Q8CG16 AF NFT

Complement C1r-A subcomponent

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigu46ndtp2zia5hndxifygxpmgho5ge2r7gm7al5zh55elwyjvhyu/metadata.json
IPFS of structure file: 
bafybeia64jn5nyhxmdbacl7v4ggsg3zxo6lctcs7cu6bnb72kqhx6cemb4/AF-Q8CG16-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x80D2ac0F5e3268bC5C1d28BBAA07E3169BB02b79
First NFT owner address (bech32): 
genesis1srf2cr67xf5tchqa9za65plrz6dmq2me66p797
Current NFT ID #47767 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
47767
Accession (UniProt):
Q8CG16
Name::
Complement C1r-A subcomponent
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 Q8CG16 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q8CG16|C1RA_MOUSE Complement C1r-A subcomponent OS=Mus musculus OX=10090 GN=C1ra PE=1 SV=1 MWLFALLVTLFYGVEGSIYLPQKLYGEVTSPLYPKPYPSDLETTTVITVPMGYRVKLVFWQFDVEPSEGCFYDYVKISADKQTLGRFCGQLDSPLGNPPGSKEFMSQGNKMLLTFHTDFSNEENGTIMFYKGFLAYYQAVDLDECASQPNSVEEGLQPRCQHLCHNYVGGYFCSCHPGYELQKDGQSCQAECSSELYTEPSGYVSSLEYPQPYPPDLRCNYSIRVERGLTVHLKFLDPFEIDDHQQVHCPYDQLQIYANGKNLGEFCGKQRPPDLDTSSNAVDLLFFTDESGDSRGWKLHYTTETIKCPQPKALDEFTIIQDPQPQYQFRDYFIVTCKQGYQLMEGNQALLSFTAVCQNDGTWHRAMPRCKIKNCGQPQSLSNGDFRYITTKGVTTYEASIQYHCHEPYYKMLTRAGSSESMRGIYTCTAQGIWKNEEEGEKMPRCLPVCGKPVNPVTQKERIIRGQPARPGNFPWQAFTTTHGRGGGALLGDRWILTAAHTIYPKHHNKENDNANPKMLVFLGHTNVEQIKKLGHHPVRRVIIHPDYRQDEPNNFEGDIALLELENSVTLGPELLPICLPDNETFYGQGLMGYVSGFGITEDKLAFDLRFVRLPVADSEACQRWLQTKKDTSPFSQNMFCSGDPAVQQDACQGDSGGVFAVRDRNRDIWVATGIVSWGIGCGEGYGFYTKVLNYVDWIKKEMGDEN