Q9HW09 2-dehydropantoate 2-reductase MolNFT, Molecular NFT on GenesisL1

2-dehydropantoate 2-reductase

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeiaccklcoqnshba4blolim2llc7kwrwlr4jlrsizhoaq7wickvborm/metadata.json

IPFS of structure file:

bafybeibscjxdk7cytw52yibf5oh6z2r2662yqgda2nx6zauavejwusotme/AF-Q9HW09-F1-model_v2.pdb

First NFT owner address (eip-55):

0xCDe39d37AEBb0A179feeF79ac73A0E0077BD5055

First NFT owner address (bech32):

genesis1eh3e6dawhv9p08lw77dvwwswqpmm65z4vnrxh9

Current NFT ID #288025 owner (web3):

0xD3703574058462cb4babd62a0Dc3a050fA4a6657

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
288025
Accession (UniProt):
Q9HW09
Name::
2-dehydropantoate 2-reductase
Experimental Method:
Predicted structure
Sequence source:
PSEUDOMONAS AERUGINOSA (STRAIN ATCC 15692 / DSM 22644 / CIP 104116 / JCM 14847 / LMG 12228 / 1C / PRS 101 / PAO1)

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 Q9HW09 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9HW09|PANE_PSEAE 2-dehydropantoate 2-reductase OS=Pseudomonas aeruginosa (strain ATCC 15692 / DSM 22644 / CIP 104116 / JCM 14847 / LMG 12228 / 1C / PRS 101 / PAO1) OX=208964 GN=panE PE=1 SV=1 MTWHILGAGSLGSLWAARLGRAGLPVRLILRDRQRLRRYQQAGGLSLVEDGQASLYPIAAETPDGGQPIQRLLLACKAYDAEEAASSVAHRLAGNAELLLLQNGLGSQQAVAARLPRSRCLFASSTEGAFRDGDFRVVFAGRGHTWLGDPRDTNAPAWLTQLSQAGIPHSWSDDILERLWRKLALNCAINPLTVLHDCRNGGLRQHPEEIAALCDELGQLLHASGYDAAARSLLEDVRAVIDATAANYSSMHQDVTRGRRTEIGYLLGYACQHGQRLGLPLPRLGTLLARLQAHLRQRGLPDR

Q9HW09 AF NFT

MOLNFT AF v1

NFT data

MOLNFT Q9HW09 research and analysis (ICN3D with VR)

FASTA sequences

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