Q4FPW3 AF NFT

Threonine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidjt6cwzfum3auhyopu2lrxzkgkirh537s33tjdqc5zmu5tub72fa/metadata.json
IPFS of structure file: 
bafybeibmtaavpjz6obela7yfwioaerrwwwaznj5w3oxyhi24xwrqt5axxm/AF-Q4FPW3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xAdBb5c32E453244bFe88dA9295e60cB3604b64E1
First NFT owner address (bech32): 
genesis14ka4cvhy2vjyhl5gm2fftesvkdsyke8pf3wgrp
Current NFT ID #454557 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
454557
Accession (UniProt):
Q4FPW3
Name::
Threonine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Psychrobacter arcticus (strain DSM 17307 / VKM B-2377 / 273-4)

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 Q4FPW3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q4FPW3|SYT_PSYA2 Threonine--tRNA ligase OS=Psychrobacter arcticus (strain DSM 17307 / VKM B-2377 / 273-4) OX=259536 GN=thrS PE=3 SV=1 MVAITLPDGSVKNFEGNTTVMEVAQSIGTGLAKATVAGRVDGHLVDAHDPIVADAKVEIVTPRDDDGVDIIRHSCAHLLGHAVKQLYPDVKMVIGPVIDDGFYYDIYSETPFTPEHMAAIEKRMMELIKQDYDVIKKITPRAEVIKIFEERGEDYKLKLINDMPGEEAFGLYHHQEYVDMCRGPHVPNTRFLKVFKLTKMSGAYWRGDAKNEQLQRIYGTAWADKKDLKTYIQRIEEAEKRDHRKIGKALNLFHMQEQAPGMVFWHANGWTIYQVLEQYMRKVQQDNGYEEIKTPQIVDRSLWERSGHWGNYATNMFTTSSEKRDYAVKPMNCPCHVQVFNQGLKSYRDLPLRMAEFGSCHRNEPSGSLHGLMRVRGFTQDDAHIFCTQSQIQQEVADFIKLTLAVYEDFGFNNIIMKLSTRPEKRVGSDESWDFAEKALADALDNSGLDWAYLPGEGAFYGPKIEFSLKDSLGRVWQCGTIQVDPNMPERLDAEFVNEQNEREVPIMLHRAILGSFERFIGILIENYAGWMPVWLAPQQVVVMNITDKQAEACENVVNELKKSGLRAISDLRNEKIGFKIREKTLERIPYMLVLGDKEVESGSVNVRTREGENLGVMSVAEFIILVETAVAEKGRQTPKIDQE