P87157 AF NFT

Probable ADP-ribosylation factor-binding protein C25H2.16c

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeido7vydq3okzaasqei3xzq3dir4swg3mue2edwhwtjfbq2x7kf4d4/metadata.json
IPFS of structure file: 
bafybeie6k6b2cur2767jueral4bmmdnotokwxs4dmrdgt2ng5fb7i3mn5i/AF-P87157-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x5BeA89782341f98147F2D811B063F91F0aE7D7bF
First NFT owner address (bech32): 
genesis1t04gj7prg8ucz3ljmqgmqcleru9w04al6k7v50
Current NFT ID #524564 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
524564
Accession (UniProt):
P87157
Name::
Probable ADP-ribosylation factor-binding protein C25H2.16c
Experimental Method:
Predicted structure
Sequence source:
SCHIZOSACCHAROMYCES POMBE (STRAIN 972 / ATCC 24843)

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 P87157 research and analysis (ICN3D with VR)

FASTA sequences

>sp|P87157|YB0G_SCHPO Probable ADP-ribosylation factor-binding protein C25H2.16c OS=Schizosaccharomyces pombe (strain 972 / ATCC 24843) OX=284812 GN=SPBC25H2.16c PE=1 SV=1 MSSAKRRLYSLIQNATEPYAFEPDLAVNLDIADLINQTGGNLPREAAFAIVRKVNDRNPTVAYLALNLLDICVKNCGYAFRLQIASKEFLNELVRRFPERPPSRLNKIQVMILSLIEEWRKTICRVDRYKEDLGFIRDMHRLLSYKGYTFPEIDKENLAVLSQKSVLKTAEELEKEDREAMSAKLQELIRRGTPADLAEANKLMKVMAGYDTEQKQKYKEHVLVDLEKVKRKAALFGEMLNEVSESDKLASGDLYDELAYSLKAAQRKVDKILEEMSPEDDSYVTVSDLKSLIASLLTQYDHLLEGDFSSARTVAADNNSLLQATTESAKSNSKTSANASNTQSAMDLLIDLDIGSDAQSPSLPASSSQMPTSSFNMESLSQSLLGTVEAPAEVGAISLTESFNSPVSNSSPNVPINNFTSTCAFENSHLNFQITPKSKTRDQVVLLATYTNLSPYDTVENLQSFIAVPKKYNLVLQPQSGTNLSPLQKDGIYQEMIVTKLLDVTELPVRFKLTYKVNGRSQEYTGQSSIRLL