A5FG48 AF NFT

Protein adenylyltransferase SelO

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidwwvkb5m76ayoz6v2uff36x7lu3lxasycdexd4t7nkssiysu4rwi/metadata.json
IPFS of structure file: 
bafybeige2htez3w6bzohhyaqm2ttbtq3romcgvk5snszuvidpyt4xvotwq/AF-A5FG48-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x46EfCa788d03A3e879DAcDb96552AB8Bbc7e20b3
First NFT owner address (bech32): 
genesis1gmhu57ydqw37s7w6ekuk254t3w78ug9ndfc7sx
Current NFT ID #425532 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
425532
Accession (UniProt):
A5FG48
Name::
Protein adenylyltransferase SelO
Experimental Method:
Predicted structure
Sequence source:
Flavobacterium johnsoniae (strain ATCC 17061 / DSM 2064 / JCM 8514 / NBRC 14942 / NCIMB 11054 / UW101)

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 A5FG48 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A5FG48|SELO_FLAJ1 Protein adenylyltransferase SelO OS=Flavobacterium johnsoniae (strain ATCC 17061 / DSM 2064 / JCM 8514 / NBRC 14942 / NCIMB 11054 / UW101) OX=376686 GN=selO PE=3 SV=1 MKNLKINNRFTAELPADPDLTNETRQVKNTAFSYVNPTKPSNPKLIHASEETAALVGISKEEIHSEEFLNVFSGKEILPETQPYAMCYAGHQFGNWAGQLGDGRAINLTEVENNNTFYTLQLKGAGKTPYSRTADGLAVLRSSIREYLCAEAMYHLGVPTTRSLSLILSGDQVLRDILYNGNPAYEKGAVVCRVAPSFIRFGSFEMLAARNELKNLKQFVEYTIKHYFPEITGEPKEQYLQFFKKVADTTREMILHWQRVGFVHGVMNTDNMSVHGITIDYGPYGWLENYDPNWTPNTTDSQNKRYRFGNQPQVAHWNLYQLANAIYPLINETEGLEKILESFMDDFILDYKEMFLNKLGLFTSTETDNDLIDNLEAVLQLTETDMTIFFRNLSSVKKTDSVEKAIEKIQFAFYKIEEVSGEILDAWKKWFSVYLDRLNAEVLSDEVRLQKMNLINPKYVLRNYMAQLAIDAADKEDYSLVNELYTLLQKPYDEQPEYQKWFAKRPDWATSKVGCSMLSCSS