Q54SC4 AF NFT

Probable serine/threonine-protein kinase DDB_G0282777

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifgfyqhxgbpps66cj5kiyqug5xvz3cqrpwqm27dh533jh2jplczx4/metadata.json
IPFS of structure file: 
bafybeifcljnvuzvtcbvka227pd5cefmzyrez2cmzvu2kjfbmyrlgfx7ase/AF-Q54SC4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x661f92Fc5950020C7aB410B5F5b9a3f429F49Ae5
First NFT owner address (bech32): 
genesis1vc0e9lze2qpqc745zz6ltwdr7s5lfxh9yetntg
Current NFT ID #513614 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
513614
Accession (UniProt):
Q54SC4
Name::
Probable serine/threonine-protein kinase DDB_G0282777
Experimental Method:
Predicted structure
Sequence source:
DICTYOSTELIUM DISCOIDEUM

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 Q54SC4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q54SC4|Y2777_DICDI Probable serine/threonine-protein kinase DDB_G0282777 OS=Dictyostelium discoideum OX=44689 GN=DDB_G0282777 PE=3 SV=2 MDISGFLKENKESLKDLKEDDINEILEDYEIDNINDPKQKIRFFKQVENTRKRLKIEEKNRMLEEDINRMYEEEKNRMLEEEKKEFLIKVEEEKKEFLTKVEEEKQKLKTEVEDLKSIILTSSTKNGDLKGTTSYSELFKIKNSLKLIEENCEFKDWNIPSGIELKKHVINLDDCNQESTMQSKLDEYFKDFNKKRKLIITNGTKIKINSIISNRYCDYFINQKGFPFEPYWMHMVGDIKKGSISSDTNLDQVLKYIDIIVEKSNHHVLNRPMFGFLMNKTKIKFVKYDIENNKYYITIDYDLRIGFQYLSNIMIYLEQFIRNIPNSLQTILKNHTNDSVEFYYGATSSVFIVNKEFVYKWFNYPYFFQTEVKYLTFIDGIEGTPSIKQQNQTENWIQISPRGQLIKNLEGKPIDISFYTKVFCRNTQKHTSREVIHRDIRLSNLLMDSGGDPLLVDFGFANFTENEEFYQGTMNTASNRIYNILINNRTNHAFSVVESDDLESLVKVYIMENEQAVKRTIKSIPNSEIGLFRTMWEFFNTECFPQYSTLFQQAQNINYEELKNEFIKIDKIKNTTTTSNNNQNHTNIHKNTIANTTSYTNTLETSTTNPNTNTTTSDTNTSTTSTTNTNTTTSNTITA