A7FHG1 AF NFT

Threonine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidh4udkm3whjc63xsyxp57zhxjsqmduby2vrekdedd22e6cbrqdxy/metadata.json
IPFS of structure file: 
bafybeifwb4mrvgnffabpgigz4mhckkw3gb6x3cxx4chstj5hzno5uosyqm/AF-A7FHG1-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xc0F878C3f3E2a1874e2A6daC80d429e553DdB0D5
First NFT owner address (bech32): 
genesis1cru83slnu2scwn32dkkgp4pfu4famvx4x7nssv
Current NFT ID #454771 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
454771
Accession (UniProt):
A7FHG1
Name::
Threonine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Yersinia pseudotuberculosis serotype O:1b (strain IP 31758)

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 A7FHG1 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A7FHG1|SYT_YERP3 Threonine--tRNA ligase OS=Yersinia pseudotuberculosis serotype O:1b (strain IP 31758) OX=349747 GN=thrS PE=3 SV=1 MPVITLPDGSQRHYDHAVSVLDVALDIGPGLAKACIAGRVNGELVDASDLIESDAQLAIITAKDAEGLEILRHSCAHLLGHAIKQLWPDTKMAIGPVIDNGFYYDVDIEHTLTQEDLALLEKRMHELADKDYDVIKKKVSWQEARDTFAARGEDYKVAILDENISRDDRPGLYHHEEYVDMCRGPHVPNMRFCHHFKLQKTSGAYWRGDSKNKMLQRIYGTAWGDKKQLNAYLQRLEEAAKRDHRKIGKQLDLYHMQEEAPGMVFWHNDGWTIFRELETFVRMKLKEYQYQEVKGPFMMDRVLWEKTGHWENYAEHMFTTSSENREYCIKPMNCPGHVQIFNQGLKSYRDLPLRMAEFGSCHRNEPSGALHGLMRVRGFTQDDAHVFCTEEQVRDEVNSCIKMVYDMYSTFGFEKIVVKLSTRPEKRIGSDELWTRAEDDLAAALTENGIPFDYQPGEGAFYGPKIEFTLHDCLDRAWQCGTVQLDFSLPGRLSASYIGENNDRQVPVMIHRAILGSMERFIGILTEEYAGFFPTWLAPVQVVVMNITDSQSDYVQQVTKKLQDAGIRAKADLRNEKIGFKIREHTLRRVPYMLVCGDKEVESGKIAVRTRRGKDLGSLDVNVVVDQLLAEIRSRSLHQLEE