New COVID-19 protease inhibitors

designed by AI with recurrent neural networks, molecular docking, and QSAR

Information about generated molecule # 37044

O=C(N[C@@H](Cc1ccccc1)[C@@H](O)Cc1ccccc1C(=O)N[C@H]1c2ccccc2O[C@H]1O)O[C@H]1CCOC1



Predicted properties

Property Value Comments
Docking score -8.7 VINA score, less is better
pIC50 (SARS, M) 5.32 bigger is better
pIC50 (HIV, M) 9.68 bigger is better
logS (M) -4.04 Solubility based on the Transformer Model, bigger is better.
Cycle >4 The cycle when the molecule was generate, the bigger cycle the more RNN is inventive.
Cardiotoxicity, hERG 0.0001 Probability of being hERG binder (0-1), less is better.
Mutagenicity, AMES 0.1635 Probability of being mutagenic (0-1), less is better.
Caco-2 permeability -5.8748 log(sm/s)
HIA, intestinal absorbtion 97.7 %
LD50, oral (rats) 2.4 -log(M)
SARS-CoV inhibition 23.0 %
Molecular weight 532.59 g/mole
This molecule was not found in references databases.

Generator summary

Random prospective compound




O=C(Nc1cnnc2ccccc12)c1cc2ccccc2cn1

COVID-19 protease

The structure has been recently solved, PDB code 6lu7. 6ul7 structure
Developed in group of Cheminformatics in the Institute of Structural Biology at Helmholtz-Zentrum Muenchen, Tetko group
With support of BIGCHEM GmBH (bigchem.de) and RULIS Ltd. (rulis.ru).