Q3SF80 Arginine--tRNA ligase MolNFT, Molecular NFT on GenesisL1

Arginine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeihg25f7a5ele6qayovyolkgfdhtaw5eezkeazggmlzgscxw2cnx7i/metadata.json

IPFS of structure file:

bafybeiamrm6v66k4w3thddzdz2imwna3nt6s27qfii7h3oc3qdqbjkzagi/AF-Q3SF80-F1-model_v2.pdb

First NFT owner address (eip-55):

0x5881B09f2D8e743400698633641fc1cD2Ed2BE6F

First NFT owner address (bech32):

genesis1tzqmp8ed3e6rgqrfscekg87pe5hd90n0e7l5st

Current NFT ID #453127 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
453127
Accession (UniProt):
Q3SF80
Name::
Arginine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Thiobacillus denitrificans (strain ATCC 25259)

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 Q3SF80 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q3SF80|SYR_THIDA Arginine--tRNA ligase OS=Thiobacillus denitrificans (strain ATCC 25259) OX=292415 GN=argS PE=3 SV=1 MSSTHPLKDQLALLIEAALEALAPDAPVSLEIERPKNPTHGDFSSNAAMQLARPLKRNPRELAQLIVTELPASTLVAKADIAGAGFINFHLTPAAWHGIVRQVRTAGAQFGRAQRETPQRVLIEFVSANPTGPLHVGHGRQAALGDALCNLYAAQGWDVYREFYYNDAGVQIATLAASVQARARGLQPGDATWPEAAYNGDYIADIARDFLAGKTVKSDDREFTASGDVDDLDSIRQFAVAYLRHEQDLDLRAFAVHFDNYYLESSLYTDGRVDATVQRLVAAGKTYEQDGALWLRTTEYGDDKDRVMKKSDGTYTYFVPDVAYHIAKWERGFARAINIQGTDHHGTIARVRAGLQAASVGIPEGYPDYLLHTMVRVMRGGEEVKISKRAGSYVTLRDLIEWTSKDAVRFFLLSRKADTEYVFDIDLALARNNDNPVYYVQYAHARICRVFEEWSGDVATLADADLAPLEAAHELALMQRLAEYPETVASAARDLAPHLLVHYLQMLAGDFHAWYNAEKFLVADEATKRARLALADATRIVIVNGLALLGVDAPEKM

Q3SF80 AF NFT

MOLNFT AF v1

NFT data

MOLNFT Q3SF80 research and analysis (ICN3D with VR)

FASTA sequences

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