Q6CWX3 AF NFT

Sorting nexin-41

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiczssj2w6y6vzbnpu2u3kajajqkyhku43fw4xb4ov6sttfsjylkqu/metadata.json
IPFS of structure file: 
bafybeigv5ot6ozovjmtbfru5ilz5kvuxye7v7dp5iksekih3xwztrf4wg4/AF-Q6CWX3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x2286c6C31A3636A92d0a0BE4443E4A3e89CDa574
First NFT owner address (bech32): 
genesis1y2rvdsc6xcm2jtg2p0jyg0j286yumft5gve0vy
Current NFT ID #432049 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
432049
Accession (UniProt):
Q6CWX3
Name::
Sorting nexin-41
Experimental Method:
Predicted structure
Sequence source:
KLUYVEROMYCES LACTIS (STRAIN ATCC 8585 / CBS 2359 / DSM 70799 / NBRC 1267 / NRRL Y-1140 / WM37)

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 Q6CWX3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q6CWX3|SNX41_KLULA Sorting nexin-41 OS=Kluyveromyces lactis (strain ATCC 8585 / CBS 2359 / DSM 70799 / NBRC 1267 / NRRL Y-1140 / WM37) OX=284590 GN=SNX41 PE=3 SV=1 MNVFDGSDEEDNNPFSGTTHLYASGIAAVTDGPDDYDFTEPSINGSSDENAQSNAVAEPIEETDEPAEEIDDDTLQTWRFASAELSRSSAFETSYTNLLGQGKNPEVIRIVDAGQYRDIYGKYAIGYKIEFGGIVVTRRYSEFDSLRQSLCRLLPTIIIPPIPSKHPIIKYLFNPLHAKKDIKIIERRQRLLSRFLNNCHKVREIRNHIVFQKFLNPEYFWKEVLNTPPISILPMNNLLAPPLNPTKPSPIHLLLPTPTVLTMRKHEQLIGRNDVMEIKFADYDSDLIRYKAILQPLNKTVRSIRSNIQTYSAVLSELGAYFNAFSLENSVFQVSALFEQMNRLSMGIEKTGQAIDVNYVSAEIFSEAIMISLEEGSKEMLQFIHEAQRVLHFRNFKQEQFYTIETTIKKRKDRIRELKEADLQAVRLGEALKLNAEESPTVAQVMDSMTRKSANKNHTDKQIMGLFRSSASPNNKSGSDSISSEVEPHLLTKDERVVQVNKLEKELEKLNECFKLIEKDLQQVNESMDNSLNNLEKYFHEKWFLIFRELAHNITSWLKDCSESWKNAKQSIDSI