Q0BQR6 AF NFT

Dihydroxy-acid dehydratase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiaxrpjdcusllru7fnhjacdggnj5unmnvb3t6ngzji3mxvrlcmfz34/metadata.json
IPFS of structure file: 
bafybeic3ysvx3zjhrp3a3cyuzf6xrftyfqxqbkcg22qpzyxdccrdby73x4/AF-Q0BQR6-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xa0b0c5caDD2aa61Cd32a103C8481800e4501Bfda
First NFT owner address (bech32): 
genesis15zcvtjka92npe5e2zq7gfqvqpezsr076tmjg9e
Current NFT ID #189128 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
189128
Accession (UniProt):
Q0BQR6
Name::
Dihydroxy-acid dehydratase
Experimental Method:
Predicted structure
Sequence source:
Granulibacter bethesdensis (strain ATCC BAA-1260 / CGDNIH1)

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 Q0BQR6 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q0BQR6|ILVD_GRABC Dihydroxy-acid dehydratase OS=Granulibacter bethesdensis (strain ATCC BAA-1260 / CGDNIH1) OX=391165 GN=ilvD PE=3 SV=1 MPQYRSRTTTHGRNMAGARGLWRATGMKDGDFGKPIIAVVNSFTQFVPGHVHLKDLGQLVAREIEAAGGVAKEFNTIAVDDGIAMGHDGMLYSLPSRELIADSVEYMVNAHCADAMVCISNCDKITPGMLMAAMRLNIPAVFVSGGPMEAGKTVVKGATRALDLVDAMVVAADESYTDEEVQAVERSACPTCGSCSGMFTANSMNCLTEALGLSLPGNGSVLATHADREKLFREAGHLIVDLARRWYEQDDVSATPRGIATHAAFENAMSLDIAMGGSTNTVLHLLAAAQEAGVDFTMADIDRLSRRVPCLCKVAPAKSDVHMEDVHRAGGIMAILGELERAGLLDASRPTVHAPTLKDALERWDIGRTSSEEVRTFFRAAPGGVPTQVAFSQSARWDSVDEDRQKGVIRSTEHPFSHDGGLAVLFGNLAPEGCIVKTAGVDESILTFRGTARVYESQDAAVSGILGGQVVAGDVVVIRYEGPKGGPGMQEMLYPTSYLKSKGLGKLCALVTDGRFSGGTSGLSIGHVSPEAAEGGLIALVETGDPVLIDIPNRIISIALPDEVLAARRTAMEAKGEAAWKPAERQRKVSPALRAYAAMTTNAARGAVRDVSQVERKR