C0RM93 D-aminopeptidase MolNFT, Molecular NFT on GenesisL1

D-aminopeptidase

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeiapaxzjztf2kd6hrncbkx4hkj4jyoz55iw77hxzkz7p24ung5jysq/metadata.json

IPFS of structure file:

bafybeidkqgxxd5cbgkiebmhf527s2wzenr3uqwppdgouxunpnpx44vgaqy/AF-C0RM93-F1-model_v2.pdb

First NFT owner address (eip-55):

0xcE2eb976c31ec9e10e42B795e6729B4659076C74

First NFT owner address (bech32):

genesis1echtjakrrmy7zrjzk727vu5mgevswmr5v8dl7r

Current NFT ID #90113 owner (web3):

0xd91633319BDB0a92cbC4f08DeA734Bf74C030064

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
90113
Accession (UniProt):
C0RM93
Name::
D-aminopeptidase
Experimental Method:
Predicted structure
Sequence source:
BRUCELLA MELITENSIS BIOTYPE 2 (STRAIN ATCC 23457)

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 C0RM93 research and analysis (ICN3D with VR)

FASTA sequences

>sp|C0RM93|DAP_BRUMB D-aminopeptidase OS=Brucella melitensis biotype 2 (strain ATCC 23457) OX=546272 GN=dap PE=3 SV=1 MPNIDLPTLEAFVHAIPQNYKGPGGAVAVVRNGEIVLRHAWGFADLAARKAMTPETRMPICSVSKQFTCAVLLDCIGEPEMLDSALAAYLDQFEDGRPAVRDLCNNQSGLRDYWALTVLCGAAPEGIFLPDQAQNLLRRLKTTHFAPGTHYSYCNGNFRILADLIEQHTGRSLADLLAERIFAPAAMKTAELIPDTALFNECTGYEGDTVRGFLPAINRIHWLGDAGICASLDDMIAWEQFIDRTRHDENGLYRRLSSPQTFADGAPAPYGFGLKFEETGGKRLTGHGGALRGWRCQRWHCADERISTIVMFNFEGNASDAALKMMNAALGIPPAKPVRAQANPGWFGSWLNPETGLVLSLEDAGGGRMKARFGTGPEKMDISGENEAQSSMTTLRRDGDMIHLARKDENLHLAMHRLKGKARQDIAGRYRSDELEADLLLVSEGGAIYGAFEGFLGKSDMYPLYAAGPDVWLLPVQRSMDAPSPGEWKLVFHRDAAGRITGVTVGCWLARGVEYKRL

C0RM93 AF NFT

MOLNFT AF v1

NFT data

MOLNFT C0RM93 research and analysis (ICN3D with VR)

FASTA sequences

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