B7GQG0 AF NFT

tRNA-2-methylthio-N(6)-dimethylallyladenosine synthase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibgrlhkmtqinbpfbiyl2bzvezfq7wsz6bc5vvr6rpfvwlraxwckp4/metadata.json
IPFS of structure file: 
bafybeiglazhvsjnphc6knte7afofro3qwnmnubkjhohsguqzf6567rjuuq/AF-B7GQG0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x38EB5C873A97281Ed18Da8DA93921002c6195C4D
First NFT owner address (bech32): 
genesis18r44epe6ju5pa5vd4rdf8yssqtrpjhzdgeadeq
Current NFT ID #234572 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
234572
Accession (UniProt):
B7GQG0
Name::
tRNA-2-methylthio-N(6)-dimethylallyladenosine synthase
Experimental Method:
Predicted structure
Sequence source:
BIFIDOBACTERIUM LONGUM SUBSP. INFANTIS (STRAIN ATCC 15697 / DSM 20088 / JCM 1222 / NCTC 11817 / S12)

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 B7GQG0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B7GQG0|MIAB_BIFLS tRNA-2-methylthio-N(6)-dimethylallyladenosine synthase OS=Bifidobacterium longum subsp. infantis (strain ATCC 15697 / DSM 20088 / JCM 1222 / NCTC 11817 / S12) OX=391904 GN=miaB PE=3 SV=1 MNEDMMTEAERASIAADGTDSLLGERGKGVFHIHTLGCQMNVHDSERIAGVLEANGYVPATEDQINDNDLDLLVLNTCAVRENAAERMYGTIGRFNRVKLVRPNLQIAVGGCMAQLDRKKIADTAPWVSAVFGTKNIEDLPKLLDQNRATGKAQVQVTEQLRQFPSQLPAARASRISSWVAISVGCNNTCTFCIVPTTRGKEKDRRPGDILDEIRQCVAGGAKEVTLLGQNVNSFGYGIGDRYAFSKLLRACGTIDGLERVRFTSPHPAAFTDDVIAAMAETPNIMHQLHFPLQSGSDRILRAMRRSYRSAKFLDILGRIREAMPDAQISTDIIVGFPGETEEDFQQTMDVVRQARFSSAFTFIYSPRPGTPAAAMEQIPRDVVQDRFDRLVALQEQITEENLATFEGRDVEVMITGKLGKKDTDTHRVTGREKTGVLVHIGVPEGEPVPEIGDFVTVTVTHAGRHNLLADPDVAAGQTYSVRH