Q1Q7V2 AF NFT

Putative membrane protein insertion efficiency factor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeig2gjyq4jmxzxxlwpxrp63x4m654dhwhcki5jdrjzln32wk6g3gke/metadata.json
IPFS of structure file: 
bafybeia2n3nuk5teb4gmfstuuot4zy7j7kivviao6ee2cr67eawlfopj74/AF-Q1Q7V2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xa61D118041847c825681Dedc6F8f8b4D4289cd58
First NFT owner address (bech32): 
genesis15cw3rqzps37gy45pmmwxlrutf4pgnn2csqfq4u
Current NFT ID #532487 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
532487
Accession (UniProt):
Q1Q7V2
Name::
Putative membrane protein insertion efficiency factor
Experimental Method:
Predicted structure
Sequence source:
PSYCHROBACTER CRYOHALOLENTIS (STRAIN ATCC BAA-1226 / DSM 17306 / VKM B-2378 / K5)

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 Q1Q7V2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q1Q7V2|YIDD_PSYCK Putative membrane protein insertion efficiency factor OS=Psychrobacter cryohalolentis (strain ATCC BAA-1226 / DSM 17306 / VKM B-2378 / K5) OX=335284 GN=Pcryo_2474 PE=3 SV=1 MNLFIKIINKYLYKLIYNFIDFYQKIISPILPARCRYYPTCSNYGKQALAWHGVLNGSLLLLKRISRCHPLGGHGVDFVPLPLASYRYQYLSCNPVAHGQFHGFYVYRDNHGYVTRLNHMMKLT