Q1J0I6 AF NFT

DNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeigtjphoa53ywd5yon32isoqky46hpx7qxbbwqdivqdfjtynihspue/metadata.json
IPFS of structure file: 
bafybeib3swmatgyac7b77j6pir2pyi4wf62gujdbfy6iebivf6qfa2glmq/AF-Q1J0I6-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x94F0aFB48B380f0BD45716993326EDb0c4b82963
First NFT owner address (bech32): 
genesis1jnc2ldyt8q8sh4zhz6vnxfhdkrzts2tr0e8yks
Current NFT ID #102440 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
102440
Accession (UniProt):
Q1J0I6
Name::
DNA ligase
Experimental Method:
Predicted structure
Sequence source:
Deinococcus geothermalis (strain DSM 11300 / AG-3a)

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 Q1J0I6 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q1J0I6|DNLJ_DEIGD DNA ligase OS=Deinococcus geothermalis (strain DSM 11300 / AG-3a) OX=319795 GN=ligA PE=3 SV=1 MRGRCYASTMSQPASQVSATLEHYLALRAEIERHNRAYYELDAPEIPDDEYDRLVRELRALEAAHPEWVAENSPAQTVGGAPSSAFLPVEHPTPMTSLDNVFSDEELAEWQEKLARALNLPPDHDGFTYTGELKIDGLSVNLYYADGVLQWAATRGNGRVGEMVTEQVLTIPGIPRALPGLTGELEVRGEVYLSRADFAAFNARAEELGLPLLKNPRNGAAGALRQKDPEVTRTRHLKALFYSLGKHDGVPVRTQGEVLAWLAEQGFPTSRYSETFTGLQAAADYHRRMTAQRAQFEFDADGTVLKLDSLALQAEAGSTSRAPRWAVAYKFPVEEVETVLESITVNVGRTGKLAPLAHLSPRLIEGSTVSKATLHNEDYIRDLDLRIGDTVVVRKSGGVIPQIMRVVLEKRPPDAAPYRFPTHCPECGHEVVRAEGDANTYCPNPACPAQQFERLRYFVSRGAMDVRGVGEKLIEQLLATGLVHDAADLYQLTAEQLASLERSGEKKAANILAQLEASKTRPLWRLINALGINHVGERNAQALARAFGTLDALLAATPESIEAVPGLGRTIAQSVSAALADPSMQDLIRRLRERGLKPVEETAPRGDALAGLSFVLTGTLSRPRDEIKARLESAGARVTGSVTKKTSYLIAGEEAGSKLDRARELGIPVLDEAGLGALLEERGV