B2GDS9 AF NFT

DNA ligase

MOLNFT AF v1 smart contract in GenesisL1 blockchain: 
0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD
IPFS of NFT metadata: 
bafybeihfn2o4uh3lhflnqoxz5ttnwx3v45fkzaebhmqdyugus6tw4qjpd4/metadata.json
IPFS of structure file: 
bafybeibukweujgwp2vc5btzxjgjjkczahiazg26sp7zuubsr4oy3njxjuq/AF-B2GDS9-F1-model_v2.pdb
First NFT owner address (eip-55): 
0x97b5432DC1040FDDCe72dc1468B30fbE934c6dc4
First NFT owner address (bech32): 
genesis1j765xtwpqs8amnnjms2x3vc0h6f5cmwyhr570y
Current NFT ID #102589 owner (web3):

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1_w

NFT id:
102589
Accession (UniProt):
B2GDS9
Name::
DNA ligase
Experimental Method:
Predicted structure
Sequence source:
Limosilactobacillus fermentum (strain NBRC 3956 / LMG 18251)

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 B2GDS9 research and analysis (ICN3D with VR)

FASTA sequences

>sp|B2GDS9|DNLJ_LIMF3 DNA ligase OS=Limosilactobacillus fermentum (strain NBRC 3956 / LMG 18251) OX=334390 GN=ligA PE=3 SV=1 MSKQEAVSELTKQQAQAELTPLREQLKKWGAEYYEQDNPSVEDYVYDRAYQRLVEIEQRFPDLVVPDSPTQRVGGAAESQLNKVTHEIPMLSMGDVFSLAELADFNRRQQDNSDVKVDFDYNLELKIDGLSLSLVYENGRLVQGSTRGNGTIGEDVTENVKTIKSIPQVLPEPLSLEFRGECYMPKEAFVKLNERREAEGQPVFANPRNAAAGSLRQLDPKVTAARQLDTFMYYVPDYQALGVTTQAQALEKMRALGFAVNPNYRVVHSQAELTAYIEEYTKKRDQLPYGIDGIVEKVNDLATQVALGNTVKVPRWEIAYKFPPEEQATVVRDIEWTVGRTGNVTPTAVMDPVQLAGTTVSRASLHNPDYLVEKDIRLGDTVLLHKAGDIIPEISRVIIEKRPADSKPYEVPTTCPECGADLVHLDDEVALRCVNPMCPAQIKEGLAHFASRNAMNIDGLGPKIIEQLWDKGMVKDVADLYRLEAAQLLTLPKFGEKSISNLLTAIANSRHNSCERLLFGLGIRHVGAKVAQLLAAEFKSVDALMAADAATISAVDSIGPIIGDAVATYFQNEQVHQLIAELKEVGVNMDYLAPTTSATESAEWAGKRVVLTGKLTKMTRGQAQEWLSARGASVTGSVSKKTDLLIAGEKAGSKLEKAQTLGIEVWDEDRFDQAMKEEN