P35697 AF NFT

Beta-elicitin DRE-beta

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeic6acxbrzmzs7p6vpcsjxohal6yryzp5xiliajnzwfedzraumujfm/metadata.json
IPFS of structure file: 
bafybeigacnzi5cmmk2ufopduubqf4we7yon6mnaic6sjzxhcbxrkcmbmzq/AF-P35697-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x434b0DC4af054BE165a98eb346BDbBb0889A5EB3
First NFT owner address (bech32): 
genesis1gd9sm390q497zedf36e5d0dmkzyf5h4ngcsemv
Current NFT ID #115755 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
115755
Accession (UniProt):
P35697
Name::
Beta-elicitin DRE-beta
Experimental Method:
Predicted structure
Sequence source:
Phytophthora drechsleri

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 P35697 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P35697|ELIB_PHYDR Beta-elicitin DRE-beta OS=Phytophthora drechsleri OX=4794 PE=1 SV=1 TTCTSTQQTAAYTTLVSILSDSSFNKCASDSGYSMLTAKALPTTAQYKLMCASTACNTMIKKIVSLNPPNCDLTVPTSGLVLNVYEYANGFSTKCASL