Q5U4Q0 AF NFT

WW domain-containing adapter protein with coiled-coil

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeicsfgzvjsrwlqfnrn2fnrqqzoioqn2bcbeke4s7aydby7xi3h5cem/metadata.json
IPFS of structure file: 
bafybeidg55eal5ttpfty4fulynbghcpzbj4olaxaf44ybnat4dobotk3iq/AF-Q5U4Q0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7012c0b45c68a2c067644b9d3e5DDa06892c6957
First NFT owner address (bech32): 
genesis1wqfvpdzudz3vqemyfwwnuhw6q6yjc62hg2ks0z
Current NFT ID #498694 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
498694
Accession (UniProt):
Q5U4Q0
Name::
WW domain-containing adapter protein with coiled-coil
Experimental Method:
Predicted structure
Sequence source:
XENOPUS TROPICALIS

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 Q5U4Q0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q5U4Q0|WAC_XENTR WW domain-containing adapter protein with coiled-coil OS=Xenopus tropicalis OX=8364 GN=wac PE=2 SV=1 MVMYARKQARLSDGCHDRRDSQPYQTLKYSSKSHPSSSDHRHDKMRDSTDPSPPNKMRRSNSPENKYIDSAGHGKAKSMHLHRVRERDGGTSFSPQENSHNHSAIHSSNSHSSTPSKTSDSAYDPADDWSEHISSSGKKYYYNCRTEVSQWEKPKEWLEREQRQKETSKVAVNSFPKDRDYRREAMQAAAAVEEKHSSDTSTMLPQNILSQTSRHNDRDYRLPRTDSHSSAAPVQQPVKAAVHPAAAPSTVPSSPFTVQPDHPPPKKSYDANGAALSKLPTPTSSIPVPKSERKETASSDKSSCTTPSTSSAPGLNLSAAPPSSSSSTVPVSPVPQSPIPPILQDPNLLRQLLPALQATLQLNNSNVDISKINEAAVTQASLQSILHKILTAGPSAFNITSLISQVAQLSAQAAQSNQSPMSLTSDASSPRSYVSPRISTPQTNTVPHKPLLSTPPVTSQPKVGTPGSKQGSSAQTASQQSSAADKSQGHEPTSPRNLQRSSSQRSPSPGPNHNSSTCASSTSAPQNSSARSSCSLTPTLAAYFNENLVKHVQGWPADHAEKQASRLREEAHNMGSIHMSEVCTELKNLRSLVRVCEIQATLREQRILFLRQQIKELEKLKNQNSFMV