Q39JU3 AF NFT

Proline--tRNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeibau66ioysbb5jqs24nw3hhdvu55fi5m46fvyra7z7dxglkftbsmi/metadata.json
IPFS of structure file: 
bafybeicswy55rexuoadcwr4zo4jpwx7hfjzfzwubcl3sptgasvsxbdvpte/AF-Q39JU3-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xd2208ADFE78260e78DbEFCf5D704c8D5Ac75625B
First NFT owner address (bech32): 
genesis16gsg4hl8sfsw0rd7ln6awpxg6kk82cjm05nfst
Current NFT ID #451583 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
451583
Accession (UniProt):
Q39JU3
Name::
Proline--tRNA ligase
Experimental Method:
Predicted structure
Sequence source:
BURKHOLDERIA LATA (STRAIN ATCC 17760 / DSM 23089 / LMG 22485 / NCIMB 9086 / R18194 / 383)

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 Q39JU3 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q39JU3|SYP_BURL3 Proline--tRNA ligase OS=Burkholderia lata (strain ATCC 17760 / DSM 23089 / LMG 22485 / NCIMB 9086 / R18194 / 383) OX=482957 GN=proS PE=3 SV=1 MKASRFFIGTLKEAPADAEIVSHKLMVRAGMIRRVAGGIYNYLPVGLRSIRKVEAIVREEMNRAGGIELLMPAVQPAELWQESGRWEQYGPELLRFKDRKDNDFVIGPTHEEVITDIARNQIKSYRQMPVNFYQIQTKFRDEIRPRFGVMRGREFIMKDAYSFDKDAAGLNESYRKMYDAYVRIFTRLGLEFRAVAADSGSIGGNFSHEFHVIADTGEDAIAYCPTSEFAANIEAAEALPLIAERAAPAEAMEKVATPGKAKCEAVAELLAIPLERTIKSIVLATDNEGAEPTIWLVMLRGDHDLNEIKVSKLPGLKNHRFATEQEIVEWFGTPPGYLGPVGTKKPVKVIADRTVANMSDFVVGANEVDYHIAGVNWGRDLPEPDVADVRNVKKGDPSPDGKGVIDICRGIEVGHVFQLGTKYSEAMGATFLDESGKPQPMLMGCYGVGVTRILGAAIEQNFDDKGIIWPESIAPFEVVLCPMGYDRSDMVRETADKLYAELVAAGIDVILDDRGERPGVMFADWELIGVPHRLVIGERGLKEGKIEYQGRRDAEATLLPADAAAATVAEKIRAALAR