Q65DX4 AF NFT

ATP synthase subunit beta

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeib5h3hpmoghk63bt3rd5dtrnufnwnshkprezlgawore4vuyojjvxa/metadata.json
IPFS of structure file: 
bafybeibybonw5lwvhwbevh2klw24iz77ncpu7gyeiggurfm323i6iojaga/AF-Q65DX4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x822BfDB52f100Af7414C872a89eE1bfF1069766B
First NFT owner address (bech32): 
genesis1sg4lmdf0zq90ws2vsu4gnmsmlugxjantxz5qlu
Current NFT ID #34073 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
34073
Accession (UniProt):
Q65DX4
Name::
ATP synthase subunit beta
Experimental Method:
Predicted structure
Sequence source:
Bacillus licheniformis (strain ATCC 14580 / DSM 13 / JCM 2505 / CCUG 7422 / NBRC 12200 / NCIMB 9375 / NCTC 10341 / NRRL NRS-1264 / Gibson 46)

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 Q65DX4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q65DX4|ATPB_BACLD ATP synthase subunit beta OS=Bacillus licheniformis (strain ATCC 14580 / DSM 13 / JCM 2505 / CCUG 7422 / NBRC 12200 / NCIMB 9375 / NCTC 10341 / NRRL NRS-1264 / Gibson 46) OX=279010 GN=atpD PE=3 SV=1 MKKGRVSQVLGPVVDVRFEDGHLPEIYNAIKVTHKAQNENEVDIDLTLEVALHLGDDSVRTIAMASTDGVTRGMEAIDLGEPISVPVGNVTLGRVFNVLGENIDLDEPLPADAAKDPIHREAPKFDQLSTEVEILETGIKVVDLLAPYIKGGKIGLFGGAGVGKTVLIQELINNIAQEHGGISVFAGVGERTREGNDLYYEMKDSGVIGKTAMVFGQMNEPPGARMRVALTGLTMAEHFRDKEGQDVLFFIDNIFRFTQAGSEVSALLGRMPSAVGYQPTLATEMGQLQERITSTNVGSVTSIQAIYVPADDYTDPAPATTFAHLDATTNLERKLSEMGIYPAVDPLASTSRALSPEIVGEEHYEVARSVQQILQRYKELQDIIAMLGMDELSDEDKLVVSRARRVQFFLSQNFHVAEQFTGQKGSYVPVKETVKGFKEILEGKYDHLPEDAFRLVGRIEEVVEKAKEMGVEV