Q92J97 AF NFT

Succinate dehydrogenase flavoprotein subunit

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiftzi56tys5vfsqi2yljlgisxh62jgwh6vnwtaumeetnr5fezdd3m/metadata.json
IPFS of structure file: 
bafybeihzicsn6grok6fjwbbjuf2mm4xlbu5xt6fjnqxtqyqhvgcg2w4a6i/AF-Q92J97-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xeDA256c6330964f3de2563F938CD47b439cE34A3
First NFT owner address (bech32): 
genesis1ak39d33np9j08h39v0un3n28ksuuud9rkx3mp5
Current NFT ID #422696 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
422696
Accession (UniProt):
Q92J97
Name::
Succinate dehydrogenase flavoprotein subunit
Experimental Method:
Predicted structure
Sequence source:
RICKETTSIA CONORII (STRAIN ATCC VR-613 / MALISH 7)

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 Q92J97 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q92J97|SDHA_RICCN Succinate dehydrogenase flavoprotein subunit OS=Rickettsia conorii (strain ATCC VR-613 / Malish 7) OX=272944 GN=sdhA PE=3 SV=1 MTKAYNIIHHKFDVVVVGAGGAGLRSAFGMAKEGLNTACITKLFPTRSHTVAAQGGISAALGNMGEDDWRWHMYDTVKGSDWLGDQDAIEYMCKNAPDAILELEHYGVPFSRTEEGKIYQRPFGGMTTEYGKGKAAQRTCAAADRTGHAILHTLYQQSLKHKVQFFVEYFAIDLLMEDGECRGVVAWNLDDGSLHCFRAHNVVLATGGYGRAYFSATSAHTCTGDGGGMAIRAGLPLQDMEFVQFHPTGIYSAGCLITEGARGEGGYLVNANGERFMERYAPAAKDLASRDVVSRAMTIEIREGRGVGEHKDHVFLHLNHLSPEILHSRLPGISETAKIFAGVDVTKEPIPVLPTVHYNMGGIPTNYHGQVIIKDGKNHNSVVKGLMAIGEAACVSVHGANRLGSNSLLDLVVFGRSSALKAAELIKPASPHRSIKEESLEKIINRFDKVRHANGNILVAELRLKMQRTMQSHASVFRTQEVLDEGAGMISEIRSGYKDIKINDKSLIWNSDLVEALELDNLLDQALVTVYSAAARKESRGAHAREDYPDRNDEDWMKHTLSSIDEAGKVVLDYKPVTLTTLTDEVTAVPPVKRVY