Q5UBY2 AF NFT

Protein FAR1-RELATED SEQUENCE 1

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiaiftrnohscnjmav6uyf7d7alrekz7bew3vopkxlpcewf54alraz4/metadata.json
IPFS of structure file: 
bafybeic7mc4c5cmkyhjfrn26diljj2n76qrgnkyn56z45paj5hrtbvio6u/AF-Q5UBY2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x84F78d27b9595c910E0E436dbec1b606A330c73d
First NFT owner address (bech32): 
genesis1snmc6faet9wfzrswgdkmasdkq63np3eag5jguq
Current NFT ID #136319 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
136319
Accession (UniProt):
Q5UBY2
Name::
Protein FAR1-RELATED SEQUENCE 1
Experimental Method:
Predicted structure
Sequence source:
ARABIDOPSIS THALIANA

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 Q5UBY2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q5UBY2|FRS1_ARATH Protein FAR1-RELATED SEQUENCE 1 OS=Arabidopsis thaliana OX=3702 GN=FRS1 PE=1 SV=1 MSSGECSNVQLDDHRKNNLEIDEGREFESKEEAFEFYKEYANSVGFTTIIKASRRSRMTGKFIDAKFVCTRYGSKKEDIDTGLGTDGFNIPQARKRGRINRSSSKTDCKAFLHVKRRQDGRWVVRSLVKEHNHEIFTGQADSLRELSGRRKLEKLNGAIVKEVKSRKLEDGDVERLLNFFTDMQVENPFFFYSIDLSEEQSLRNIFWVDAKAMHGCRPRVILTKHDQMLKEAVLEVFPSSRHCFYMWDTLGQMPEKLGHVIRLEKKLVDEINDAIYGSCQSEDFEKNWWEVVDRFHMRDNVWLQSLYEDREYWVPVYMKDVSLAGMCTAQRSDSVNSGLDKYIQRKTTFKAFLEQYKKMIQERYEEEEKSEIETLYKQPGLKSPSPFGKQMAEVYTREMFKKFQVEVLGGVACHPKKESEEDGVNKRTFRVQDYEQNRSFVVVWNSESSEVVCSCRLFELKGFLCRHAMIVLQMSGELSIPSQYVLKRWTKDAKSREVMESDQTDVESTKAQRYKDLCLRSLKLSEEASLSEESYNAVVNVLNEALRKWENKSNLIQNLEESESVTAQDLPIHEEQNNTYDMNKDDNVADTGQEYSLQEVWKVTALQEQRNRYSILDDYLSAQHMSHEMGQINSMASNRNGYCSVHQNIHSLQGQSITHPRLYETEQSSFRPEAMYERLQDMVKDLN