Q9W4Y2 AF NFT

PDF receptor

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeifndhjrvnn77cw3imwhxevquk2nuv6kkdkohmt75d3gb6zdam2bl4/metadata.json
IPFS of structure file: 
bafybeihmqyigsmk5pmcg3rtzdodubh4qgwdhnbhyvmgst345flveexnnne/AF-Q9W4Y2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x1356c5012d2a4B7147D097c2440ef76F9D0C0f34
First NFT owner address (bech32): 
genesis1zdtv2qfd9f9hz37sjlpygrhhd7wscre5y36qrv
Current NFT ID #290763 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
290763
Accession (UniProt):
Q9W4Y2
Name::
PDF receptor
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 Q9W4Y2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q9W4Y2|PDFR_DROME PDF receptor OS=Drosophila melanogaster OX=7227 GN=Pdfr PE=1 SV=2 MTLLSNILDCGGCISAQRFTRLLRQSGSSGPSPSAPTAGTFESKSMLEPTSSHSLATGRVPLLHDFDASTTESPGTYVLDGVARVAQLALEPTVMDALPDSDTEQVLGNLNSSAPWNLTLASAAATNFENCSALFVNYTLPQTGLYCNWTWDTLLCWPPTPAGVLARMNCPGGFHGVDTRKFAIRKCELDGRWGSRPNATEVNPPGWTDYGPCYKPEIIRLMQQMGSKDFDAYIDIARRTRTLEIVGLCLSLFALIVSLLIFCTFRSLRNNRTKIHKNLFVAMVLQVIIRLTLYLDQFRRGNKEAATNTSLSVIENTPYLCEASYVLLEYARTAMFMWMFIEGLYLHNMVTVAVFQGSFPLKFFSRLGWCVPILMTTVWARCTVMYMDTSLGECLWNYNLTPYYWILEGPRLAVILLNFCFLVNIIRVLVMKLRQSQASDIEQTRKAVRAAIVLLPLLGITNLLHQLAPLKTATNFAVWSYGTHFLTSFQGFFIALIYCFLNGEVRAVLLKSLATQLSVRGHPEWAPKRASMYSGAYNTAPDTDAVQPAGDPSATGKRISPPNKRLNGRKPSSASIVMIHEPQQRQRLMPRLQNKAREKGKDRVEKTDAEAEPDPTISHIHSKEAGSARSRTRGSKWIMGICFRGQKVLRVPSASSVPPESVVFELSEQ