A1CGD1 AF NFT

Probable alpha-L-arabinofuranosidase B

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiaoupmh2cbtq7y43su4fhq3it7mnlfer5nttvmepsr4skrvtgydhy/metadata.json
IPFS of structure file: 
bafybeievzqaygkly2w7v6taoqr4fxcmdxicl6cou6yhcpuspkxhx3hmhiu/AF-A1CGD1-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xEa58c7534E5701aA8370E0fAEb19b7e14653e69c
First NFT owner address (bech32): 
genesis1afvvw56w2uq64qmsurawkxdhu9r98e5uajuhsx
Current NFT ID #3653 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
3653
Accession (UniProt):
A1CGD1
Name::
Probable alpha-L-arabinofuranosidase B
Experimental Method:
Predicted structure
Sequence source:
Aspergillus clavatus (strain ATCC 1007 / CBS 513.65 / DSM 816 / NCTC 3887 / NRRL 1 / QM 1276 / 107)

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 A1CGD1 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A1CGD1|ABFB_ASPCL Probable alpha-L-arabinofuranosidase B OS=Aspergillus clavatus (strain ATCC 1007 / CBS 513.65 / DSM 816 / NCTC 3887 / NRRL 1 / QM 1276 / 107) OX=344612 GN=abfB PE=3 SV=1 MLSQPSRERAFVLALGLVVSSSLAAAAPCDIYSSGGTPCVAAHSTTRALYSAYSGPLYQVKRGSDGATTNIAPRSAGGVANAAAQDTFCASMTCLITVIYDQSGRGNHLTQAPPGGFKGPEANGYDNLASAIGAPVTLNGQKAYGVFISPGTGYRNNAASGTAIGDAAEGMYAVLDGTHYNGGCCFDYGNAETSSLDTGNGHMEAIYFGTNTVWGSGSGSGPWIMADLENGLFSGSSPANNAGDPSVSYRFLTAAIKGGPNRWAIRGANAASGSLATYYSGARPNASGYNPMSKEGAIILGIGGDNSNGAQGTFYEGVMTSGYPSDATENAVQADIVAANYAVTSLTSGPALTVGSAISLRATTSCCTTRYLAHTGSTINTQVVSSASATTLKQQATWTVRTGLANSGCFSFESKDTPGSFIRHSNFALVLNGNDGTKQFKEDATFCPQAGLNGQGSSIRSWSFPTRYFRHYSNVLYAASNGGVHTFDAAGSFNDDVSWVISSGFA