A0KPL4 AF NFT

Bifunctional protein HldE

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigx5i6jpxk6bvoy7oju3ej6chpf7dehucbt5b3aq22no4ila3xsie/metadata.json
IPFS of structure file: 
bafybeigpgupdawrbhmg7znzrj4ovjxwqb6awdyi5fsz3tqri3gnwtmnb4q/AF-A0KPL4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x71112d4fF7ebb3b617963c05f052289e073082FD
First NFT owner address (bech32): 
genesis1wygj6nlhawemv9uk8szlq53gncrnpqha56an79
Current NFT ID #174280 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
174280
Accession (UniProt):
A0KPL4
Name::
Bifunctional protein HldE
Experimental Method:
Predicted structure
Sequence source:
Aeromonas hydrophila subsp. hydrophila (strain ATCC 7966 / DSM 30187 / BCRC 13018 / CCUG 14551 / JCM 1027 / KCTC 2358 / NCIMB 9240 / NCTC 8049)

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 A0KPL4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A0KPL4|HLDE_AERHH Bifunctional protein HldE OS=Aeromonas hydrophila subsp. hydrophila (strain ATCC 7966 / DSM 30187 / BCRC 13018 / CCUG 14551 / JCM 1027 / KCTC 2358 / NCIMB 9240 / NCTC 8049) OX=380703 GN=hldE PE=3 SV=1 MKITLPEFEKARVLVVGDVMLDRYWHGPTGRISPEAPVPVVKVEHIEERPGGAANVALNSAALGAHAVLLGLTGQDEAADALAGQMAGVKVACDFVRLADYPTITKLRVLSRNQQLLRLDFEEAFHDVDSTLLMGKVEQALPHSDVMILSDYGKGALNDVPSMIQRARAAGIPVLVDPKGTDFEKYRGATLLTPNMSEFEAVVGKVKSEEELVAKGLELVKRFELEALLVTRSENGMTLIREGQPELHLPAQAHEVYDVTGAGDTVISTLATSLAAGKSLDEACALANTAAGIVVGKLGTSTVSPVELANALYTEQETGFGVMSEAQLKIAVQAARLRGEKVVMTNGCFDILHAGHVSYLANAGKLGDRLIVAVNTDESVRRLKGPGRPVNPTERRMAVLAALGAVDWVVPFAEDTPQRLIAEVLPDLLVKGGDYKPEEIAGYAEVTANGGEVRVLNFEDGCSTSDIIKTIRERG