O70583 AF NFT

E3 ubiquitin-protein ligase Midline-1

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigrk2zii3yvtngsn2pk4mvijclm6hfyigsxn5usv3bhywhx4vfd4i/metadata.json
IPFS of structure file: 
bafybeicqucmk4fqkhe25zdpsd3vmtofvxoivupzoyf45xa2jfp4c5ahpde/AF-O70583-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x9e5E98E011361C5888c92e2CDb7652E02Bd5C7Ed
First NFT owner address (bech32): 
genesis1ne0f3cq3xcw93zxf9ckdkajjuq4at3ldwq49kv
Current NFT ID #473140 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
473140
Accession (UniProt):
O70583
Name::
E3 ubiquitin-protein ligase Midline-1
Experimental Method:
Predicted structure
Sequence source:
MUS MUSCULUS

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 O70583 research and analysis (ICN3D with VR)

FASTA sequences

>sp|O70583|TRI18_MOUSE E3 ubiquitin-protein ligase Midline-1 OS=Mus musculus OX=10090 GN=Mid1 PE=1 SV=2 METLESELTCPICLELFEDPLLLPCAHSLCFNCAHRILVSHCATNEPVESINAFQCPTCRHVITLSQRGLDGLKRNVTLQNIIDRFQKASVSGPNSPSETRRERAFDANTMSSAEKVLCQFCDQDPAQDAVKTCVTCEVSYCDECLKATHPNKKPFTGHRLIEPIPDSHIRGLMCLEHEDEKVNMYCVTDDQLICALCKLVGRHRDHQVAALSERYDKLKQNLESNLTNLIKRNTELETLLAKLIQTCQHVEVNASRQEAKLTEECDLLIEIIQQRRQIIGTKIKEGKVIRLRKLAQQIANCKQCLERSASLISQAEHSLKENDHARFLQTAKNITERVSMATASSQVLIPEINLNDTFDTFALDFSREKKLLECLDYLTAPNPPAIREELCTASYDTITVHWTSEDEFSVVSYELQYTIFTGQANVVNVACDGTCLLGSAGLCNSADSWMIVPNIKQNHYTVHGLQSGTKYIFTVKAINQAGSRSSEPGKLKTNSQPFRLDPKSAHRKLKVSHDNLTVERDESSSKKSHAPERFAGQGSYGVAGNVFIDSGRHYWEVVTSGSTWYAIGLAYRSAPKHEWIGKNAASWALCRCHNHWAVRHDGKETPIAPAPHLRRVGVLLDYDNGSIAFYDALSSVHLHTFHAALAQPVCPTFTVWNKCLTIVTGLPIPDHLDCTEQRP