Q1C1E0 AF NFT

Glycogen debranching enzyme

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibsim7kuohj4mfmjix55forws3j3dg3guqspew33g4uxkrniajdqu/metadata.json
IPFS of structure file: 
bafybeiezvytizcrjknao47jmuxk5e6fztbv4r2pqkos5ziltwiwi63pmmu/AF-Q1C1E0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7b62bBB2fd1BEFAF6006b9Ca6951A38Dfd038f9d
First NFT owner address (bech32): 
genesis10d3thvhar0h67cqxh89xj5dr3h7s8rua0gkvwr
Current NFT ID #149024 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
149024
Accession (UniProt):
Q1C1E0
Name::
Glycogen debranching enzyme
Experimental Method:
Predicted structure
Sequence source:
Yersinia pestis bv. Antiqua (strain Antiqua)

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 Q1C1E0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q1C1E0|GLGX_YERPA Glycogen debranching enzyme OS=Yersinia pestis bv. Antiqua (strain Antiqua) OX=360102 GN=glgX PE=3 SV=1 MAVLTHGSPTPSGAHFDGKGINFTLFSAHAEQVTLCLFDEQGQERQIAMPARTGDIWHGYLPGGKPGQRYGYRVSGPFEPSRGHRFNPHKLLIDPRTRALEGKVGDDPRFTGGVSQPDVRDSAAALPKCLVIHEEYDWQGDKPPAIPWGNTVIYEAHVRGLTQLHPDIPPELRGTYAALAHPALIEHLKTLGITTLELLPVQFHIDEPRLQKMGLSNYWGYNVLAPFAVDPDYASGREGISPLRELRDAVKALHNAGIEVILDVVFNHSAELDVFGPTLCQRGIDNASYYWLTPDGEYDNITGCGNALRLSHPYVTQWVIDCLNYWRDSCHVDGFRFDLGTVLGRTPAFDQHAPLFAALAADERLSACKLIAEPWDIGLGGYQLGNFPTGFSEWNDQYRDAMRGFWLRGEVPRGTFAQHFAASSRLFEQRGRLPSASINQITAHDGFTLLDLLCFNQKHNQMNGEENRDGSDNNHSNNFGCEGLVADAAIWQRRKACQRALLTTLLLSQGTPMLLAGDEQGHSQQGNNNAYCQNNILTWLDWGSADRALMTFTADLIRLRQQIPALTQDQWWQSGDSNVQWLDSQGQALSDAAWEQGCQQQLQILLSQRWLVLINATDHECEMHLPEGEWEGIPPFGVSDHAERLTTWRGSAHTICVLIKRD