Q3K1K8 AF NFT

DNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiehpfk73axqq3nxkw7bfozkaidvgt4sozbxfh4lnutx44zvf255ki/metadata.json
IPFS of structure file: 
bafybeiff5dq577lq4ewrjulsvzzco2xf7ocxwl5ii3d7m5ncqrhvwmejj4/AF-Q3K1K8-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xc4D46881AFD81F838F24Bb4F822bcC9938d48395
First NFT owner address (bech32): 
genesis1cn2x3qd0mq0c8reyhd8cy27vnyudfqu4apsgvw
Current NFT ID #102860 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
102860
Accession (UniProt):
Q3K1K8
Name::
DNA ligase
Experimental Method:
Predicted structure
Sequence source:
Streptococcus agalactiae serotype Ia (strain ATCC 27591 / A909 / CDC SS700)

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 Q3K1K8 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q3K1K8|DNLJ_STRA1 DNA ligase OS=Streptococcus agalactiae serotype Ia (strain ATCC 27591 / A909 / CDC SS700) OX=205921 GN=ligA PE=3 SV=1 MENRMNELVSLLNQYAKEYYTQDNPTVSDSQYDQLYRELVELEKQHPENILPNSPTHRVGGLVLEGFEKYQHEYPLYSLQDAFSKEELIAFDKRVKAEFPTAAYMAELKIDGLSVSLTYVNGVLQVGATRGDGNIGENITENLKRVHDIPLHLDQSLDITVRGECYLPKESFEAINIEKRANGEQEFANPRNAAAGTLRQLNTGIVAKRKLATFLYQEASPTQKETQDDVLKELESYGFSVNHHRLISSSMEKIWDFIQTIEKDRVSLPYDIDGIVIKVNSLAMQEELGFTVKAPRWAIAYKFPAEEKEAEILSVDWTVGRTGVVTPTANLTPVQLAGTTVSRATLHNVDYIAEKDIRIGDTVVVYKAGDIIPAVLNVVMSKRNQQEVMLIPKLCPSCGSELVHFEGEVALRCINPLCPNQIKERLAHFASRDAMNITGFGPSLVEKLFDAHLIADVADIYRLSIENLLTLDGIKEKSATKIYHAIQSSKENSAEKLLFGLGIRHVGSKASRLLLEEFGNLRQLSQASQESIASIDGLGGVIAKSLHTFFEKEEVDKLLEELTSYNVNFNYLGKRVSTDAQLSGLTVVLTGKLEKMTRNEAKEKLQNLGAKVTGSVSKKTDLIVAGSDAGSKLTKAQDLGITIQDEDWLLNL