A8ADI2 AF NFT

DNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiedlxybvfjpjqwb46gvjojc65e46ffv57opiljwlu4jyxoehhzdg4/metadata.json
IPFS of structure file: 
bafybeiegcuxoax3ygqq22rwoxzjdhngduvmfgnzgyz676ipvfbw66wg7sm/AF-A8ADI2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x4Ef77Afb5a3D9F41c95Be3227D1CC986CCb61835
First NFT owner address (bech32): 
genesis1fmmh47668k05rj2muv3868xfsmxtvxp4uykwq9
Current NFT ID #102392 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
102392
Accession (UniProt):
A8ADI2
Name::
DNA ligase
Experimental Method:
Predicted structure
Sequence source:
CITROBACTER KOSERI (STRAIN ATCC BAA-895 / CDC 4225-83 / SGSC4696)

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 A8ADI2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|A8ADI2|DNLJ_CITK8 DNA ligase OS=Citrobacter koseri (strain ATCC BAA-895 / CDC 4225-83 / SGSC4696) OX=290338 GN=ligA PE=3 SV=1 MESIEQQLTELRTTLRHHEYLYHVMDAPEIPDAEYDRLMRELRELEAQHPDLITPDSPSQRVGAAPLAAFSQIRHEVPMLSLDNVFDEESFLAFNKRVQDRLKSGDKLTWCCELKLDGLAVSILYENGVLISAATRGDGTTGEDITSNVRTIRAIPLKLRGDNIPARLEVRGEVFLPQAGFEKINEEARRTGNKVFANPRNAAAGSLRQLDPRITAKRPLTFFCYGVGILEGGELPDTHLGRLLQFKAWGLPVSDRVTLCDSPEAVLDFYHKVEEDRPTLGFDIDGVVIKVNSMALQEQLGFVARAPRWAVAFKFPAQEQMTFVRDVEFQVGRTGAITPVARLEPVHVAGVLVSNATLHNADEIERLGLRIGDKVVIRRAGDVIPQVVNVVLSERPEETRPVEFPTHCPVCGSDVERVEGEAVARCTGGLICGAQRKESLKHFVSRRAMDVDGMGDKIIDQLVEKEYVHTPADLFRLTAGKLTGLDRMGPKSAQNVVNALEKAKETTFARFLYALGIREVGEATAAGLAAYFGTLEALEAASIDELQKVPDVGIVVATHVFNFFAEESNRDVIGQLLAEGIHWPAPIVVNADEIDSPFAGKTIVLTGSLSLMSRDDAKARLVALGAKVAGSVSKKTDLVIAGEAAGSKLAKAQELGIDVIDEAEMLRLLGV