Q6K5F8 AF NFT

Cyclin-dependent kinase G-1

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeicfas5n6i7ck2ebxk7pgdpz62s6gimx4bh2n3ez4yk4g665pow5fy/metadata.json
IPFS of structure file: 
bafybeifzw4jidch3rhgjzcfwrhn77fbqmuc2dqrbypwmo4vn74x5vweri4/AF-Q6K5F8-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xF08fAe9D996f49AeeA206b8725A645c4144bB389
First NFT owner address (bech32): 
genesis17z86a8veday6a63qdwrjtfj9cs2yhvuf4q00vl
Current NFT ID #57149 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
57149
Accession (UniProt):
Q6K5F8
Name::
Cyclin-dependent kinase G-1
Experimental Method:
Predicted structure
Sequence source:
ORYZA SATIVA SUBSP. JAPONICA

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 Q6K5F8 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q6K5F8|CDKG1_ORYSJ Cyclin-dependent kinase G-1 OS=Oryza sativa subsp. japonica OX=39947 GN=CDKG-1 PE=2 SV=1 MAAGSHGGYRGYEVAREREHDVGVSRRSKEHYHHRHPSRHRDSERRRDGGRSGGRELSNGYSHRRDSPRPPPRRRPSEGRTEDREPGEVSGGSGSERSGERPMKTGEPRENGVTRVSKEEAKMSPSKKRKQSPVIWDRNGSKRQARDPVRGIREVDAVVAEIIMHQSHSLPVMSSLSSIGDGHSPMILDVSVDKVQEYEKNRIVDEEEEGYPTMRNILTSRWADAGDEEENVFVPKKKKSVSPVDSIERGSTKKVTSPESGEVLVYNSVRSSSRSSDSGVLQGSANRDLEVEKGDNIDVEEAADDDYPAGHLLDSDFEGEDCRSETPECTRSPRRCINMLQGCRSVDEFERLNTINEGTYGVVFRVRDKRTGEIVALKKVKMEKEREGFPLTSLREMNILLSFHHPSIVEVKEVVVGSNDRDIFMVMEYMEHDLKGVMETMKQPYSQSEVKCLMLQLLEGVKYLHDNWVLHRDLKTSNLLLNNRGELKICDFGLSRQYGSPLKPYTQLVVTLWYRAPELLLGAKDYSTAIDMWSLGCIMGELLSKGPLFNGKSEIDQLDKIFRTLGTPDENIWPGYSKLPGATVKFGKQTHNRLRDKFRAVSFTGGPMLSEAGFDLLNRLLTYDPEKRISAEDALNHEWFRELPLPRSKDFMPTFPALNEQDRRFKKHMKSPDPLEEQRMKEQGNNGDRGLFG