Q5ZSA7 D-alanine--D-alanine ligase MolNFT, Molecular NFT on GenesisL1

D-alanine--D-alanine ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeiaohbcxritgcg7tmc73qeadvg6m7bdzfnc4vuklvyeb5gaqvffiry/metadata.json

IPFS of structure file:

bafybeico5qf3bcgg5o2pwrdd4vyh5q2olpsw7wovzdnww6hxuw2h5eovlu/AF-Q5ZSA7-F1-model_v2.pdb

First NFT owner address (eip-55):

0xBCB99685929aa6d5A6201026C8CEC007c0951315

First NFT owner address (bech32):

genesis1hjuedpvjn2ndtf3qzqnv3nkqqlqf2yc438xzsa

Current NFT ID #93040 owner (web3):

0xF435Cc7528760B6B8D880Df3befF1C3095f62B98

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
93040
Accession (UniProt):
Q5ZSA7
Name::
D-alanine--D-alanine ligase
Experimental Method:
Predicted structure
Sequence source:
LEGIONELLA PNEUMOPHILA SUBSP. PNEUMOPHILA (STRAIN PHILADELPHIA 1 / ATCC 33152 / DSM 7513)

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 Q5ZSA7 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q5ZSA7|DDL_LEGPH D-alanine--D-alanine ligase OS=Legionella pneumophila subsp. pneumophila (strain Philadelphia 1 / ATCC 33152 / DSM 7513) OX=272624 GN=ddl PE=3 SV=2 MSKPVNLVLLYGGKSGEHEVSLVSAASVLKHLDSEKYHIIPIAMDKSGRFHRHDYNDLLACSDKLPVVTEKSTPLEGLLINGRLAVDAKIVFPVVHGPLYEDGCLQGLLELAGVAYVGCDVLSSAIGMDKDMARRLACINGLKSARYKLLSWHANASERQQFCHEVASEFGWPLFVKPCSLGSSVGIHKANNMDELNAAVADALRYDEEILVEEFIVGREIELAVLENSIPCGKPRVSMVGEIKVNHPDGYYSYTAKYLESSQTDLIIPAQLNNSLEEQLKQAAANIFSYLKCKGMARVDFFVNDKTEEIYFNEINTLPGFTSISMYPKLWQATGIAYPDLLDELINLAMVHHNCRQHLVTNYL

Q5ZSA7 AF NFT

MOLNFT AF v1

NFT data

MOLNFT Q5ZSA7 research and analysis (ICN3D with VR)

FASTA sequences

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