Q5N2P4 AF NFT

DNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihrjoexhskz76txgbttmsw6zxqaac7wouqrx2aionwtr7pi5joy6q/metadata.json
IPFS of structure file: 
bafybeihsqpg56mxtbdhp256o7bvk22vhwhrte33ftos2tqv4cqftfyv4qu/AF-Q5N2P4-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xDECA75F0856D2EC1875f8A036e3c794d32481d05
First NFT owner address (bech32): 
genesis1mm98tuy9d5hvrp6l3gpku0ref5eys8g9snq9dp
Current NFT ID #102912 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
102912
Accession (UniProt):
Q5N2P4
Name::
DNA ligase
Experimental Method:
Predicted structure
Sequence source:
SYNECHOCOCCUS SP. (STRAIN ATCC 27144 / PCC 6301 / SAUG 1402/1)

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 Q5N2P4 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q5N2P4|DNLJ_SYNP6 DNA ligase OS=Synechococcus sp. (strain ATCC 27144 / PCC 6301 / SAUG 1402/1) OX=269084 GN=ligA PE=3 SV=1 MTASQTGPTTTAIAQRASELRQLLQQASYAYYVLDQPVMEDAVYDRLYRELQDLEQQHPSLITPDSPTQRVGEQPATGFESVQHRIPLYSLENAFDAEELRSWDQRWRKLAPDVPADAGYVCELKIDGAAIALSYENGLLVRGATRGDGTRGEEITANLRTIKSIPLRLQTDQPPEWLEVRGEAFLSLTRFKQLNTEREKHGEALFANPRNAAAGTLRQLDPRIVAERQLDFFAYSIQGPNDWANLDQAASLDCLQSLGFRVEPHRQTCPTLAEVEQYFSDWDARRRDLPYLTDGVVVKLQSRRLQDELGFTQKFPRWAIALKYPADEAPTQLQHVTVQVGRTGALTPVAEFSPVALAGTTVSRATLHNADRLRELDLHIGDTIVVRKAGEIIPEVVRVLTDLRPADAKPVVLPEKCPECGQPVQRPEEEAVTRCVNSTCPAIVRGALTHWASRDALDIEGLGEKLVDQLVSKGLVNAIADLYRLDAPLLASLERFGEKSAQNLVQAIAKSRQQPWSRVLYGLGIRHVGSVNAKNLAATFTSAEALAQATPDELAAVYGIGSEIADAVHQWFTVATNQNLIAALEQAGLQLHGEAASPRSQALAGQTFVLTGTLPTLSRNEAKALIEAAGGKVSGSVSKKTSYVVAGEEAGSKLEKAIALNIPQLNETQLLDLLAQAEG