P14785 G2/mitotic-specific cyclin-A MolNFT, Molecular NFT on GenesisL1

G2/mitotic-specific cyclin-A

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeifpem6dejtuydknayoqeuh343v6b34r5q3ctz66ezhf4ki6txqhvu/metadata.json

IPFS of structure file:

bafybeiahxi6yv3x3kn2capi622u2ej24pp5kds45eojdc2kfgc75yhlleq/AF-P14785-F1-model_v2.pdb

First NFT owner address (eip-55):

0x0E31920A67aafd5e006BeA2a197680e7C7330186

First NFT owner address (bech32):

genesis1pcceyzn84t74uqrtag4pja5qulrnxqvxq3f4zu

Current NFT ID #55337 owner (web3):

0x41f108fA06D265DE995730b2D626Bd9440871B04

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
55337
Accession (UniProt):
P14785
Name::
G2/mitotic-specific cyclin-A
Experimental Method:
Predicted structure
Sequence source:
DROSOPHILA MELANOGASTER

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 P14785 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P14785|CCNA_DROME G2/mitotic-specific cyclin-A OS=Drosophila melanogaster OX=7227 GN=CycA PE=1 SV=3 MASFQIHQDMSNKENPGIKIPAGVKNTKQPLAVIGGKAEKNALAPRANFAVLNGNNNVPRPAGKVQVFRDVRNLNVDENVEYGAKKSNVVPVVEQFKTFSVYEDNNDTQVAPSGKSLASLVDKENHDVKFGAGQKELVDYDLDSTPMSVTDVQSPMSVDRSILGVIQSSDISVGTETGVSPTGRVKELPPRNDRQRFLEVVQYQMDILEYFRESEKKHRPKPLYMRRQKDISHNMRSILIDWLVEVSEEYKLDTETLYLSVFYLDRFLSQMAVVRSKLQLVGTAAMYIAAKYEEIYPPEVGEFVFLTDDSYTKAQVLRMEQVILKILSFDLCTPTAYVFINTYAVLCDMPEKLKYMTLYISELSLMEGETYLQYLPSLMSSASVALARHILGMEMWTPRLEEITTYKLEDLKTVVLHLCHTHKTAKELNTQAMREKYNRDTYKKVAMMESVEMSKDDFDQLCEAYNCKQKEDEHQQPDINTKSNVNLFYKF

P14785 AF NFT

MOLNFT AF v1

NFT data

MOLNFT P14785 research and analysis (ICN3D with VR)

FASTA sequences

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