Q7SYC9 AF NFT

Choline transporter-like protein 2

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibsesh7rf4czlyo4kcsiwulgbxtr3whwow4ttxmfvbmcfstrt4sam/metadata.json
IPFS of structure file: 
bafybeietszr4kfubkxjvot4vyb2gdqwrobe7xfqdwofp2d7fwgkyivqym4/AF-Q7SYC9-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xB35df660264f41795De49C83276C108A4ba91ADE
First NFT owner address (bech32): 
genesis1kdwlvcpxfaqhjh0ynjpjwmqs3f96jxk780zc93
Current NFT ID #80211 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
80211
Accession (UniProt):
Q7SYC9
Name::
Choline transporter-like protein 2
Experimental Method:
Predicted structure
Sequence source:
DANIO RERIO

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 Q7SYC9 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q7SYC9|CTL2_DANRE Choline transporter-like protein 2 OS=Danio rerio OX=7955 GN=slc44a2 PE=2 SV=1 MDMEEKPKYGEPRKFDPSFKGPIQNRGCTDIVCCIIFIIAILGYLAVGILAWTHGDPRKVIYPTDSMGQFCGQGKLEKQPFLFYFNMMKCASPMVLLEFQCPTPQVCVQTCPNRTMTLITAISKPQDWEYYKSYCKEDPGHKAAAQILKEKLCPAYLVSSNPFLQRCFPSMGKKGEVITVGDQEKFSDGVNVLDAKDLMAGMKNASIVMEGRQVAMKIFEDYTKSWYWILICLLIAVVLSLIFIVLLRFLAGVMVWVMILMVVAVIAYGIAHCSIKYVSLKDTPGSNITLQQLGFQPDFAVYLHIRQTWLAFIIILAILELIIILLLIFLRNRIRVAVELMKEASRAIGYVMSSLVFPIFTFFLLAIVIAFWGVNAVFLSTSSEPVYKVFNETECVHSRETCNPENFTSSSMKSDCPHSQCLFAFYGGETPYHKYLILLQFYNVFLFFWCANFVTALGQMTLAGAFASYYWAFDKSKDMPAFPLCASLGRSLRYHTGSLAFGSLLLAIVQVIRVLLEYIDHKLKGAENKFAKFLLCCLKCCFWCLEKFIKFINRNAYIMVAIYGKNFCRSARDAFFLLMRNVVRVVVLDKVTDFILFLGKLLIVGLVGIFAFFFFSGQTDAFKGTAPSLHYYWVPILTVLVCSYLIAHGFFSVYAMCVDTLFLCFLEDLERNDGSAERPYLMSENLLNVLKKKNQAN