Q99KG7 AF NFT

Hermansky-Pudlak syndrome 4 protein homolog

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiautb43huvo7nltotqyk6id4ucy6ffrxipazuzicy2pk6g3ib3vxy/metadata.json
IPFS of structure file: 
bafybeicvrziaco43nzdjms2ixrnupt4anlqzlqn5dyfzdkvve4po52gu7m/AF-Q99KG7-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x3d944850D26fB5c0d71746C4caCa5CD27831DE39
First NFT owner address (bech32): 
genesis18k2ys5xjd76up4chgmzv4jju6furrh3eljrnzv
Current NFT ID #176599 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
176599
Accession (UniProt):
Q99KG7
Name::
Hermansky-Pudlak syndrome 4 protein homolog
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 Q99KG7 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q99KG7|HPS4_MOUSE Hermansky-Pudlak syndrome 4 protein homolog OS=Mus musculus OX=10090 GN=Hps4 PE=1 SV=2 MATTTPPETKSAAWWNYFFLYDGSKVKGEGDPTRAGICYFYPPQTLLDQQELLCGQLAGVVRCLWDLSGTPPMLIRMRNLKFAIRADGDYLWALGCGVEISDASCRQFLDQLIGFFHFYMGPVSLAYKSHPQEELSLQWDTSITQVLRSTSESHRIFNALWNLDRTKVEPLLLLKAALILQTCQRSPHVLAGCILYKGLIVNSQLLPSLTAKVLLHQTVPADQRLPGAGAAPQETGAALPPDVQITSVFLSEEEVASLHEFPVEHETRLQGSSVQYPPWDQSSPTQAEDAWASAAIPEPTPHDGACPSGSGADERLPRLEQECAGPTGLCTTACGQGSGLSSRLQKELCLSREELDSSEMHVSEAQEAFPPLPALGDLETLHSSHSAPTLPEDTAICSCLHPCPLERLPESGRLGQLADLPLTNGQTQVPGTDPLPSSMPVALPPQHPVGVEPSVEPYGNGAQESHSALPRSSRSPDSPGPSPSADRTGFKPSPSGRHAGLVPMNLYTHSVNGLVLSLLAEETLLSDTAAIEEVYHSSLASLNGLEVHLKETLPRDEASLTSSTYNFLHYDRIQSVLSANLPLVTAPQDRRFLQAVNLMHSDFALLPMLYEMTIRNASTAVYACSSPAQETYFQQLAPTARSSGFPNPQDCAFSLAGKAKQKLLKHGVNLL