B2IIK5 AF NFT

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

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiezhunzpfinnj4c5x2mzl7wo4s3lrtehzf2e4yyqbtwtpfm32i7ei/metadata.json
IPFS of structure file: 
bafybeic6zpp2x6dzmiqvomn5mva77xuohvj7bkjckk6gzu4lwuzx6owhza/AF-B2IIK5-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x9073C46348542FfE4327c3F363F9B51B22058e75
First NFT owner address (bech32): 
genesis1jpeugc6g2shluse8c0ek87d4rv3qtrn44vl0u5
Current NFT ID #234568 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
234568
Accession (UniProt):
B2IIK5
Name::
tRNA-2-methylthio-N(6)-dimethylallyladenosine synthase
Experimental Method:
Predicted structure
Sequence source:
Beijerinckia indica subsp. indica (strain ATCC 9039 / DSM 1715 / NCIMB 8712)

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 B2IIK5 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B2IIK5|MIAB_BEII9 tRNA-2-methylthio-N(6)-dimethylallyladenosine synthase OS=Beijerinckia indica subsp. indica (strain ATCC 9039 / DSM 1715 / NCIMB 8712) OX=395963 GN=miaB PE=3 SV=1 MSGFNDSPVPESAEKADGLLSQERGTQDPLVNTRKLFVKSYGCQMNVYDAERMADLLAPEGYAETSAPEDADLVILNTCHIREHAAEKVFSELGKLRLLKAEQQAAGRPVKIVVAGCVAQAEGEEILRRQKAVDLVVGPQSYHRLPDLLRRVAHTPGLVDTEFPAEDKFDHLVAPQPEKIAERGVGAFVTVQEGCDKFCSFCVVPYTRGAETSRPVEAILAEVETLIASGVREVTLIGQNVNAYHGFDAMTGAPASLASLMARVAAMPGLLRIRYTTSHPNDMGEDLIAAHRDIPALMPFLHLPVQSGSDKILAAMNRRHKAGDYLELIASIRAARPDIALSSDFIVGFPGETEADFEATLALIEQVGFASAFSFKYSQRPGTPGADRPDQIDEDVKAQRLARLQALLEEQRQAFNKAMIGRVLPVLFEKPGRHPGQIAGKTPYLQALYAEGDKALIGTVQPVEILEAGPNSFHGRLLARETGQESAQGQESAQGMERMEQNARAWEVPV