Q95T64 AF NFT

Peptidoglycan-recognition protein LA

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifvjawim2gnedvq6zwp2hmumjd2k7ct7yneniek4vuz5z4gnn4exi/metadata.json
IPFS of structure file: 
bafybeicklwymmihxckmx6q7u2ph7qot3rdpabfnsvpw264lxy6y5axpiby/AF-Q95T64-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x04726090273ee3Cf442C951969BB1de9607d29f6
First NFT owner address (bech32): 
genesis1q3expyp88m3u73pvj5vknwcaa9s8620ky57waa
Current NFT ID #297174 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
297174
Accession (UniProt):
Q95T64
Name::
Peptidoglycan-recognition protein LA
Experimental Method:
Predicted structure
Sequence source:
DROSOPHILA MELANOGASTER

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 Q95T64 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q95T64|PGPLA_DROME Peptidoglycan-recognition protein LA OS=Drosophila melanogaster OX=7227 GN=PGRP-LA PE=1 SV=2 MFEENNSPTTDNSLWTLQGRQRASPAQRLHNLTSAGSSTSSSGLPLPQNIFTNPAIQPSSVINLNHSTDVVIGPMTQYQGPVSIYYMDYMEAHAMQTAAGINSNNANGNGNANRSRDKSPSRRVTRNTILLITLILLVLATGLIVLYVELNRPKPELPSNKAIYFGNNYDHQTFPNLGNGHLVVDREQWGASKNSHGLTIPLKRPIPYVLITHIGVQSLPCDNIYKCSIKMRTIQDSAIAEKGLPDIQSNFYVSEEGNIYVGRGWDWANTYANQTLAITFMGDYGRFKPGPKQLEGVQFLLAHAVANRNIDVDYKLVAQNQTKVTRSPGAYVYQEIRNWPHFYGCGMDEAPACGIELGMKTESWDAKQ