Q1JI30 AF NFT

Threonine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeichbwe4mctrxqqligbajpfastpfwjxcwk4xpccbnmuvhbo42i5jse/metadata.json
IPFS of structure file: 
bafybeic2pn7guvcu6ibqlljigfxznnm3h46ykldb5gytn47zetvku53ctu/AF-Q1JI30-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x67Caacc81C91Ffe8C5b6E9623969278a00FCc789
First NFT owner address (bech32): 
genesis1vl92ejquj8l733dka93rj6f83gq0e3ufu8rlpk
Current NFT ID #454684 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
454684
Accession (UniProt):
Q1JI30
Name::
Threonine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Streptococcus pyogenes serotype M2 (strain MGAS10270)

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 Q1JI30 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q1JI30|SYT_STRPD Threonine--tRNA ligase OS=Streptococcus pyogenes serotype M2 (strain MGAS10270) OX=370552 GN=thrS PE=3 SV=1 MIKITFPDGAVREFESGVTTFDIAESISKSLAKKALAGKFNDQLIDTTRAIEEDGSIEIVTPDHKDAYEVLRHSAAHLFAQAAKRLFPNLHLGVGPAIAEGFYYDTDNAEGQISNEDLPCIEAEMQKIVTENYPCIREEVTKEEALELFKDDPYKVELINEHAGAGLTVYRQGEFVDLCRGPHVPSTGRIQVFHLLNVAGAYWRGNSDNNMMQRIYGTAWFDKKDLKAYLTRLEEAKERDHRKLGKELDLFMISQEVGQGLPFWLPDGATIRRTLERYITDKELASGYQHVYTPPLASVELYKTSGHWDHYQEDMFPVMDMGDGEEFVLRPMNCPHHIQVYKNHVRSYRELPIRIAELGMMHRYEKSGALSGLQRVREMTLNDGHIFVTPEQIQEEFQRALQLIIDVYADFNLTDYRFRLSYRDPNDTHKYYDNDEMWENAQSMLKAALDEMDVDYFEAEGEAAFYGPKLDIQVKTALGNEETLSTIQLDFLLPERFDLKYIGADGEEHRPVMIHRGVISTMERFTAILIETYKGAFPTWLAPHQVTVIPISNEAHIDYAWEVAKTLRDRGVRADVDDRNEKMQYKIRASQTSKIPYQLIVGDKEMEDKSVNVRRYGSKATHTESVEEFVENILADIARKSRPDAQA