Q6ZU52 AF NFT

Uncharacterized protein KIAA0408

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeicmz7on6ybmngrewkavbvwgtbaf64abl6x4kmsixpv2nuykwbg66q/metadata.json
IPFS of structure file: 
bafybeifur7afwy3mrdmhdpras4l4xmlkh7mxssbvxs3l4x5naer6a2ml3a/AF-Q6ZU52-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x704b266C60eE3C2b5627B10EA6a5488E5F686b34
First NFT owner address (bech32): 
genesis1wp9jvmrqac7zk438ky82df2g3e0ks6e5y02nwv
Current NFT ID #196646 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
196646
Accession (UniProt):
Q6ZU52
Name::
Uncharacterized protein KIAA0408
Experimental Method:
Predicted structure
Sequence source:
HOMO SAPIENS

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 Q6ZU52 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q6ZU52|K0408_HUMAN Uncharacterized protein KIAA0408 OS=Homo sapiens OX=9606 GN=KIAA0408 PE=1 SV=1 MDLHKQWENTETNWHKEKMELLDQFDNERKEWESQWKIMQKKIEELCREVKLWRKININESAKIIDLYHEKTIPEKVIESSPNYPDLGQSEFIRTNHKDGLRKENKREQSLVSGGNQMCKEQKATKKSKVGFLDPLATDNQKECEAWPDLRTSEEDSKSCSGALSTALEELAKVSEELCSFQEEIRKRSNHRRMKSDSFLQEMPNVTNIPHGDPMINNDQCILPISLEKEKQKNRKNLSCTNVLQSNSTKKCGIDTIDLKRNETPPVPPPRSTSRNFPSSDSEQAYERWKERLDHNSWVPHEGRSKRNYNPHFPLRQQEMSMLYPNEGKTSKDGIIFSSLVPEVKIDSKPPSNEDVGLSMWSCDIGIGAKRSPSTSWFQKTCSTPSNPKYEMVIPDHPAKSHPDLHVSNDCSSSVAESSSPLRNFSCGFERTTRNEKLAAKTDEFNRTVFRTDRNCQAIQQNHSCSKSSEDLKPCDTSSTHTGSISQSNDVSGIWKTNAHMPVPMENVPDNPTKKSTTGLVRQMQGHLSPRSYRNMLHEHDWRPSNLSGRPRSADPRSNYGVVEKLLKTYETATESALQNSKCFQDNWTKCNSDVSGGATLSQHLEMLQMEQQFQQKTAVWGGQEVKQGIDPKKITEESMSVNASHGKGFSRPARPANRRLPSRWASRSPSAPPALRRTTHNYTISLRSEALMV