A0R635 AF NFT

Putative Rieske 2Fe-2S iron-sulfur protein MSMEG_6410/MSMEI_6242

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeicrx74cg3uxblavalzwscgb2mnzos57kgf2cyvzeka7dputre6gh4/metadata.json
IPFS of structure file: 
bafybeicj6torpdxkypwcfgwfzsoblmldmubqohsptiywgughdppypnak6e/AF-A0R635-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7012c0b45c68a2c067644b9d3e5DDa06892c6957
First NFT owner address (bech32): 
genesis1wqfvpdzudz3vqemyfwwnuhw6q6yjc62hg2ks0z
Current NFT ID #520436 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
520436
Accession (UniProt):
A0R635
Name::
Putative Rieske 2Fe-2S iron-sulfur protein MSMEG_6410/MSMEI_6242
Experimental Method:
Predicted structure
Sequence source:
MYCOLICIBACTERIUM SMEGMATIS (STRAIN ATCC 700084 / MC(2)155)

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 A0R635 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A0R635|Y6410_MYCS2 Putative Rieske 2Fe-2S iron-sulfur protein MSMEG_6410/MSMEI_6242 OS=Mycolicibacterium smegmatis (strain ATCC 700084 / mc(2)155) OX=246196 GN=MSMEG_6410 PE=1 SV=1 MQVTSVGHAGFLIESRAGSILCDPWVNPAYFASWFPFPDNSQLDWDALGDVDYLYVSHLHKDHFDPEHLRRYVNKDAVVLLPDYPVPDLRRELEKLGFHNFFETTDSVKHTVSGPKGDLDVMIIALRAPADGPIGDSGLVVSDRVTTVFNMNDARPVDLDVLHTDFGQIDVHMLQYSGAIWYPMVYDMPARAKEAFGIQKRQRQMDRCRQYIAQVGATWVVPSAGPPCFLDPELRDLNDDHGDPANIFPDQMVFLEQLRIHGHDGGLLMIPGSTADFTGSTLNSLTHPVDDPESIFTTGKAAYIEDYAQRMAPVLAAEKARWAPSAGEPMLEALRALFEPIMTQTDQICDGIGYPVELRLTGRDHNETVVLDFPKRVVREPIPDEKFRYGFEIPAALVRTVLRDEEPDWVNTIFLSTRFRAWRVGGYNEYLYTFFKCLTDERIAYADGWFAEAHDDSSSITLDGFQIQRRCPHLKADLSKFGVVEGNTLTCNLHGWQWNLENGRCLTTKGHELRCQKL