Q91WL0 AF NFT

Epidermal growth factor receptor kinase substrate 8-like protein 3

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigxpdrevrzs4vws7w3vd4g5tnlhbtwr7ws7nnw6kuwpxmmzo4n43q/metadata.json
IPFS of structure file: 
bafybeihe6cpm6hmtvsu3g4e2yvaf7hwi65necbno2emt37gexj6vr2n5bi/AF-Q91WL0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x362a6d063b1B7E1B6EfD3A9A7CA3612e3FE037AA
First NFT owner address (bech32): 
genesis1xc4x6p3mrdlpkmha82d8egmp9cl7qda2uxz2xy
Current NFT ID #120421 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
120421
Accession (UniProt):
Q91WL0
Name::
Epidermal growth factor receptor kinase substrate 8-like protein 3
Experimental Method:
Predicted structure
Sequence source:
MUS MUSCULUS

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 Q91WL0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q91WL0|ES8L3_MOUSE Epidermal growth factor receptor kinase substrate 8-like protein 3 OS=Mus musculus OX=10090 GN=Eps8l3 PE=2 SV=1 MSRPSSRAIYLHRKEYSQSMASEPTLLQHRVEHLMTCKLGTQRVREPKDALQKLQEMDAQGRVWSQDLFLQVRDGWLHLLDIETKEELDSYRLDNIKAIDVALNTCSYNSILSVTVQESGLPGISTLLFQCQEVGAEQLRTSLQKALEEELEERPRFGVHHPSQDRWKGPPLERPLPIQQAPPLEQRFSPEHRFPPEQPHNMTSERSISPSSRSLTHYPSAREPNGFTLPPPPRRAPSPEDPERDEEVLNHVLRDIELFAGKLKEVQARNSHKKTKLGRKKKKSKNGITQAEYIDCFQKIKLSFNLLGKLALRMQETSAPEFVGLIFQTLKFILSQCPEAGLPAKVISPLLTPKAIDLLQSCLSPPEDTLWKSLGTSWTTSWADWTGSEPPPYQPTFYDGWQIPQPRSMMPITNQDSISLRGSRMRSSLHFPRDEPYNHNPEYEDSNLPLSSPSPGRAALKMQVLYEFEARNAQELTVAQGEILEVLDQSKRWWLVKNEAGLTGYIPSNILEPLPAGAPRGHRQPSFRAPMLRLSSKPEEVTAWLQAENFSTVTVRTLGSLMGSQLLHMRPGELQMLCPQEAPRIQARLDAVRRMLGMTH