Q9XWN6 AF NFT

Anillin-like protein 3

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidr5q4okzpkp7wwzgfwk734wkyljtydthnd6s2jghugmzrfskr2qm/metadata.json
IPFS of structure file: 
bafybeigrv4kyhhbrue6fmqksp43pfohj6ynhhs55kxqzv53gvtk4p2wgku/AF-Q9XWN6-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x025f3b1a898b05AD2731bE6Ab72687b5920c4A3F
First NFT owner address (bech32): 
genesis1qf0nkx5f3vz66fe3he4twf58kkfqcj3lqjrpt3
Current NFT ID #16310 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
16310
Accession (UniProt):
Q9XWN6
Name::
Anillin-like protein 3
Experimental Method:
Predicted structure
Sequence source:
CAENORHABDITIS ELEGANS

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 Q9XWN6 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9XWN6|ANI3_CAEEL Anillin-like protein 3 OS=Caenorhabditis elegans OX=6239 GN=ani-3 PE=4 SV=1 MENFDGKSMPPTPVPIGSSQFYRWMPHPIVDTPPSDATWRKPVPRGRIRDLVAAFDQCSGMLEQKPPPPPTQRVESLENEHIAPPPTSKSSKIPEILAKKSEKYISPYEKRHFHGRRGTQAVVFNSNNAQNAPNVGGAYPYGATPLKLRNLAQKMDKEELYVADDVGISKKSENFENSDDDVANFQELLVLDEVLENAENSENLESQQYDEESTLNRTFQDSGVPENQENLLQLPECPKTPKFTSSPTLFTPYAAGEPIVEYRCSSGSAGGPLKIVVKKLQAPIALATSTPKPAMCRPPKHSEPPPAFQDSFVSSISNWSAVDHHATDSRRQMNRLLNSIDETRHHILLAEHSLLEAQKSKCPMQELASQRVLLICRERLKVQLEEVRRLQAMTVVRHPPPPINRHFKSTMVISNISLQFNKHFHSRGSYAFLVLLKCRTEVEATGVVTLLAQFQTPQNFILFGEHLRFSNLPVDFTIGMEIYMMRVPEHRPPEKTCAAFLAQKVRNLLVPSNAAHRRPTTSTPQKSIQNATSPACDFQLCGNLTLDRDSSGDNRRFYLDDVIYPLEGTVKLNSHCTSLPDAIDMEYRGFLHILHDSASPLERAKKVPIWHKYWSLLHRGAILFWSTPQEEVHEKVPIFQIDLTKCTNNSIEESREMSQGAEHEFHIELLIDQDPDLIEKRRVILAAESSDHLNSWLSAINDTLDILRS