Q95250 AF NFT

Membrane-associated progesterone receptor component 1

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeieogt2j6u4ko4mzgddpfzfkkctfd7sw2qb3izj34xbk6ygjbo6a4a/metadata.json
IPFS of structure file: 
bafybeic7akz7hnzlo5suteyl42enf2nrxkesvkzi3voian6qyjm2fu5ozm/AF-Q95250-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x403EcfA800ce17640bdC169169720B7Bf7e06A2b
First NFT owner address (bech32): 
genesis1gqlvl2qqectkgz7uz6gkjust00m7q63trkhld3
Current NFT ID #297242 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
297242
Accession (UniProt):
Q95250
Name::
Membrane-associated progesterone receptor component 1
Experimental Method:
Predicted structure
Sequence source:
SUS SCROFA

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 Q95250 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q95250|PGRC1_PIG Membrane-associated progesterone receptor component 1 OS=Sus scrofa OX=9823 GN=PGRMC1 PE=1 SV=3 MAAEDVAATGADPSELEGGGLLHEIFTSPLNLLLLGLCIFLLYKIVRGDQPAASDSDDDEPPPLPRLKRRDFTPAELRRFDGVQDPRILMAINGKVFDVTKGRKFYGPEGPYGVFAGRDASRGLATFCLDKEALKDEYDDLSDLTPAQQETLNDWDSQFTFKYHHVGKLLKEGEEPTVYSDEEEPKDESARKND