P13259 Choline-phosphate cytidylyltransferase MolNFT, Molecular NFT on GenesisL1

Choline-phosphate cytidylyltransferase

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeifvlweeqk34grhpnreoh7ktk6u6xff4bjhqyvwaz3oflhlr2hu75q/metadata.json

IPFS of structure file:

bafybeifytgsp6t44o22msoja3zaf6h6ijwhx42nkgdtfr3ehkwglazzza4/AF-P13259-F1-model_v2.pdb

First NFT owner address (eip-55):

0x76FE725d33d5838c54501068f07a12aAb661539b

First NFT owner address (bech32):

genesis1wml8yhfn6kpcc4zszp50q7sj42mxz5um8mwdsa

Current NFT ID #290403 owner (web3):

0x1309d1b5deb373471d3FB243145F68f72a78D518

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
290403
Accession (UniProt):
P13259
Name::
Choline-phosphate cytidylyltransferase
Experimental Method:
Predicted structure
Sequence source:
SACCHAROMYCES CEREVISIAE (STRAIN ATCC 204508 / S288C)

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 P13259 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P13259|PCY1_YEAST Choline-phosphate cytidylyltransferase OS=Saccharomyces cerevisiae (strain ATCC 204508 / S288c) OX=559292 GN=PCT1 PE=1 SV=2 MANPTTGKSSIRAKLSNSSLSNLFKKNKNKRQREETEEQDNEDKDESKNQDENKDTQLTPRKRRRLTKEFEEKEARYTNELPKELRKYRPKGFRFNLPPTDRPIRIYADGVFDLFHLGHMKQLEQCKKAFPNVTLIVGVPSDKITHKLKGLTVLTDKQRCETLTHCRWVDEVVPNAPWCVTPEFLLEHKIDYVAHDDIPYVSADSDDIYKPIKEMGKFLTTQRTNGVSTSDIITKIIRDYDKYLMRNFARGATRQELNVSWLKKNELEFKKHINEFRSYFKKNQTNLNNASRDLYFEVREILLKKTLGKKLYSKLIGNELKKQNQRQRKQNFLDDPFTRKLIREASPATEFANEFTGENSTAKSPDDNGNLFSQEDDEDTNSNNTNTNSDSDSNTNSTPPSEDDDDNDRLTLENLTQKKKQSAN

P13259 AF NFT

MOLNFT AF v1

NFT data

MOLNFT P13259 research and analysis (ICN3D with VR)

FASTA sequences

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