Q9U5L1 AF NFT

Signal recognition particle receptor subunit alpha homolog

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeicvc6d2dokfnbmsm7b4vbqnsh2fpmg3ik3emovzhib6pvvifkhcke/metadata.json
IPFS of structure file: 
bafybeihezsdmkxvn4og5tiwuwoax4dfcpcg3zv7decz5ktku3pjhzlx7pq/AF-Q9U5L1-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xF6092B45C6BBe716c5d0098E90A91B0f3f0fe4cA
First NFT owner address (bech32): 
genesis17cyjk3wxh0n3d3wspx8fp2gmpulslex2re984h
Current NFT ID #436824 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
436824
Accession (UniProt):
Q9U5L1
Name::
Signal recognition particle receptor subunit alpha homolog
Experimental Method:
Predicted structure
Sequence source:
DROSOPHILA MELANOGASTER

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 Q9U5L1 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9U5L1|SRPRA_DROME Signal recognition particle receptor subunit alpha homolog OS=Drosophila melanogaster OX=7227 GN=SrpRalpha PE=1 SV=2 MLDFVVIFTKGGVVLWHSNASGNSFASCINSLIRGVILEERNTEAKYYEEDHLAVQFKLDNELDLVYAAIFQKVIKLNYLDGFLADMQAAFKEKYGDIRLGDDYDFDREYRRVLSAAEEASAKQVKAPKTMRSYNESQKSKKTVASMIQDDKKPVEKRVNIQEAPPPSKSQPSSPPTGSPMDKIIMEKRRKLREKLTPTKKTSPSDSKSSKPEKAGKKPRVWDLGGNSKDAALLDRSRDSPDDVQYQNINSELVGTMQGVIRDLDVESEDEADNEDASSEGEAEEQVQSKKGKRGGLLSYFKGIVGAKTMSLADLQPALEKMRDHLISKNVASEIAAKLCDSVAASLDGKQMGTFDSIASQVKEALTESLVRILSPKRRIDIIRDALESKRNGRPYTIIFCGVNGVGKSTNLAKICFWLIENDFNVLIAACDTFRAGAVEQLRTHTRHLNALHPAAKHDGRNMVQLYEKGYGKDAAGIAMEAIKFAHDTRVDVVLVDTAGRMQDNEPLMRSLSKLIKVNNPDLVLFVGEALVGNEAVDQLVKFNQSLADYSSNENPHIIDGIVLTKFDTIDDKVGAAISMTYITGQPIVFVGTGQTYADLKAINVNAVVNSLMK