESAYNLAKKLGVEMPIIEQMYQMLYQNKSAREAVLELMTRNLKAEGV

B5E7Q3 AF NFT

MOLNFT AF v1

NFT data

MOLNFT B5E7Q3 research and analysis (ICN3D with VR)

FASTA sequences

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