Q9RSH4 AF NFT

Putative membrane protein insertion efficiency factor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibgqklqzhlp5fv52scdt2isoh6rrqofox7jgbwvlnffud6pzviov4/metadata.json
IPFS of structure file: 
bafybeibhozzk2nktrjo2rjhlrm3pp5uwph4lrtpfxywwiqpus3snqn6bry/AF-Q9RSH4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x2a4F51CacdE69AF149E8aF7a5Afb18a1E9398A69
First NFT owner address (bech32): 
genesis19f84rjkdu6d0zj0g4aa947cc585nnznf2l0h22
Current NFT ID #532310 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
532310
Accession (UniProt):
Q9RSH4
Name::
Putative membrane protein insertion efficiency factor
Experimental Method:
Predicted structure
Sequence source:
DEINOCOCCUS RADIODURANS (STRAIN ATCC 13939 / DSM 20539 / JCM 16871 / LMG 4051 / NBRC 15346 / NCIMB 9279 / R1 / VKM B-1422)

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 Q9RSH4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9RSH4|YIDD_DEIRA Putative membrane protein insertion efficiency factor OS=Deinococcus radiodurans (strain ATCC 13939 / DSM 20539 / JCM 16871 / LMG 4051 / NBRC 15346 / NCIMB 9279 / R1 / VKM B-1422) OX=243230 GN=DR_2150 PE=3 SV=1 MSAAPLVRAVRWYQRVLSPRKPAPTCRFSPTCSEYAAQALDRHGALKGGWLALWRVLRCNPLVPGGFDPVPEHFPARHPRPQGSPPTDHPPTDQPS