Q79VC4 AF NFT

Ectoine/proline transporter ProP

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigcoj2wmoaapnh2wr5k56nccvbioqtcqzujlmozlpcey64waah6a4/metadata.json
IPFS of structure file: 
bafybeigs3c2u7henli64jvp2x5diobvqunrzb2wmpdprf3ddohq3325dni/AF-Q79VC4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x88DB42AFD1c918761d553B3c6CEc7ba83c6f79bC
First NFT owner address (bech32): 
genesis13rd59t73eyv8v8248v7xemrm4q7x77du3l8xmx
Current NFT ID #310904 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
310904
Accession (UniProt):
Q79VC4
Name::
Ectoine/proline transporter ProP
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 Q79VC4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q79VC4|PROP_CORGL Ectoine/proline transporter ProP OS=Corynebacterium glutamicum (strain ATCC 13032 / DSM 20300 / BCRC 11384 / JCM 1318 / LMG 3730 / NCIMB 10025) OX=196627 GN=proP PE=1 SV=1 MSPIRSKKKIKNEPRLTVDDVNVVPPKKIRPAIKGTVVGNFMEWYDFGIYGYLTVTMTAVFTQGLPQEWQLLAVMFGFAVSYLVRPLGGLVLGPLGDKVGRQKVLYVTMAMMAVSTALIGLLPTAASIGAWALVLLYLLKMVQGFSTGGEYAGATTYVAEFAPDRRRGFFGAFLDMGSYLGFAAGASVVAITTWVTTHFYGATAMEDFGWRIPFLTAIPLGIIAVYLRTRIPETPAFENNQDEPNAVVEKDTEDPYARLGLAGVIRHHWRPLLIGIAIVAATNTAGYALTSYMPVYLEEQIGLHSASAAAVTVPILVVMSLLLPFVGMWSDRVGRKPVYATAVAATLILMVPAFLIMNTGTIGAVLIALSMVAIPTGLYVALSASALPALFPTASRFSGMGISYNISVSLFGGTTPLITQFLLQKTGLDIVPALYIMFFSAIAGVALLFMTESSQKPLLGSFPTVETKSEAVEIVKNQDEDPNIDLSHMPFPDEENVGAEKQNA