E0SAL0 AF NFT

Putative type VI secretion system protein VgrGA

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiffwjblhwrs5zvpwebvrxeu2t3pczsghsl72vrko23uknoygieamm/metadata.json
IPFS of structure file: 
bafybeieqqk7hvqml3c3qxd36h4pvwgpdvw4djcoehljejf4g6ptu4f6qyq/AF-E0SAL0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7BeA38dAb4565F0858708331148660F2A14d4201
First NFT owner address (bech32): 
genesis1004r3k452e0sskrssvc3fpnq72s56sspespdx4
Current NFT ID #496269 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
496269
Accession (UniProt):
E0SAL0
Name::
Putative type VI secretion system protein VgrGA
Experimental Method:
Predicted structure
Sequence source:
DICKEYA DADANTII (STRAIN 3937)

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 E0SAL0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|E0SAL0|VGRGA_DICD3 Putative type VI secretion system protein VgrGA OS=Dickeya dadantii (strain 3937) OX=198628 GN=vgrGA PE=3 SV=1 MANSTGLQFTVKVGALPDTTFAVVDFELSEALNQPFALSLNLASSLPGIDFGAVLDQPCELLVWYEGELQRRVSGIVSRFAQGDTGFRRTRYQAEVRPALWRLGLRTNARIFQTQKPDAIIGTLLEEAGITDFAFALRHEHAVREYCVQYRESDLAFINRLAAEEGLFYFHEFEAGKHRVVFADDAGALTKGPELFFNLATQGLSEGAYVRRFRYAEAVSTAEVALKDYSFKTPAYGLLHNKMSSELDHQRETYQHFDYPGRFKQDPSGKAFTGYRLDALRAGAMTGEGESNAAELMPGSSFTLTEHPNPAFNLAWQVVAVTHSGQQPQALEEESGGEPTTLSNSFEVVKGTTTWRAAMPYKPMVDGPQIATVVGPAGEEIYCDEFGRIKLQFPWDRYGASDDQSSCWVRVSQGWAGGQYGLIAIPRIGHEVVVSFLEGDPDQPIVTGRTFHATNPSPYPLPASKTRTSLRTSTHKGAGFNELRFEDQAGQEEVFIHAQKDMNTVVLNNRSTSVNASHTENVGGDQTVVVQHNQTVSVKENQVTEIQGEQTVAVTQNRNTTVNDNESLQVKNNIAIQSQSGDILIATAGGFIAIDKDGNISITGKGLVLNGTRIDLN