O30565 AF NFT

Cyclomaltodextrin glucanotransferase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihgodokx6n3nlwrdypr3znu4cmdadg44lgr7dx4v7hbtuzyanptbi/metadata.json
IPFS of structure file: 
bafybeihojsgbevnkdlxwefv5zhbt72yh2iigujia77dke3fazwytq4edrq/AF-O30565-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xA40142fE4BDa34A12E7e506aD8115eEBb8b9eedb
First NFT owner address (bech32): 
genesis15sq59ljtmg62ztn72p4dsy27awutnmkm2tulpr
Current NFT ID #56850 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
56850
Accession (UniProt):
O30565
Name::
Cyclomaltodextrin glucanotransferase
Experimental Method:
Predicted structure
Sequence source:
BREVIBACILLUS BREVIS

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 O30565 research and analysis (ICN3D with VR)

FASTA sequences

>sp|O30565|CDGT_BREBE Cyclomaltodextrin glucanotransferase OS=Brevibacillus brevis OX=1393 GN=cgt PE=3 SV=1 MITPSFIISSFLSLPTVVEASVTNKVNYSKDVIYQIVTDRFSDGNPANNPSGAIFSQNCSDLHKYCGGDWQGIINKMNDGYLTDLGITALWISQPVENVYALHPSGYTSYHGYWARDYKKTNPYFGNFSDFDRLVSTAHNKGIKIIMDFTPNHSSLALETNPNYVENGALYNNGALLGNYSNDRNKLFHHNGGTDFSSYEDSIYRNLYDLADYDLNNKVVDQYLKESIKLWLIKIDGIRVDAVKHMSEGWQTSLMSDIYTYKPVFTFGEWFLGTGEVDPQNHHFANESGMSLLDFQFGQTIRSVLKDRTSNWYDFNEMIKSTEKDYDEVIDQVTFIDNHDMSRFSMVVFNFQTDIALAVLLTSRGVPTIYYGTEQYLTGGNDPDNRKPMKTFDRSTNSYKITSKLASLRQRNSALGYGNTTERWINSDVYIYERKFGNSIVLTAVNSSNRNQTISNLNTSLPQGNYTDELQQLLDGNTITVNANGSANSPQLQANSVAVWQVTKESTSPLIGHVGPMIGKTGNTVTVSGEGFGDKKGSVLFGSTSAEIVSWSNTEIQVKVPNVTAGHYNLSVVNATNTKSPAYEKFEVLSGNQVSVRFAVNNATTNSGTNVYIVGNVSELGNWDPNKAIGPMFNQVMYKYPTWYYDISVPAGKNLEYKYIKKDHNGNVTWQSGNNRTYTSPATGTDTVISNW