Q6CQH2 AF NFT

tRNA (guanine-N(7)-)-methyltransferase non-catalytic subunit TRM82

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeib6psdt6ucwny53advcvemgws2laohzzv6ynbpklwtvory2d3z5nm/metadata.json
IPFS of structure file: 
bafybeic7pi46rdth6lmoa432yiq5hmskhzcu772wwjmqrhz5isnelpa5qy/AF-Q6CQH2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7EAF4972fBCA2131d603a72C142a37eC45Edd45A
First NFT owner address (bech32): 
genesis106h5juhmegsnr4sr5ukpg23ha3z7m4z64frpwd
Current NFT ID #473751 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
473751
Accession (UniProt):
Q6CQH2
Name::
tRNA (guanine-N(7)-)-methyltransferase non-catalytic subunit TRM82
Experimental Method:
Predicted structure
Sequence source:
KLUYVEROMYCES LACTIS (STRAIN ATCC 8585 / CBS 2359 / DSM 70799 / NBRC 1267 / NRRL Y-1140 / WM37)

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 Q6CQH2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q6CQH2|TRM82_KLULA tRNA (guanine-N(7)-)-methyltransferase non-catalytic subunit TRM82 OS=Kluyveromyces lactis (strain ATCC 8585 / CBS 2359 / DSM 70799 / NBRC 1267 / NRRL Y-1140 / WM37) OX=284590 GN=TRM82 PE=3 SV=1 MLHPFQSVLLNRDGSLLFCVVKNEIKAFKVEGNGYVLRGEWVDDLDNTPLIKEKVLKEQARQLIENASKKLKTNDGEPVAQPKKQAKVPKPGPGAPPVYQYIRNLALSRDGKLLLACTDSDKAAVIFNIDLDDKDNIFKLIKRQPYPKRPNAITTSVDDKDLILADKFGDVYSMPIQNDVITSINAEKAPILGHVSMLTDVNMLTDSEGKQYIVTADRDEHIRISHYPQSFIVDKWLFGHEEFVSTICIPEWSDKLLFSAGGDKFVFSWNWKTGALLFKFDYTDLIQKYLTSDHLAPERFQNEKGDVIEYSVAKIVTLKDVPYIAFFVEATKVLFVLKVDEKSGALSLHQTLEFDEKIVSLTSALDVNTLCISLDNRDNQDCDLVKLLLLEGDVFIEQKDTNSQLMNTIRSTLKSDLIANVEAGDVYPLYHNASLRKHGEHFS