A2RFY5 AF NFT

Threonine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeicazubdhx63xfcsqkufh7t3facfnhhhmoy64rvp6vnhm2ct4qacyy/metadata.json
IPFS of structure file: 
bafybeibtvg3f3stuf4uke63dbpqjvlwkltp4s5on4drgqthgscvqbv7n24/AF-A2RFY5-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x5BeA89782341f98147F2D811B063F91F0aE7D7bF
First NFT owner address (bech32): 
genesis1t04gj7prg8ucz3ljmqgmqcleru9w04al6k7v50
Current NFT ID #454686 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
454686
Accession (UniProt):
A2RFY5
Name::
Threonine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Streptococcus pyogenes serotype M5 (strain Manfredo)

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 A2RFY5 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A2RFY5|SYT_STRPG Threonine--tRNA ligase OS=Streptococcus pyogenes serotype M5 (strain Manfredo) OX=160491 GN=thrS PE=3 SV=1 MIKITFPDGAVREFESGVTTFDIAESISKSLAKKALAGKFNDQLIDTTRAIEEDGSIEIVTPDHKDAYEVLRHSAAHLFAQAAKRLFPNLHLGVGPAIAEGFYYDTDNAEGQISNEDLPRIEAEMQKIVTENYPCIREEVTKEEALELFKDDPYKVELINEHAGAGLTVYRQGEFVDLCRGPHVPSTGRIQVFHLLNVAGAYWRGNSDNNMMQRIYGTAWFDKKDLKAYLTRLEEAKERDHRKLGKELDLFMISQEVGQGLPFWLPDGATIRRTLERYITDKELASGYQHVYTPPLASVELYKTSGHWDHYQEDMFPVMDMGDGEEFVLRPMNCPHHIQVYKNHVRSYRELPIRIAELGMMHRYEKSGALSGLQRVREMTLNDGHIFVTPEQIQEEFQRALQLIIDVYADFNLTDYRFRLSYRDPNDTHKYYDNDEMWENAQSMLKAALDEMGVDYFEAEGEAAFYGPKLDIQVKTALGNEETLSTIQLDFLLPERFDLKYIGADGEEHRPVMIHRGVISTMERFTAILIETYKGAFPTWLAPHQVTVIPISNEAHIDYAWEVAKTLRDRGVRADVDDRNEKMQYKIRASQTSKIPYQLIVGDKEMEDKSVNVRRYGSKATHTESVEEFVENILADIARKSRPDAQA