Q0AAV2 AF NFT

DNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeiddueqqmmvuwezckzvlfknpjc5n2dki6ohm2bkdsc3v2hrzjzytwq/metadata.json
IPFS of structure file: 
bafybeigre77ctylndbju5s6queuohwqh3gkadmtqrzviwbujebxjeo2ora/AF-Q0AAV2-F1-model_v2.pdb
First NFT owner address (eip-55): 
0xd10960F956646DE8b64d3598984c91C2d5Af3D7b
First NFT owner address (bech32): 
genesis16yykp72kv3k73djdxkvfsny3ct2670tm7h5hjv
Current NFT ID #102236 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
102236
Accession (UniProt):
Q0AAV2
Name::
DNA ligase
Experimental Method:
Predicted structure
Sequence source:
Alkalilimnicola ehrlichii (strain ATCC BAA-1101 / DSM 17681 / MLHE-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 Q0AAV2 research and analysis (ICN3D with VR)

FASTA sequences

>sp|Q0AAV2|DNLJ_ALKEH DNA ligase OS=Alkalilimnicola ehrlichii (strain ATCC BAA-1101 / DSM 17681 / MLHE-1) OX=187272 GN=ligA PE=3 SV=1 MAQTGTDPQARIEALRREIREHDHRYYVLDAPVIADAEYDALMAELQALEAEHPELITPDSPSQRVAGRPAEGFGEVTHAEPMLSLDNAFEEADLAEFDRRVRQALGLDPVVYVAEPKLDGLSVSIRYEDGRLVRAGTRGDGRVGEAITENVRTIRSVPLRLRGEGWPPVMEVRGEVVIRRADFERLNEQRLADGERPFANPRNAAAGSLRQLDPRITARRRLTFFTFGVAAAGRLAASHHEVLDKLAGWGFRVNERVERVRGLDGCREYYQRLLADRDELSFEIDGVVYKVDDLDAREELGFTARAPRWAIAWKLPAQEATTVVRRILPSVGRTGAITPVAELEPVGVGGVTVSRATLHNLDEVRRKDVRKGDTVMVRRAGDVIPEITAVVTEKRPEGAEPWAMPAECPVCGSEVLRLDDEAVHRCMGGLYCPAQREGALLHFASRKALDIDGLGEKVVSQLVERGMVRSPADLFTLEHCQLAGLERMGDKSADNLVAALDKARRTTLPRFLYALGIQHVGEVTARRLAEHFGSLEAIMNADESALAETPDVGPVVAQAIAHFFAEPHNREVVQALRAAGVTWEEVDPAERGEQPLAGRTFVLTGTLSGMTRDEAKAALEALGARVSGSVSKKTDYLVAGEKAGSKLAKAESLGVEVLDEQALQALLQEHGR