A0QID4 AF NFT

Threonine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihdmzsn2bp56olehnxvlfwn7tirv6tqgkevbn5ix3echo223txfoe/metadata.json
IPFS of structure file: 
bafybeiff3cpmszi57t5v4hme4tonkekibntkpoqirssroag4dwkzdx22q4/AF-A0QID4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x0f9ea44ee4A7bb5204B8D5Bb20340F8E41e9B7ac
First NFT owner address (bech32): 
genesis1p702gnhy57a4yp9c6kajqdq03eq7ndavle0n2l
Current NFT ID #454452 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
454452
Accession (UniProt):
A0QID4
Name::
Threonine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
MYCOBACTERIUM AVIUM (STRAIN 104)

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 A0QID4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A0QID4|SYT_MYCA1 Threonine--tRNA ligase OS=Mycobacterium avium (strain 104) OX=243243 GN=thrS PE=3 SV=1 MTVPATDSWPAPIRVPAGTTAAAAVRDAGLPGRGAPDAVVVVRDASGTLRDLSWVPDTDAEVVPVAANTDEGRSVIRHSAAHVLAQAVQELFPQAKLGIGPPITDGFYYDFDVPEPFTPEDLDKLEKRMRQIVKEGQLFSRRVYESKEQARAELAGEPYKLELVDDKSGDPDIMEVGGDELTAYDNLNPRTRERVWGDLCRGPHIPTTRHIPAFKLTRSSAAYWRGDQNNASLQRIYGTAWESQEALDDHLRLIEEAQRRDHRKLGSELDLFSFPDEIGSGLAVFHPRGGVVRRELEEYSRRKHIEAGYEFVNTPHITKAQLFHTSGHLDWYADGMFPPMHLDAEYDDDGTVRKPGQDYYLKPMNCPMHTLIYRSRGRSYRELPLRLFEFGTVYRYEKSGVVHGLTRARGFTMDDSHIFCTREQLHGELASLLRFVLELLGDYGLTDFYLELSTKDPDKFVGSDEMWEQATTSLADVAAESGLELVPDPGGAAFYGPKISVQARDALGRSWQMSTIQVDFNFPERFELEYTASDGTRQRPVMIHRALFGSIERFFGILTEHYAGAFPAWLAPVQAVGIPVADEHVPYLESVAAQLKSHGVRVEVDASDDRMAKKIVHHTAQKVPFMLLAGDRDVAAGAVSFRFGDRTQINGVPRDSAVDAIVKWIADRENSVPSAELVKVSSGE