Q8ZIG8 2-isopropylmalate synthase MolNFT, Molecular NFT on GenesisL1

2-isopropylmalate synthase

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeiacdcpd43cby4cmanyxbcae6x3ezsb7q4jyjmhwwnvyiveqv3nzi4/metadata.json

IPFS of structure file:

bafybeiggkwdhpjlmsfjnewtnv6cpbzd74qlfkgxaa367redok7fvgin3am/AF-Q8ZIG8-F1-model_v2.pdb

First NFT owner address (eip-55):

0x41CeC9196Eb401e6912C97187dA1a9626eD4e80D

First NFT owner address (bech32):

genesis1g88vjxtwksq7dyfvjuv8mgdfvfhdf6qdw7r7r4

Current NFT ID #210437 owner (web3):

0x463a972e031C685D1BD2C43E9dFA3Ed66670D0bc

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
210437
Accession (UniProt):
Q8ZIG8
Name::
2-isopropylmalate synthase
Experimental Method:
Predicted structure
Sequence source:
YERSINIA PESTIS

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 Q8ZIG8 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q8ZIG8|LEU1_YERPE 2-isopropylmalate synthase OS=Yersinia pestis OX=632 GN=leuA PE=3 SV=1 MSQQVIIFDTTLRDGEQALQASLSVKEKLQIALALERMGVDIMEVGFPVSSPGDFESVRTIAQQVKNSRVCALARCVDKDIDVAAEALRIAEAFRIHVFLATSTLHIESKLKRSFDDVLAMAVHSVKRARNYTDDVEFSCEDAGRTPIDNLCRVVEAAITAGATTINIPDTVGYTTPYQFGGIITDLYERVPNIDKAIISVHCHDDLGMSVANSITAVQAGARQVEGTINGLGERAGNCSLEEVIMAIKVRHEMLGVHTNINHQEIYRTSQLVSKICNMPIPGNKAIVGSNAFAHSSGIHQDGVLKNRENYEIMTPESIGLKEVQLNLTSRSGRAAVKHRMEEMGYQDKDYNLDSLYDAFLKLADKKGQVFDYDLEALAFINKQQEEPEYYRLDYFSVQSGSSVMATASVKLVCGEEIKSEAATGNGPVDAVYQAINRITDYPIELVKYQLSAKGQGKDALGQVDIVVDHKGRRFHGVGLATDIVESSAKALVHVLNNIWRAHQVEKEKQRLQQNNQEMV

Q8ZIG8 AF NFT

MOLNFT AF v1

NFT data

MOLNFT Q8ZIG8 research and analysis (ICN3D with VR)

FASTA sequences

We use cookies on this site to enhance your user experience