Q2RQ51 AF NFT

Glucose-6-phosphate isomerase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiatrsyud7bk56uq7quazfxn3jk3e4ea7rlhlbqh47rhqgezudttj4/metadata.json
IPFS of structure file: 
bafybeiaxz5ygvtyq5jxrp6bmbbolc7r343t7vqghabymelxzfeqsrbsdhm/AF-Q2RQ51-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x9073C46348542FfE4327c3F363F9B51B22058e75
First NFT owner address (bech32): 
genesis1jpeugc6g2shluse8c0ek87d4rv3qtrn44vl0u5
Current NFT ID #139902 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
139902
Accession (UniProt):
Q2RQ51
Name::
Glucose-6-phosphate isomerase
Experimental Method:
Predicted structure
Sequence source:
RHODOSPIRILLUM RUBRUM (STRAIN ATCC 11170 / ATH 1.1.1 / DSM 467 / LMG 4362 / NCIMB 8255 / S1)

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 Q2RQ51 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q2RQ51|G6PI_RHORT Glucose-6-phosphate isomerase OS=Rhodospirillum rubrum (strain ATCC 11170 / ATH 1.1.1 / DSM 467 / LMG 4362 / NCIMB 8255 / S1) OX=269796 GN=pgi PE=3 SV=1 MPDPTTLSAWAALAAHAPTLSDQPLRVLFDADPDRFARFHLRFEDLVLDYSKNRITGETMALLADLARQSGVEARRDAMFAGEPINTTEGRAVLHVALRDPTPTPVLVDGADVKPAIAAVLAHMEAFSEAVRSGAWTGATGKAITDVVNIGIGGSDLGPVMVVEALKAYAKPGLRVHFVSNVDGTHIAETLKGLSPETTLFLVASKTFTTQETLTNAHTARDWLVGALGEPAVARHFAALSTNAKAVSAFGIDTANMFEFWDWVGGRYSLWSAIGLPIAISVGFANFRALLDGAHAMDTHFREAPIERNLPVILGLLGVWYGDFLGARAQAVLPYDQYLHRLAAYLQQADMESNGKRTTLDGKTVAYATGAVLFGEPGTNGQHSFYQLIHQGTSLIPCDFIAPAISHNPLGRHHAILLSNFLAQTEALMRGKTEAEARAELAAQGLAGEALEALLPHKVFPGNRPTNAILVKRLDPRTLGMLIALYEHKIHVQATVWNINAYDQWGVELGKQLAKAILPELEDATISPAHDSSTNGLIALYREFSAG