C0MCN7 AF NFT

Threonine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeih5rdmpgemc7vbqx4rguhn4c5ewlnoitz2ycsgqjpgslioyv7ef7q/metadata.json
IPFS of structure file: 
bafybeifxbtu2szcp2fmwlg355vz7ewafsvsatxmcmvyzuztpgtgog56j3m/AF-C0MCN7-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x9bF5F84C75690a56a78965Df98E262fC9c087f0C
First NFT owner address (bech32): 
genesis1n06lsnr4dy99dfufvh0e3cnzljwqslcvfyc43z
Current NFT ID #454695 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
454695
Accession (UniProt):
C0MCN7
Name::
Threonine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Streptococcus equi subsp. zooepidemicus (strain H70)

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 C0MCN7 research and analysis (ICN3D with VR)

FASTA sequences

>sp|C0MCN7|SYT_STRS7 Threonine--tRNA ligase OS=Streptococcus equi subsp. zooepidemicus (strain H70) OX=553483 GN=thrS PE=3 SV=1 MITITFPDGAVREFESGVTTFEIADSISKSLAKKALAGKFNGQLIDTTRAIEEDGSIEIITADHEDAFEVLRHSAAHLFAQAAKRLFPKLHLGVGPAIADGFYYDTDNADGQISNEDLPRIEEEMKKIVKENFPCIREEITKEEALELFKDDPYKVELINEHADDAAGLTVYRQGEFVDLCRGPHVPSTGRIQVFHLLNVAGAYWRGNSDNNMMQRVYGTAWFDKKDLKAYLTRLEEAKERDHRKLGKELDLFMISQEVGQGLPFWLPNGATIRRTLERYITDKELASGYQHVYTPPLASVELYKTSGHWEHYQEDMFPTMDMGDGEEFVLRPMNCPHHIQVYKNHVHSYRELPIRIAELGMMHRYEKSGALSGLQRVREMTLNDGHLFVMPEQIQEEFQRALQLIIDVYEDFNLTDYRFRLSYRDPKDTHKYYDNDEMWENAQSMLKAALDEMGVDYFEAEGEAAFYGPKLDIQVKTALGNEETLSTIQLDFLLPERFNLSYIGADGEEHRPVMIHRGVISTMERFTAILIETYKGAFPTWLAPRQVTVIPISNEAHIDYAWEVAKTLRDHGIRADVDDRNEKMQYKIRASQTSKIPYQLIVGDKEMQDKSVNVRRYGSKATHTEAISAFVDNILADIARKSRPAEG