Q9EP64 AF NFT

Tenomodulin

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeictnbtrq546bjese6x4pi6kouizmhtlv36mwychr33m2wtuhypsqa/metadata.json
IPFS of structure file: 
bafybeifbsr2edyufamuvbokhjdtvznsv6gh4o455fhtciuiy7cvbtfnt4m/AF-Q9EP64-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xC8051e607417A2890274BC226Eb475379945EA5C
First NFT owner address (bech32): 
genesis1eqz3ucr5z73gjqn5hs3xadr4x7v5t6jursnv0w
Current NFT ID #469107 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
469107
Accession (UniProt):
Q9EP64
Name::
Tenomodulin
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 Q9EP64 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9EP64|TNMD_MOUSE Tenomodulin OS=Mus musculus OX=10090 GN=Tnmd PE=2 SV=1 MAKNPPENCEGCHILNAEALKSKKICKSLKICGLVFGILALTLIVLFWGSKHFWPEVSKKTYDMEHTFYSNGEKKKIYMEIDPITRTEIFRSGNGTDETLEVHDFKNGYTGIYFVGLQKCFIKTQIKVIPEFSEPEEEIDENEEITTTFFEQSVIWVPAEKPIENRDFLKNSKILEICDNVTMYWINPTLIAVSELQDFEEDGEDLHFPTSEKKGIDQNEQWVVPQVKVEKTRHTRQASEEDLPINDYTENGIEFDPMLDERGYCCIYCRRGNRYCRRVCEPLLGYYPYPYCYQGGRVICRVIMPCNWWVARMLGRV