Q8AA22 AF NFT

Uncharacterized RNA methyltransferase BT_0643

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeih4zx2aeqrrkcc7rp7l4r5glwarpmq3wdhequof2mpfsixlg7tsuq/metadata.json
IPFS of structure file: 
bafybeib5pvkuwh3o72qh44khxuds7yis4mhtuz7obdjtw7axxogta2ol44/AF-Q8AA22-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x30d872b97D5A8BBB2071246F96F833576bC307D1
First NFT owner address (bech32): 
genesis1xrv89wtat29mkgr3y3hed7pn2a4uxp73ejvvak
Current NFT ID #520452 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
520452
Accession (UniProt):
Q8AA22
Name::
Uncharacterized RNA methyltransferase BT_0643
Experimental Method:
Predicted structure
Sequence source:
Bacteroides thetaiotaomicron (strain ATCC 29148 / DSM 2079 / JCM 5827 / CCUG 10774 / NCTC 10582 / VPI-5482 / E50)

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 Q8AA22 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q8AA22|Y643_BACTN Uncharacterized RNA methyltransferase BT_0643 OS=Bacteroides thetaiotaomicron (strain ATCC 29148 / DSM 2079 / JCM 5827 / CCUG 10774 / NCTC 10582 / VPI-5482 / E50) OX=226186 GN=BT_0643 PE=3 SV=1 MAAEGKAIAKVNDLVIFVPYVVPGDVVDLQIKRKKNKYAEAEAVKFHELSPVRAVPFCQHYGVCGGCKWQVLPYSEQIRYKQKQVEDNLRRIGKIELPEISPILGSAKTEFYRNKLEFTFSNKRWLTNDEVRQDVKYDQMNAVGFHIPGAFDKVLAIEKCWLQDDISNRIRNAVRDYAYEHDYSFINLRTQEGMLRNLIIRTSSTGELMVIVICKITEDHEMELFKQLLQFIADSFPEITSLLYIINNKCNDTINDLDVHVFKGKDHMFEEMEGLRFKVGPKSFYQTNSEQAYNLYKIAREFAGLTGKELVYDLYTGTGTIANFVSRQARQVIGIEYVPEAIEDAKVNAEINEIKNALFYAGDMKDMLTQEFINQHGRPDVIITDPPRAGMHQDVVDVILFAEPKRIVYVSCNPATQARDLQLLDGKYKVKAVQPVDMFPHTHHVENVVLLELR