Q80ZE3 AF NFT

Sialic acid-binding Ig-like lectin 10

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibikujhqplddk2n4m62f4zattioe5whqtfdivr73qtr6sdbsv7fzq/metadata.json
IPFS of structure file: 
bafybeidufma6qngxhdrscrdlbpoywgyw337cfkz7h7mgwiixeat7ozwp6y/AF-Q80ZE3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xb4D2d9c96b0D792d0b77e7147D724cc1F801ae58
First NFT owner address (bech32): 
genesis1knfdnjttp4uj6zmhuu286ujvc8uqrtjce36hs0
Current NFT ID #428728 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
428728
Accession (UniProt):
Q80ZE3
Name::
Sialic acid-binding Ig-like lectin 10
Experimental Method:
Predicted structure
Sequence source:
MUS MUSCULUS

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 Q80ZE3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q80ZE3|SIG10_MOUSE Sialic acid-binding Ig-like lectin 10 OS=Mus musculus OX=10090 GN=Siglec10 PE=1 SV=1 MSLLLFLLSFLLDGPQGQMESYFLQVQRIVKAQEGLCIFVPCSFSSPEGKWLNRSPLYGYWFKGIRKPSLSFPVATNNKDKVLEWEARGRFQLLGDISKKNCSLLIKDVQWGDSTNYFFRMERGFERFSFKEEFRLQVEALTQKPDIFIPEVLEPGEPVTVVCLFSWTFNQCPAPSFSWMGDAVSFQESRPHTSNYSVLSFIPGLQHHDTELTCQLDFSRMSTQRTVRLRVAYAPRSLAISIFHDNVSVPDLHENPSHLEVQQGQSLRLLCTADSQPPATLSWVLEDQVLSWSSPVGSRTLALELPWVKAGDSGHYTCQAENRLGSQQHTLDLSVLYPPQDLRVTVSQANRTVLEILRNAISLPVLEGQSLCLVCVTYSNPPANVSWAWVTQTLIPIQSSEPGVLELPLVQREHEGEFTCAAQNPLGAQRISLSLSVHYPPQMSSPSCSWEAKGLHCNCSSRAWPAPSLRWRLGEGLLEGNSSNASFTVTFSSLGPWVNSSLSLLQELGPSLWLSCESWNTHGAQTTSVLLLPDKDSATAFSKGAVLGFGITALLALCLIVVIVKTLQKKGTQEEPSRPKLSRGSTILDYINVVPKTRSLARNWKAEPDAPSRSSPLDTHFPKPKKKQKDPHFTYPGCPDPTSSSQVPVSENNPEELHYAALNFSRLRLQETQDPQDTYSDYTEVRVH