P41245 AF NFT

Matrix metalloproteinase-9

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeig25x63gscvgshydkugad4uddu6qwo3cwe46ejyqs5ns4midpjakq/metadata.json
IPFS of structure file: 
bafybeicd7flqk4az5rure3sbbwwq27bfpygtvsuyvtoosebnevbdprhvue/AF-P41245-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xFb1Fd01bBa777F5321d3CeBE17CEDAC28290Fb4D
First NFT owner address (bech32): 
genesis1lv0aqxa6wal4xgwne6lp0nk6c2pfp76dp4375g
Current NFT ID #237165 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
237165
Accession (UniProt):
P41245
Name::
Matrix metalloproteinase-9
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 P41245 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P41245|MMP9_MOUSE Matrix metalloproteinase-9 OS=Mus musculus OX=10090 GN=Mmp9 PE=1 SV=2 MSPWQPLLLALLAFGCSSAAPYQRQPTFVVFPKDLKTSNLTDTQLAEAYLYRYGYTRAAQMMGEKQSLRPALLMLQKQLSLPQTGELDSQTLKAIRTPRCGVPDVGRFQTFKGLKWDHHNITYWIQNYSEDLPRDMIDDAFARAFAVWGEVAPLTFTRVYGPEADIVIQFGVAEHGDGYPFDGKDGLLAHAFPPGAGVQGDAHFDDDELWSLGKGVVIPTYYGNSNGAPCHFPFTFEGRSYSACTTDGRNDGTPWCSTTADYDKDGKFGFCPSERLYTEHGNGEGKPCVFPFIFEGRSYSACTTKGRSDGYRWCATTANYDQDKLYGFCPTRVDATVVGGNSAGELCVFPFVFLGKQYSSCTSDGRRDGRLWCATTSNFDTDKKWGFCPDQGYSLFLVAAHEFGHALGLDHSSVPEALMYPLYSYLEGFPLNKDDIDGIQYLYGRGSKPDPRPPATTTTEPQPTAPPTMCPTIPPTAYPTVGPTVGPTGAPSPGPTSSPSPGPTGAPSPGPTAPPTAGSSEASTESLSPADNPCNVDVFDAIAEIQGALHFFKDGWYWKFLNHRGSPLQGPFLTARTWPALPATLDSAFEDPQTKRVFFFSGRQMWVYTGKTVLGPRSLDKLGLGPEVTHVSGLLPRRLGKALLFSKGRVWRFDLKSQKVDPQSVIRVDKEFSGVPWNSHDIFQYQDKAYFCHGKFFWRVSFQNEVNKVDHEVNQVDDVGYVTYDLLQCP