Q21270 AF NFT

Conserved oligomeric Golgi complex subunit 6

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiejbbuqa2vxhofypjla66kj3af36zc3zn4aoj6a5xgtanbcta5oji/metadata.json
IPFS of structure file: 
bafybeigfjezhbeeg3bgfgrfocfusimpkkkzbe7ykgdwvbmjtivrrqc4uaq/AF-Q21270-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xc5ddbFd578Ee8bf0Bb22bF47F38D91D88bE1AdDf
First NFT owner address (bech32): 
genesis1chwml4tca69lpwezharl8rv3mz97rtwlgklhem
Current NFT ID #72063 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
72063
Accession (UniProt):
Q21270
Name::
Conserved oligomeric Golgi complex subunit 6
Experimental Method:
Predicted structure
Sequence source:
CAENORHABDITIS ELEGANS

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 Q21270 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q21270|COG6_CAEEL Conserved oligomeric Golgi complex subunit 6 OS=Caenorhabditis elegans OX=6239 GN=cogc-6 PE=3 SV=1 MSVIDKTSSAVNPLREKVTTACAKKLYNDKDCIKIADFITPLVEDMNLDSNVDRKLHNKLERYELRLNKEYLSEFEKINNIVQKFDELCVKMNSTCTNLSKQMETVKFKSVDLVQKTASLKEKKASIESRCNMINEFLENYSLSSEELRELDECEQSGHLSEFFFKVLERCHEIRENCRNMVQEQGHLAAFEVMEKMQKIDERSHAIICNNLKREFQNLTVDSHQKKQILSKAFKIISQNDAVFQLAIDQYISSRSQELLNQFVEINKMAVQMPEGLAEPLKAVGDMLTSIHELTEQEKQLFSSICSAENLPIVLDECLKSLTSPFKIRVEQLLSTEKNAITIFKMGNILIFYANKFETLIRKDSYFTIMLADLVKTVRQVCIAGINHHVDGLMRKMTSPHYDLLPVPEVRQCLSLYHGLISIAVKTGDLNLLLEPERIYEYVLEPLIQTVQLSATRLKSDIEVSVFTINCLTVIRSAISEISAFKKKIEMIDAMIEGNSDVLVSVQVSEMLEKSGILELYQKFNAVNPAEKKPLSTLPGLESTTVGEAIVMFTQYLHNHASSDHTYDIDQQILASEERQRIRERNTLEFLKVYKMIVDRLGNPTNGYENLHYLPIEHVESVLKFEKEKENTPSSNESESLA