Q92GM7 AF NFT

DNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeia42uwu6svi4f6zlcjmg3fwzslx2neuhimwq3vqx2thkmsygyp7jq/metadata.json
IPFS of structure file: 
bafybeicvjd5lbmntlwka3i6di3ian7waatwy7abj2u4kqmhdigqf3soocq/AF-Q92GM7-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x7A8d0de136F476946697d10c096A32feA3C2aFd7
First NFT owner address (bech32): 
genesis102xsmcfk73mfge5h6yxqj63jl63u9t7hxnvwsl
Current NFT ID #102771 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
102771
Accession (UniProt):
Q92GM7
Name::
DNA ligase
Experimental Method:
Predicted structure
Sequence source:
RICKETTSIA CONORII (STRAIN ATCC VR-613 / MALISH 7)

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 Q92GM7 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q92GM7|DNLJ_RICCN DNA ligase OS=Rickettsia conorii (strain ATCC VR-613 / Malish 7) OX=272944 GN=ligA PE=3 SV=1 MQNIDLISEEEAQKLLEELADKIAAYNHAYYIEDNPLVSDSEYDQLFNTNLKLEQKFPHLILENSPSKKVGAKIANKFAKVTHQVPMLSLSNAFDEQDVRDFVDRIKIFLRLNEFAPIFCEPKIDGLSFSAVYKHGVLTTGATRGDGYVGEDITANIKTIKNFPHKIDNVPEFLEVRGEIYIEKQDFLNLNKEQEEQGKDKFANPRNAAAGSLRQLDSSITAKRPLKYFVYSGGVTEQNLASSQDQLLTKLKECGFNINEISKLASSEEEIFAFYEYLKTNRENLPYEIDGVVYKLNDFALQNRMGFIARSPRFATAHKFPAIIGQTKLLSITVQVGRTGTLTPVAELEPIEIGGVTVSRATLHNFQEIARKDLRIKDYVFLQRAGDVIPKIMGVDFDKRPNDTETFDTPLFCLSCNSKLHYTPEDIIIRCDNGLNCPAQNYERIRHFVSKNAMDIEGLGRKQVEFLIDKGLISNLLDIFFLKEKNDSSLAKLENMDGWGKKSVENLFKNIEKSKNVSLPRFIYALGIRHIGEQNAKLLAREFGSYNNFIAQMELLRTNEPDIYQKLKNLEGIGDKILVDIIDFFDVKENIELIKKLGEILNIEDYKETREQSGLTDKIVVFTGSLPTISRAEAKATAEKLGAKVAVGVSSNTDLVVAGVDAGSKLKKAKELNIKIIDEEEWLTLIKNV