A7I107 AF NFT

Threonine--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeidojkbwqxh5eesqcoj7zwq5jmtv3xa2iphfappekgc5biscbv7kci/metadata.json
IPFS of structure file: 
bafybeidobzexulkj5gm4m557w7b4r46elfmwa2oigyok4gfwat44bjbnbi/AF-A7I107-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x665CBc036828f0545913b4B24EA0229BB1e4F3f2
First NFT owner address (bech32): 
genesis1vewtcqmg9rc9gkgnkjeyagpznwc7fulj3rvrxp
Current NFT ID #454218 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
454218
Accession (UniProt):
A7I107
Name::
Threonine--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
Campylobacter hominis (strain ATCC BAA-381 / LMG 19568 / NCTC 13146 / CH001A)

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 A7I107 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A7I107|SYT_CAMHC Threonine--tRNA ligase OS=Campylobacter hominis (strain ATCC BAA-381 / LMG 19568 / NCTC 13146 / CH001A) OX=360107 GN=thrS PE=3 SV=1 MSDIIAYKVDGEIVDTQSFKSLKNVKNAEEIYFDNSEDALKVIRHSCAHLMAQAILALYPNAKFFVGPAIEDGFYYDFRVTKENGEKLGKEDLQAIEKKMKEFIDAKEEIAKICSTKSEIANEFKNDDLKQEVLKRIPDGEVSVYKQGDFKDICRGPHVPNTKFLRFFKLTRVAGAYLGGDEKREMLTRIYGTAFADKENLNEYLRILEEAKKRDHRIIGNEMKLFTFDDQIGAGLPVWLPNGARMRSKLEKILFGVHRRRGYEPVRGPEILKADAWKISGHYTNYKENMYFTKIDEQEYGIKPMNCVGHIKVYQSEIRSYRDLPLKFFEYGVVHRHEKSGVMHGLFRVREFTQDDAHIFCMPSQIKENVLEILDFVDKIMKNFGFSYEMEISTKPEKAIGDDKVWEIATNALKEALDENGFKYGIDEGGGAFYGPKIDIKITDALKRKWQCGTIQVDFNLPSRFDLGYIDENNERKQPVMLHRAILGSFERFIGILIEHTAGELPFFIAPTGVSIIPINDAHLNYAKEVQKALANLEVDSEILSKNETLNKRIRTAEKGRVPMILVLGDNEVKNRSVALRDRRARAQSNLSLDEFLEFVKNKLNEVNF