A1RQB0 ATP synthase subunit beta MolNFT, Molecular NFT on GenesisL1

ATP synthase subunit beta

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeigx5siplbzfuquofzignwvno7wgshsc5kpbx2cbh3666mzskhmc5i/metadata.json

IPFS of structure file:

bafybeig6jng5zunxwwsc6bpnuilv2gyex24pbzjct7ikliqla3ylnxeexe/AF-A1RQB0-F1-model_v2.pdb

First NFT owner address (eip-55):

0xa4785222Bbe47502ED0a362Ddab993F3F3B268aC

First NFT owner address (bech32):

genesis153u9yg4mu36s9mg2xcka4wvn70emy69v6rl83x

Current NFT ID #34736 owner (web3):

0xa4785222Bbe47502ED0a362Ddab993F3F3B268aC

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
34736
Accession (UniProt):
A1RQB0
Name::
ATP synthase subunit beta
Experimental Method:
Predicted structure
Sequence source:
Shewanella sp. (strain W3-18-1)

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 A1RQB0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A1RQB0|ATPB_SHESW ATP synthase subunit beta OS=Shewanella sp. (strain W3-18-1) OX=351745 GN=atpD PE=3 SV=1 MSTGTVVQVIGAVVDVEFPQDAVPQVYDALKITGEGACNGLVLEVQQQLGGGVVRTIAMGSSDGLRRGLEVVNSGSPISVPVGTATLGRIMNVLGEPIDEAGPIGEEERYVIHRAAPSYEDQSNTTELLETGIKVIDLVCPFAKGGKVGLFGGAGVGKTVNMMELINNIAKAHSGLSVFAGVGERTREGNDFYYEMKDSGVLDKVAMVYGQMNEPPGNRLRVALSGLTMAEKFRDEGRDVLLFVDNIYRYTLAGTEVSALLGRMPSAVGYQPTLAEEMGVLQERITSTKTGSITSVQAVYVPADDLTDPSPATTFAHLDATVVLSRQIASLGIYPAVDPLDSTSRQLDPLVVGQEHYDVANGVQTVLQRYKELKDIIAILGMDELSDDDKTTVFRARKIERFLSQPFFVAEVFTGSPGKYVSLKDTIRGFKGILNGEFDHLPEQAFYMVGSIDEVIEKANKKK

A1RQB0 AF NFT

MOLNFT AF v1

NFT data

MOLNFT A1RQB0 research and analysis (ICN3D with VR)

FASTA sequences

We use cookies on this site to enhance your user experience