Q6PCG6 AF NFT

Vezatin

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigrd2ja2ebl5cjpmhfq7aoxwf3csactmkzuvyavmwjpp3o4l7kcga/metadata.json
IPFS of structure file: 
bafybeigsndbk7itumrkf2g7vhxf6etuvxjot7a522plxmmjn4shtila5ge/AF-Q6PCG6-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x309D94817aCF44c169EAF3731054957434d07b89
First NFT owner address (bech32): 
genesis1xzwefqt6eazvz6027de3q4y4ws6dq7ufdr67d3
Current NFT ID #496174 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
496174
Accession (UniProt):
Q6PCG6
Name::
Vezatin
Experimental Method:
Predicted structure
Sequence source:
XENOPUS LAEVIS

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 Q6PCG6 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q6PCG6|VEZA_XENLA Vezatin OS=Xenopus laevis OX=8355 GN=vezt PE=2 SV=1 MTAEFDEEVVFENSPLFQYLQDLGHTDFEICPLSKEEERLAENGQGKQDVHTTEKKSIISRTVEFLKSWSPFLSKKKKDEKIHLLEIGFRLESLRTILQQEVLIQEDVELIELLDPGILSAGQTQNQQNDHLPTLWSIATPNIWETSILFVFLSAVAAFQSWSISSSLIWGPSLILFAAFTVLKTLHTWRSARLRIILRKYCTQVEGTVSNSRAFTNLVRKALRLIQETEVISRGFTLVSAACPYGKAGQHASQHLLGLRKAVYRTVRTNFRISRLATLYMLKHYPLNSEIDNVTNYICVVPLKDLGLGLCEEHVSEEDAHNLTDAFSLPALKVLFQLWIGQSSEFFRRLALLLSPENASQGPSTSPEQLPHFIWSDVVQDLPHTQAACMAELKRSYEFYRYFETQHQSGLERTAKRKEVGELNNLHGAVRSLQLHLKALLNEVIVLEDELDKLSSCKEMQAVTPEASLMLEEKLRIIQPHVQASNTCWEEALCQVERMVRKPTTKKDTGKYSCENLNYPVVSNVPPAMRIEDRDPVPEEQILEAYVEEAVTDQEFNSEEIYLFSPEERERQKREREESRRVLQELKAVLGLKASEAERQKWKQLLFSEHAVITPLLPEEPVGHFEPLLSIYPEEPHKNLGFYGEIPSEINGTEHVKDAPIQVDHGNMNHEDEAKICPVSEEVEPASCKEEEDETPCPAPRTVLPPAIKERLARIHQSSDLNFTSGLATQVAARSLTFTFLQEQTFGDEWDDDDDNEDHDHDKERNNDSSQLEG