Q8NQC4 AF NFT

L-cysteine:1D-myo-inositol 2-amino-2-deoxy-alpha-D-glucopyranoside ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeia3th6tevcnqsmpwln3o2zfh4dozs7d7u6kt3yzqhpu3leac2mzty/metadata.json
IPFS of structure file: 
bafybeifwnewu3yxkpcgecqvo54yku3tfhzxua5ui3alcbdiblgwocn4tem/AF-Q8NQC4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x0D671490EE06E75975e90D7F99F73B20BE618744
First NFT owner address (bech32): 
genesis1p4n3fy8wqmn4ja0fp4lenaemyzlxrp6y5ma6w5
Current NFT ID #245217 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
245217
Accession (UniProt):
Q8NQC4
Name::
L-cysteine:1D-myo-inositol 2-amino-2-deoxy-alpha-D-glucopyranoside ligase
Experimental Method:
Predicted structure
Sequence source:
Corynebacterium glutamicum (strain ATCC 13032 / DSM 20300 / BCRC 11384 / JCM 1318 / LMG 3730 / NCIMB 10025)

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 Q8NQC4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q8NQC4|MSHC_CORGL L-cysteine:1D-myo-inositol 2-amino-2-deoxy-alpha-D-glucopyranoside ligase OS=Corynebacterium glutamicum (strain ATCC 13032 / DSM 20300 / BCRC 11384 / JCM 1318 / LMG 3730 / NCIMB 10025) OX=196627 GN=mshC PE=3 SV=1 MPLELFDTADQEVRLVETPPAGSDTPVGMYVCGITPYDSTHLGHAATYLAFDLIYRILLDNDHDVHYVQNITDVDDPLFERAARDGVDWRDLGTSQINLFRSDMEALSIIPPKDYIGAIESIDEVIEMVKTLLDEGAAYIVEDAEYPDVYASINATDKFGYESNYDAATMAEFFAERGGDPERPGKKNPMDALLWRAAREGEPSWESPFGAGRPGWHIECSAIATNRLGHSFDIQGGGSDLIFPHHEFSAAHAEAAHGVERMAKHYVHAGMISQDGVKMSKSLGNLEFVSRLTAAGHEPGAIRLGVFANHYRGNRDWNAESLATAEQRLATWREAARAATNREDAIAVVEQLRAHLSADLDTPGALAAVDNWAAGIDTTTDSKEFTEVGNIVVAAIDALLGVQL