Q6FRR0 AF NFT

Phosphoenolpyruvate carboxykinase (ATP)

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigqsnl6kadvhl4itqm37jdxu6v327slikfro7pumzzqykktv5hwma/metadata.json
IPFS of structure file: 
bafybeibvnhjvnj773fmhjqfrl2jk33bfu27hk2dvazwxrjpiii27coinxm/AF-Q6FRR0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x10F20E5FD6223F71224Fba7496Eba14cf3dd37D0
First NFT owner address (bech32): 
genesis1zrequh7kyglhzgj0hf6fd6apfnea6d7ssvfter
Current NFT ID #289559 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
289559
Accession (UniProt):
Q6FRR0
Name::
Phosphoenolpyruvate carboxykinase (ATP)
Experimental Method:
Predicted structure
Sequence source:
CANDIDA GLABRATA (STRAIN ATCC 2001 / CBS 138 / JCM 3761 / NBRC 0622 / NRRL Y-65)

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 Q6FRR0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q6FRR0|PCKA_CANGA Phosphoenolpyruvate carboxykinase (ATP) OS=Candida glabrata (strain ATCC 2001 / CBS 138 / JCM 3761 / NBRC 0622 / NRRL Y-65) OX=284593 GN=PCK1 PE=3 SV=1 MPSKSSVSGNSVEERIRSELGLSKEVTLIRRNAPAAVLYQDALKEKKTVISSAGALIAYSGEKTGRSPKDKRIVEEETSRDNVWWGPVNKPCSERTWAINRERAADYLRTRETLYVVDAFAGWDPKYRIKVRVVCARAYHALFMTNMLIRPTEEELANFGEPDFTVWNAGQFPANARTQDMTSKTTIEINFKAMEMVILGTEYAGEMKKGIFTVMFYLMPVHHNVLTLHSSCNQGIKNGDVTLFFGLSGTGKTTLSADPHRLLIGDDEHCWSDEGVFNIEGGCYAKCINLSREKEPEIFDAIRFGSVLENVIYDSESHEVDYDDSSITENTRCAYPIDFIPSAKIPCLAPAHPKNIILLTCDASGVLPPVSKLTPEQVMYHFISGYTSKMAGTEQGVTEPEPTFSSCFGQPFLSLHPMRYATMLAEKMHEHSANAWLINTGWTGSSYVSGGKRCALKYTRAILDAIHDGSLAKAEFESLPIFNLQVPKAVEGVPSELLNPARNWSEGEAKYQSAVSKLAGLFVENFKTYQDKATSDVLAAGPQL