A9R5L9 AF NFT

Glycogen debranching enzyme

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigl7ahvgkitj7225xgap23p7w4sk3wmf4xkwkc77anms45mmdfdhy/metadata.json
IPFS of structure file: 
bafybeibzky64om6rp3grx4b7fa62yt6grci3xw4xsruvsm45kdozidftmm/AF-A9R5L9-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xB82BBF8d96C5B3247800FA85d8C9E56fE8DbE5c2
First NFT owner address (bech32): 
genesis1hq4mlrvkckejg7qql2za3j09dl5dhewzhxxfam
Current NFT ID #149027 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
149027
Accession (UniProt):
A9R5L9
Name::
Glycogen debranching enzyme
Experimental Method:
Predicted structure
Sequence source:
Yersinia pestis bv. Antiqua (strain Angola)

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 A9R5L9 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A9R5L9|GLGX_YERPG Glycogen debranching enzyme OS=Yersinia pestis bv. Antiqua (strain Angola) OX=349746 GN=glgX PE=3 SV=1 MAVLTHGSPTPSGAHFDGKGINFTLFSAHAEQVTLCLFDEQGQERQIAMPARTGDIWHGYLPGGKPGQRYGYRVSGPFEPSRGHRFNPHKLLIDPRTRALEGKVGDDPRFTGGVSQPDVRDSAAALPKCLVIHEEYDWQGDKPPAIPWGNTVIYEAHVRGLTQLHPDIPPELRGTYAALAHPALIEHLKTLGITTLELLPVQFHIDEPRLQKMGLSNYWGYNVLAPFAVDPDYASGREGISPLRELRDAVKALHNAGIEVILDVVFNHSAELDVFGPTLCQRGIDNASYYWLTPDGEYDNITGCGNALRLSHPYVTQWVIDCLNYWRDSCHVDGFRFDLGTVLGRTPAFDQHAPLFAALAADERLSACKLIAEPWDIGLGGYQLGNFPTGFSEWNDQYRDAMRGFWLRGEVPRGTFAQHFAASSSLFEQRGRLPSASINQITAHDGFTLLDLLCFNQKHNQMNGEENRDGSDNNHSNNFGCEGLVADAAIWQRRKACQRALLTTLLLSQGTPMLLAGDEQGHSQQGNNNAYCQNNILTWLDWGSADRALMTFTADLIRLRQQIPALTQDQWWQSGDSNVQWLDSQGQALSDAAWEQGCQQQLQILLSQRWLVLINATDHECEMHLPEGEWEGIPPFGVSDHAERLTTWRGSAHTICVLIKRD