C1EX54 AF NFT

1,4-alpha-glucan branching enzyme GlgB

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeicpffw7ryvq5wepx47tyhueimbojmaqfawgxktge3ghqkqrql4ikm/metadata.json
IPFS of structure file: 
bafybeib7v3liqqvejx2zamsqbbdy5dif2k5hiij6ncq72tdtuxaeacw6vy/AF-C1EX54-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xcF8718B7057788C15119b9100F4d16e9b411fbD9
First NFT owner address (bech32): 
genesis1e7r33dc9w7yvz5gehygq7ngkax6pr77ehjhycd
Current NFT ID #148345 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
148345
Accession (UniProt):
C1EX54
Name::
1,4-alpha-glucan branching enzyme GlgB
Experimental Method:
Predicted structure
Sequence source:
Bacillus cereus (strain 03BB102)

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 C1EX54 research and analysis (ICN3D with VR)

FASTA sequences

>sp|C1EX54|GLGB_BACC3 1,4-alpha-glucan branching enzyme GlgB OS=Bacillus cereus (strain 03BB102) OX=572264 GN=glgB PE=3 SV=1 MSVINCEEVKRDEFHTEKYYESYNIFGAHIVTEDEMRGVRFTVWAPHAKAMSVVGDFNEWDYEQHKMLQVTEEGIWSLFIPHIEEREIYKYAIETMAGDVIFKADPYAVYAEVRPNTASVVFDIKGYEWNDKNWSRKKKKKSVYKEAMTVYELHFGSWKKKEDGTLYSYREMAEELIPYVVEHQFTHIEIMPLVEHPYDRSWGYQGTGYYAATSRFGTPYDLMHFVDECHKYGIGVILDWVPGHFCKDAHGLYLFDGTPTYEYKDKDVQENPVWGTVNFDLGKREVRNFLISNALFWMRYFHIDGFRVDAVANMLYWNKEGQEQSNEHAVSFLRELNEAVFAEDEDFLMTAEDSTAWPLVTAPTYEGGLGFNYKWNMGWMNDVLKYMECAPEYRKYIHDKMTFSLLYTYSENFILPLSHDEVVHGKKSLLNKMPGDYWDKFAQLRLLYGYFFTHPGKKLLFMGGEFGQFDEWKDLEDLDWNLHDFEMHRYMHDYFKELIALYKRSKPLWQLDHSREGFQWIDANNNEQSIFSFIRQGDKQEDALVVVCNFTKATYENYKVGVPDFEYYNEILNSDAEQYGGSGQVNKKRLKTIQEPYHNQTAHVEITIPPFGVSILRPVKTRKGSKKQDGSKTKVRSNVTSRGKR