Q63185 AF NFT

Eukaryotic translation initiation factor 2-alpha kinase 1

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifgamduarltpi7z4kpjvvqxxlde52ob4efm4sztmw3hd6ghnbeg7i/metadata.json
IPFS of structure file: 
bafybeiauoj4lczer6dl64lj6jpydphnoengrrqlopgss4suhk7ywxljl3m/AF-Q63185-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x4D2f726a53462B8485b032d4e0D605D7AED7A976
First NFT owner address (bech32): 
genesis1f5hhy6jngc4cfpdsxt2wp4s967hd02tke9da8r
Current NFT ID #108906 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
108906
Accession (UniProt):
Q63185
Name::
Eukaryotic translation initiation factor 2-alpha kinase 1
Experimental Method:
Predicted structure
Sequence source:
RATTUS NORVEGICUS

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 Q63185 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q63185|E2AK1_RAT Eukaryotic translation initiation factor 2-alpha kinase 1 OS=Rattus norvegicus OX=10116 GN=Eif2ak1 PE=1 SV=2 MLGGGSVDGERDTDDDAAGAVAAPPAIDFPAEVSDPKYDESDVPAELQVFKEPLQQPTFPFLVANQLLLVSLLEHLSHVHEPNPLHSKQVFKLLCQTFIKMGLLSSFTCSDEFSSLRLHHNRAITHLMRSAKERVRQDPCQDNSYMQKIRSREIALEAQTSRYLNEFEELAILGKGGYGRVYKVRNKLDGQHYAIKKILIKSATKTDCMKVLREVKVLAGLQHPNIVGYHTAWIEHVHVLQPQDRVPIQLPSLEVLSEHEGDRNQGGVKDNESSSSIIFAELTPEKENPLAESDVKNENNNLVSYRANLVIRSSSESESSIELQEDGLNESPLRPVVKHQLPLGHSSDVEGNFTSTDESSEDNLNLLGQTEARYHLMLHIQMQLCELSLWDWIAERNNRSRECVDEAACPYVMASVATKIFQELVEGVFYIHNMGIVHRDLKPRNIFLHGPDQQVKIGDFGLACADIIQKSADWTNRNGKGTPTHTSRVGTCLYASPEQLEGSEYDAKSDMYSLGVILLELFQPFGTEMERATVLTGVRTGRIPESLSKRCPVQAKYIQLLTGRNAAQRPSALQLLQSELFQTTGNVNLTLQMKIMEQEKEIEELKKQLSLLSQDKGLKR