B3QSH0 AF NFT

DNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeie3fgptubywi6sh7szjcwlia36yee6gmaxuekls2nmrifhikrf66m/metadata.json
IPFS of structure file: 
bafybeiaw7lz2klyqfig64q66lkfni5ciptgj4yqczg4jv5bcz3ickn6oq4/AF-B3QSH0-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x55F166d9F6A3981E60dDA03De65e7EbdD73842e2
First NFT owner address (bech32): 
genesis12hckdk0k5wvpucxa5q77vhn7hhtnsshz6r40vx
Current NFT ID #102384 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
102384
Accession (UniProt):
B3QSH0
Name::
DNA ligase
Experimental Method:
Predicted structure
Sequence source:
Chloroherpeton thalassium (strain ATCC 35110 / GB-78)

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 B3QSH0 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B3QSH0|DNLJ_CHLT3 DNA ligase OS=Chloroherpeton thalassium (strain ATCC 35110 / GB-78) OX=517418 GN=ligA PE=3 SV=1 MNKSEAEAKIRALRREINEHNYNYYNLAKPKISDYDFDALLRTLAELEAKYPDLVTPDSPSQRVGGEVTKNFPIVRHKTRMLSLSNTYNLGELGDFLARVAKSLESEGVQAYDFTAELKYDGVAVSLIYRDGLLVQGATRGDGSQGDEITANLKTVRTIPLRLRAPASGSAFDTEKWNGSGDIEVRGEVFMTKADFEKINAERDESEQFANPRNATAGTLKQQDSREVAKRRLTMVAYYLDGRPFADLSHGERLEKLAELGFYTGEAHRTCRSLQDIQAFLDEWENKRDALAYEIDGAVIKLNNVRYQELLGATSKSPRWAIAYKYAARRAETVLENVVFQVGRTGAITPVAELQPVKLSGSVISRSTLHNLDEIRRLDLHIGDRVIIEKSGDVIPKVVGVVAEKRPPEARTIEPLSTCPSCGTPLEHPENEVIYYCPNEFGCPAQRKARLVHFASRHAMDIEGLGEAVVEQLLGAGLIGDPGDLYFIEKTALLALERFAEKSAQNLLNGIEASKSRSFERLIFALGIRYVGRRTASILADRFTSLDTIKSASQAELCETEEIGETIAKSVALFFTKPQVQELLGKLERAGLRLASDKKSPDAPQTFAGMTVVFTGSLENFTRDDAAAKVGERGGKVTSTVSKKTSLVVAGKEAGGKLAKAEKLGVKIVTEAEFQTMLAAESGD