P51944 AF NFT

Cyclin-F

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeicrdzvjqxf63abhfusuybansjnjpe4j53eowy7xcemet4pftprmem/metadata.json
IPFS of structure file: 
bafybeidftwc6i46kh6gmm2bqwf36qukkgjvli3em2exv3abnocbcmkri5u/AF-P51944-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x53ef4eA89edf91901402D21891094e22555c6D4C
First NFT owner address (bech32): 
genesis120h5a2y7m7geq9qz6gvfzz2wyf24cm2vsahamc
Current NFT ID #55442 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
55442
Accession (UniProt):
P51944
Name::
Cyclin-F
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 P51944 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P51944|CCNF_MOUSE Cyclin-F OS=Mus musculus OX=10090 GN=Ccnf PE=2 SV=2 MGSGGVIHCRCAKCFCYPTKRRIKRRPRNLTILSLPEDVLFHILKWLSVGDILAVRAVHSHLKYLVDNHASVWASASFQELWPSPQNLKLFERAAEKGNFEAAVKLGIAYLYNEGLSVSDEACAEVNGLKASRFFSMAERLNTGSEPFIWLFIRPPWSVSGSCCKAVVHDSLRAECQLQRSHKASILHCLGRVLNLFEDEEKRKQARSLLEESSRQGCLISSYLLWESDRKVDMSDPGRCLHSFRKLRDYAAKGCWEAQLALAKACAGGSQLGLEGKACSESVCQLFQASQAVNKQQIFSVQKGLSDTMRYILIDWLVEVATMKDFTSLCLHLTVECVDRYLRRRLVPRYKLQLLGIACMVICTRFISKEILTIREAVWLTDNTYKYEDLVRVMGEIISALEGKIRIPTVVDYKEVLLTLVPVAPRTQHLCSFLCELTLLHTSLSIYAPARLASAALLLARLMHGQTQPWTTHLWDLTGFSYSDLVPCVLSLHKKCFHDDAPKDYRQVSLTAVKQRFEDKCYEEISREEVLSYADLCSTIGVKQESPEPPSFPSSGEIHTFLSSPSGRRSKRKRENSLQEDRGSFVTTPTAELSNQEETLLGSLLDWSLECCSGYEGDQESEGEKEGDVTAPSRLLDVTVVYLNPEEHCCQESSDEEAWPEDKIHPAPGTQAPPASAPRPLLCNRGDRAKDITTSGYSSVSSSSPISSLDGGMGGSPQSTSVLSVGSHSSTKPCHHQAKKSCLQCRPPNSPESGVHQQPVKRQNLSVHSDKDMHLAS