Q4WM08 AF NFT

Probable 1,4-beta-D-glucan cellobiohydrolase B

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeictcfzy4evscbinx63534p2v5yld6ey6irkodb65btphflz3vpuqy/metadata.json
IPFS of structure file: 
bafybeifmeqkxuzs7udchgehjk5twgimfcmete3gdlq5vqmmtkzndkymle4/AF-Q4WM08-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xb4D2d9c96b0D792d0b77e7147D724cc1F801ae58
First NFT owner address (bech32): 
genesis1knfdnjttp4uj6zmhuu286ujvc8uqrtjce36hs0
Current NFT ID #52653 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
52653
Accession (UniProt):
Q4WM08
Name::
Probable 1,4-beta-D-glucan cellobiohydrolase B
Experimental Method:
Predicted structure
Sequence source:
NEOSARTORYA FUMIGATA (STRAIN ATCC MYA-4609 / AF293 / CBS 101355 / FGSC A1100)

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 Q4WM08 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q4WM08|CBHB_ASPFU Probable 1,4-beta-D-glucan cellobiohydrolase B OS=Neosartorya fumigata (strain ATCC MYA-4609 / Af293 / CBS 101355 / FGSC A1100) OX=330879 GN=cbhB PE=1 SV=1 MLASTFSYRMYKTALILAALLGSGQAQQVGTSQAEVHPSMTWQSCTAGGSCTTNNGKVVIDANWRWVHKVGDYTNCYTGNTWDTTICPDDATCASNCALEGANYESTYGVTASGNSLRLNFVTTSQQKNIGSRLYMMKDDSTYEMFKLLNQEFTFDVDVSNLPCGLNGALYFVAMDADGGMSKYPTNKAGAKYGTGYCDSQCPRDLKFINGQANVEGWQPSSNDANAGTGNHGSCCAEMDIWEANSISTAFTPHPCDTPGQVMCTGDACGGTYSSDRYGGTCDPDGCDFNSFRQGNKTFYGPGMTVDTKSKFTVVTQFITDDGTSSGTLKEIKRFYVQNGKVIPNSESTWTGVSGNSITTEYCTAQKSLFQDQNVFEKHGGLEGMGAALAQGMVLVMSLWDDHSANMLWLDSNYPTTASSTTPGVARGTCDISSGVPADVEANHPDAYVVYSNIKVGPIGSTFNSGGSNPGGGTTTTTTTQPTTTTTTAGNPGGTGVAQHYGQCGGIGWTGPTTCASPYTCQKLNDYYSQCL